处理时间#

在使用时序数据进行特征工程时，仔细选择用于计算的数据至关重要。通过使用 Woodwork 时间索引 列标注数据框，并在特征计算期间提供截止时间，Featuretools 将在进行任何计算之前自动过滤掉截止时间之后的数据。

注意

本指南侧重于对时序数据进行特征工程，但不专门针对时间序列问题的特征工程，后者是独立的机器学习问题类别。有关使用 Featuretools 进行时间序列特征工程的指南，请参见此处。

什么是时间索引？#

时间索引是数据中指定每行数据何时已知/可用的列。例如，我们来看一个客户交易表

[2]:

import featuretools as ft

es = ft.demo.load_mock_customer(return_entityset=True, random_seed=0)
es["transactions"].head()

/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/woodwork/type_sys/utils.py:33: UserWarning: Could not infer format, so each element will be parsed individually, falling back to `dateutil`. To ensure parsing is consistent and as-expected, please specify a format.
  pd.to_datetime(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/woodwork/type_sys/utils.py:33: UserWarning: Could not infer format, so each element will be parsed individually, falling back to `dateutil`. To ensure parsing is consistent and as-expected, please specify a format.
  pd.to_datetime(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/woodwork/type_sys/utils.py:33: UserWarning: Could not infer format, so each element will be parsed individually, falling back to `dateutil`. To ensure parsing is consistent and as-expected, please specify a format.
  pd.to_datetime(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/woodwork/type_sys/utils.py:33: UserWarning: Could not infer format, so each element will be parsed individually, falling back to `dateutil`. To ensure parsing is consistent and as-expected, please specify a format.
  pd.to_datetime(

[2]:

	transaction_id	session_id	transaction_time	product_id	amount	_ft_last_time
10	10	1	2014-01-01 00:00:00	5	127.64	2014-01-01 00:00:00
2	2	1	2014-01-01 00:01:05	2	109.48	2014-01-01 00:01:05
438	438	1	2014-01-01 00:02:10	3	95.06	2014-01-01 00:02:10
192	192	1	2014-01-01 00:03:15	4	78.92	2014-01-01 00:03:15
271	271	1	2014-01-01 00:04:20	3	31.54	2014-01-01 00:04:20

在此表中，每笔交易对应一行，其中 transaction_time 列指定了交易发生的时间。这意味着 transaction_time 是时间索引，因为它指示了每行中的信息何时已知并可用于特征计算。暂时忽略 _ft_last_time 列。它是 Featuretools 生成的列，稍后会讨论。

然而，并非所有日期时间列都是时间索引。考虑 customers 数据框

[3]:

es["customers"]

[3]:

	customer_id	zip_code	join_date	birthday	_ft_last_time
5	5	60091	2010-07-17 05:27:50	1984-07-28	2014-01-01 08:09:40
4	4	60091	2011-04-08 20:08:14	2006-08-15	2014-01-01 05:31:30
1	1	60091	2011-04-17 10:48:33	1994-07-18	2014-01-01 07:26:20
3	3	13244	2011-08-13 15:42:34	2003-11-21	2014-01-01 09:00:35
2	2	13244	2012-04-15 23:31:04	1986-08-18	2014-01-01 08:23:45

这里，我们有两个时间列：join_date 和 birthday。虽然这两列都可以用于构建特征，但 join_date 应该用作时间索引，因为它指示了该客户首次在数据集中可用/已知的时间。

重要提示

时间索引 定义为一行中的任何信息首次可以被使用的时间点。如果在计算特征时指定了截止时间，则时间索引值晚于截止时间的行将自动被忽略。

什么是截止时间？#

cutoff_time（截止时间）指定了行数据可用于特征计算的最后时间点。此时间点之后的任何数据将在计算特征之前被过滤掉。

例如，考虑一个带有时间戳的客户交易数据集，我们想预测客户 1、2 和 3 是否会在 1 月 1 日 04:00 到当天结束之间消费 500 美元。在为此预测问题构建特征时，我们需要确保在计算中不使用 04:00 之后的数据。

retail cutoff time diagram

我们可以使用 cutoff_time 参数将截止时间传递给 featuretools.dfs() 或 featuretools.calculate_feature_matrix()，如下所示：



[4]:


fm, features = ft.dfs(
    entityset=es,
    target_dataframe_name="customers",
    cutoff_time=pd.Timestamp("2014-1-1 04:00"),
    instance_ids=[1, 2, 3],
    cutoff_time_in_index=True,
)
fm







/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function max at 0x7f99e0108790> is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "max" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function max at 0x7f99e0108790> is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "max" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function max at 0x7f99e0108790> is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "max" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function max at 0x7f99e0108790> is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "max" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(



[4]:






  
    
      
      
      zip_code
      COUNT(sessions)
      MODE(sessions.device)
      NUM_UNIQUE(sessions.device)
      COUNT(transactions)
      MAX(transactions.amount)
      MEAN(transactions.amount)
      MIN(transactions.amount)
      MODE(transactions.product_id)
      NUM_UNIQUE(transactions.product_id)
      SKEW(transactions.amount)
      STD(transactions.amount)
      SUM(transactions.amount)
      DAY(birthday)
      DAY(join_date)
      MONTH(birthday)
      MONTH(join_date)
      WEEKDAY(birthday)
      WEEKDAY(join_date)
      YEAR(birthday)
      YEAR(join_date)
      MAX(sessions.COUNT(transactions))
      MAX(sessions.MEAN(transactions.amount))
      MAX(sessions.MIN(transactions.amount))
      MAX(sessions.NUM_UNIQUE(transactions.product_id))
      MAX(sessions.SKEW(transactions.amount))
      MAX(sessions.STD(transactions.amount))
      MAX(sessions.SUM(transactions.amount))
      MEAN(sessions.COUNT(transactions))
      MEAN(sessions.MAX(transactions.amount))
      MEAN(sessions.MEAN(transactions.amount))
      MEAN(sessions.MIN(transactions.amount))
      MEAN(sessions.NUM_UNIQUE(transactions.product_id))
      MEAN(sessions.SKEW(transactions.amount))
      MEAN(sessions.STD(transactions.amount))
      MEAN(sessions.SUM(transactions.amount))
      MIN(sessions.COUNT(transactions))
      MIN(sessions.MAX(transactions.amount))
      MIN(sessions.MEAN(transactions.amount))
      MIN(sessions.NUM_UNIQUE(transactions.product_id))
      MIN(sessions.SKEW(transactions.amount))
      MIN(sessions.STD(transactions.amount))
      MIN(sessions.SUM(transactions.amount))
      MODE(sessions.DAY(session_start))
      MODE(sessions.MODE(transactions.product_id))
      MODE(sessions.MONTH(session_start))
      MODE(sessions.WEEKDAY(session_start))
      MODE(sessions.YEAR(session_start))
      NUM_UNIQUE(sessions.DAY(session_start))
      NUM_UNIQUE(sessions.MODE(transactions.product_id))
      NUM_UNIQUE(sessions.MONTH(session_start))
      NUM_UNIQUE(sessions.WEEKDAY(session_start))
      NUM_UNIQUE(sessions.YEAR(session_start))
      SKEW(sessions.COUNT(transactions))
      SKEW(sessions.MAX(transactions.amount))
      SKEW(sessions.MEAN(transactions.amount))
      SKEW(sessions.MIN(transactions.amount))
      SKEW(sessions.NUM_UNIQUE(transactions.product_id))
      SKEW(sessions.STD(transactions.amount))
      SKEW(sessions.SUM(transactions.amount))
      STD(sessions.COUNT(transactions))
      STD(sessions.MAX(transactions.amount))
      STD(sessions.MEAN(transactions.amount))
      STD(sessions.MIN(transactions.amount))
      STD(sessions.NUM_UNIQUE(transactions.product_id))
      STD(sessions.SKEW(transactions.amount))
      STD(sessions.SUM(transactions.amount))
      SUM(sessions.MAX(transactions.amount))
      SUM(sessions.MEAN(transactions.amount))
      SUM(sessions.MIN(transactions.amount))
      SUM(sessions.NUM_UNIQUE(transactions.product_id))
      SUM(sessions.SKEW(transactions.amount))
      SUM(sessions.STD(transactions.amount))
      MODE(transactions.sessions.device)
      NUM_UNIQUE(transactions.sessions.device)
    
    
      customer_id
      time
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
    
  
  
    
      1
      2014-01-01 04:00:00
      60091
      4
      tablet
      3
      67
      139.23
      74.002836
      5.81
      4
      5
      -0.006928
      42.309717
      4958.19
      18
      17
      7
      4
      0
      6
      1994
      2011
      25.0
      85.469167
      8.74
      5.0
      0.234349
      46.905665
      1613.93
      16.75
      135.0100
      76.150425
      6.905
      5.0
      -0.126261
      42.393218
      1239.5475
      12.0
      129.00
      64.557200
      5.0
      -0.830975
      39.825249
      1025.63
      1
      4
      1
      2
      2014
      1
      3
      1
      1
      1
      1.614843
      -0.451371
      -0.233453
      1.452325
      0.0
      1.235445
      1.197406
      5.678908
      5.027226
      10.426572
      1.285833
      0.0
      0.500353
      271.917637
      540.04
      304.601700
      27.62
      20.0
      -0.505043
      169.572874
      tablet
      3
    
    
      2
      2014-01-01 04:00:00
      13244
      4
      desktop
      2
      49
      146.81
      84.700000
      12.07
      4
      5
      -0.134786
      39.289512
      4150.30
      18
      15
      8
      4
      0
      6
      1986
      2012
      16.0
      96.581000
      56.46
      5.0
      0.295458
      47.935920
      1320.64
      12.25
      142.3225
      85.197948
      26.310
      5.0
      0.011293
      39.315685
      1037.5750
      8.0
      138.38
      76.813125
      5.0
      -0.455197
      27.839228
      634.84
      1
      2
      1
      2
      2014
      1
      3
      1
      1
      1
      -0.169238
      0.459305
      0.651941
      1.815491
      0.0
      -0.966834
      -0.823347
      3.862210
      3.470527
      8.983533
      20.424007
      0.0
      0.324809
      307.743859
      569.29
      340.791792
      105.24
      20.0
      0.045171
      157.262738
      desktop
      2
    
    
      3
      2014-01-01 04:00:00
      13244
      1
      tablet
      1
      15
      146.31
      62.791333
      8.19
      1
      5
      0.618455
      47.264797
      941.87
      21
      13
      11
      8
      4
      5
      2003
      2011
      15.0
      62.791333
      8.19
      5.0
      0.618455
      47.264797
      941.87
      15.00
      146.3100
      62.791333
      8.190
      5.0
      0.618455
      47.264797
      941.8700
      15.0
      146.31
      62.791333
      5.0
      0.618455
      47.264797
      941.87
      1
      1
      1
      2
      2014
      1
      1
      1
      1
      1
      NaN
      NaN
      NaN
      NaN
      NaN
      NaN
      NaN
      NaN
      NaN
      NaN
      NaN
      NaN
      NaN
      NaN
      146.31
      62.791333
      8.19
      5.0
      0.618455
      47.264797
      tablet
      1
    
  



即使 entityset 包含了每个客户的完整交易历史，用于计算上述特征的数据也仅限于时间索引在截止时间之前（含截止时间）的数据。

使用截止时间 DataFrame#
通常，机器学习的训练样本来自不同的时间点。为了为结果特征矩阵的每一行指定一个唯一的截止时间，我们可以传递一个数据框，其中包含一列用于实例 ID，另一列用于相应的截止时间。这些列的顺序可以任意，但必须正确命名。包含实例 ID 的列必须命名为 instance_id 或与目标数据框的 index 同名。包含截止时间值的列必须命名为 time 或与目标数据框的 time_index 同名。
实例 ID 列和截止时间值列的名称应该明确。传递一个数据框，如果它既包含与目标数据框 index 同名的列，又包含名为 instance_id 的列，将会导致错误。类似地，如果截止时间数据框既包含与目标数据框 time_index 同名的列，又包含名为 time 的列，也会引发错误。

注意
只有对应于实例 ID 和截止时间的列用于计算特征。任何额外传递的列都会附加到结果特征矩阵中。这通常用于传递机器学习标签，以确保它们与特征矩阵保持一致。


[5]:


cutoff_times = pd.DataFrame()
cutoff_times["customer_id"] = [1, 2, 3, 1]
cutoff_times["time"] = pd.to_datetime(
    ["2014-1-1 04:00", "2014-1-1 05:00", "2014-1-1 06:00", "2014-1-1 08:00"]
)
cutoff_times["label"] = [True, True, False, True]
cutoff_times
fm, features = ft.dfs(
    entityset=es,
    target_dataframe_name="customers",
    cutoff_time=cutoff_times,
    cutoff_time_in_index=True,
)
fm







/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function max at 0x7f99e0108790> is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "max" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function max at 0x7f99e0108790> is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "max" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function max at 0x7f99e0108790> is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "max" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function max at 0x7f99e0108790> is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "max" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function max at 0x7f99e0108790> is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "max" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function max at 0x7f99e0108790> is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "max" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function max at 0x7f99e0108790> is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "max" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function max at 0x7f99e0108790> is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "max" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function max at 0x7f99e0108790> is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "max" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function max at 0x7f99e0108790> is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "max" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function max at 0x7f99e0108790> is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "max" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function max at 0x7f99e0108790> is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "max" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function max at 0x7f99e0108790> is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "max" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function max at 0x7f99e0108790> is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "max" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function max at 0x7f99e0108790> is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "max" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function max at 0x7f99e0108790> is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "max" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(



[5]:






  
    
      
      
      zip_code
      COUNT(sessions)
      MODE(sessions.device)
      NUM_UNIQUE(sessions.device)
      COUNT(transactions)
      MAX(transactions.amount)
      MEAN(transactions.amount)
      MIN(transactions.amount)
      MODE(transactions.product_id)
      NUM_UNIQUE(transactions.product_id)
      SKEW(transactions.amount)
      STD(transactions.amount)
      SUM(transactions.amount)
      DAY(birthday)
      DAY(join_date)
      MONTH(birthday)
      MONTH(join_date)
      WEEKDAY(birthday)
      WEEKDAY(join_date)
      YEAR(birthday)
      YEAR(join_date)
      MAX(sessions.COUNT(transactions))
      MAX(sessions.MEAN(transactions.amount))
      MAX(sessions.MIN(transactions.amount))
      MAX(sessions.NUM_UNIQUE(transactions.product_id))
      MAX(sessions.SKEW(transactions.amount))
      MAX(sessions.STD(transactions.amount))
      MAX(sessions.SUM(transactions.amount))
      MEAN(sessions.COUNT(transactions))
      MEAN(sessions.MAX(transactions.amount))
      MEAN(sessions.MEAN(transactions.amount))
      MEAN(sessions.MIN(transactions.amount))
      MEAN(sessions.NUM_UNIQUE(transactions.product_id))
      MEAN(sessions.SKEW(transactions.amount))
      MEAN(sessions.STD(transactions.amount))
      MEAN(sessions.SUM(transactions.amount))
      MIN(sessions.COUNT(transactions))
      MIN(sessions.MAX(transactions.amount))
      MIN(sessions.MEAN(transactions.amount))
      MIN(sessions.NUM_UNIQUE(transactions.product_id))
      MIN(sessions.SKEW(transactions.amount))
      MIN(sessions.STD(transactions.amount))
      MIN(sessions.SUM(transactions.amount))
      MODE(sessions.DAY(session_start))
      MODE(sessions.MODE(transactions.product_id))
      MODE(sessions.MONTH(session_start))
      MODE(sessions.WEEKDAY(session_start))
      MODE(sessions.YEAR(session_start))
      NUM_UNIQUE(sessions.DAY(session_start))
      NUM_UNIQUE(sessions.MODE(transactions.product_id))
      NUM_UNIQUE(sessions.MONTH(session_start))
      NUM_UNIQUE(sessions.WEEKDAY(session_start))
      NUM_UNIQUE(sessions.YEAR(session_start))
      SKEW(sessions.COUNT(transactions))
      SKEW(sessions.MAX(transactions.amount))
      SKEW(sessions.MEAN(transactions.amount))
      SKEW(sessions.MIN(transactions.amount))
      SKEW(sessions.NUM_UNIQUE(transactions.product_id))
      SKEW(sessions.STD(transactions.amount))
      SKEW(sessions.SUM(transactions.amount))
      STD(sessions.COUNT(transactions))
      STD(sessions.MAX(transactions.amount))
      STD(sessions.MEAN(transactions.amount))
      STD(sessions.MIN(transactions.amount))
      STD(sessions.NUM_UNIQUE(transactions.product_id))
      STD(sessions.SKEW(transactions.amount))
      STD(sessions.SUM(transactions.amount))
      SUM(sessions.MAX(transactions.amount))
      SUM(sessions.MEAN(transactions.amount))
      SUM(sessions.MIN(transactions.amount))
      SUM(sessions.NUM_UNIQUE(transactions.product_id))
      SUM(sessions.SKEW(transactions.amount))
      SUM(sessions.STD(transactions.amount))
      MODE(transactions.sessions.device)
      NUM_UNIQUE(transactions.sessions.device)
      label
    
    
      customer_id
      time
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
    
  
  
    
      1
      2014-01-01 04:00:00
      60091
      4
      tablet
      3
      67
      139.23
      74.002836
      5.81
      4
      5
      -0.006928
      42.309717
      4958.19
      18
      17
      7
      4
      0
      6
      1994
      2011
      25.0
      85.469167
      8.74
      5.0
      0.234349
      46.905665
      1613.93
      16.75
      135.01000
      76.150425
      6.90500
      5.0
      -0.126261
      42.393218
      1239.5475
      12.0
      129.00
      64.557200
      5.0
      -0.830975
      39.825249
      1025.63
      1
      4
      1
      2
      2014
      1
      3
      1
      1
      1
      1.614843
      -0.451371
      -0.233453
      1.452325
      0.0
      1.235445
      1.197406
      5.678908
      5.027226
      10.426572
      1.285833
      0.0
      0.500353
      271.917637
      540.04
      304.601700
      27.62
      20.0
      -0.505043
      169.572874
      tablet
      3
      True
    
    
      2
      2014-01-01 05:00:00
      13244
      5
      desktop
      2
      62
      146.81
      83.149355
      12.07
      4
      5
      -0.121811
      38.047944
      5155.26
      18
      15
      8
      4
      0
      6
      1986
      2012
      16.0
      96.581000
      56.46
      5.0
      0.295458
      47.935920
      1320.64
      12.40
      137.62800
      83.619281
      25.41200
      5.0
      -0.053949
      38.197555
      1031.0520
      8.0
      118.85
      76.813125
      5.0
      -0.455197
      27.839228
      634.84
      1
      2
      1
      2
      2014
      1
      4
      1
      1
      1
      -0.379092
      -1.814717
      1.082192
      1.959531
      0.0
      -0.213518
      -0.667256
      3.361547
      10.919023
      8.543351
      17.801322
      0.0
      0.316873
      266.912832
      688.14
      418.096407
      127.06
      25.0
      -0.269747
      190.987775
      desktop
      2
      True
    
    
      3
      2014-01-01 06:00:00
      13244
      4
      desktop
      2
      44
      146.31
      65.174773
      6.65
      1
      5
      0.318315
      40.349758
      2867.69
      21
      13
      11
      8
      4
      5
      2003
      2011
      17.0
      91.760000
      91.76
      5.0
      0.618455
      47.264797
      944.85
      11.00
      123.26750
      72.742004
      31.66500
      4.0
      0.286859
      39.712232
      716.9225
      1.0
      91.76
      55.579412
      1.0
      -0.289466
      35.704680
      91.76
      1
      1
      1
      2
      2014
      1
      2
      1
      1
      1
      -1.330938
      -1.060639
      0.201588
      1.874170
      -2.0
      1.722323
      -1.977878
      7.118052
      22.808351
      16.540737
      40.508892
      2.0
      0.500999
      417.557763
      493.07
      290.968018
      126.66
      16.0
      0.860577
      119.136697
      desktop
      2
      False
    
    
      1
      2014-01-01 08:00:00
      60091
      8
      mobile
      3
      126
      139.43
      71.631905
      5.81
      4
      5
      0.019698
      40.442059
      9025.62
      18
      17
      7
      4
      0
      6
      1994
      2011
      25.0
      88.755625
      26.36
      5.0
      0.640252
      46.905665
      1613.93
      15.75
      132.24625
      72.774140
      9.82375
      5.0
      -0.059515
      39.093244
      1128.2025
      12.0
      118.90
      50.623125
      5.0
      -1.038434
      30.450261
      809.97
      1
      4
      1
      2
      2014
      1
      4
      1
      1
      1
      1.946018
      -0.780493
      -0.424949
      2.440005
      0.0
      -0.312355
      0.778170
      4.062019
      7.322191
      13.759314
      6.954507
      0.0
      0.589386
      279.510713
      1057.97
      582.193117
      78.59
      40.0
      -0.476122
      312.745952
      mobile
      3
      True
    
  



现在我们可以看到，特征矩阵的每一行都是在截止时间数据框中的相应时间计算的。由于我们在不同时间计算每一行，因此可能会出现重复客户。在这种情况下，我们分别在 04:00 和 08:00 为客户 1 计算了特征向量。


训练窗口#
默认情况下，使用直到（包括）截止时间的所有数据。我们可以使用“训练窗口”来限制选择用于计算的历史数据量。
这是一个使用两小时训练窗口的示例

[6]:


window_fm, window_features = ft.dfs(
    entityset=es,
    target_dataframe_name="customers",
    cutoff_time=cutoff_times,
    cutoff_time_in_index=True,
    training_window="2 hour",
)

window_fm







/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function max at 0x7f99e0108790> is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "max" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function max at 0x7f99e0108790> is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "max" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function max at 0x7f99e0108790> is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "max" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function max at 0x7f99e0108790> is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "max" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function max at 0x7f99e0108790> is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "max" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function max at 0x7f99e0108790> is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "max" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function max at 0x7f99e0108790> is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "max" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function max at 0x7f99e0108790> is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "max" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function max at 0x7f99e0108790> is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "max" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function max at 0x7f99e0108790> is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "max" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function max at 0x7f99e0108790> is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "max" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function max at 0x7f99e0108790> is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "max" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function max at 0x7f99e0108790> is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "max" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function max at 0x7f99e0108790> is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "max" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function max at 0x7f99e0108790> is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "max" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function max at 0x7f99e0108790> is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "max" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(



[6]:






  
    
      
      
      zip_code
      COUNT(sessions)
      MODE(sessions.device)
      NUM_UNIQUE(sessions.device)
      COUNT(transactions)
      MAX(transactions.amount)
      MEAN(transactions.amount)
      MIN(transactions.amount)
      MODE(transactions.product_id)
      NUM_UNIQUE(transactions.product_id)
      SKEW(transactions.amount)
      STD(transactions.amount)
      SUM(transactions.amount)
      DAY(birthday)
      DAY(join_date)
      MONTH(birthday)
      MONTH(join_date)
      WEEKDAY(birthday)
      WEEKDAY(join_date)
      YEAR(birthday)
      YEAR(join_date)
      MAX(sessions.COUNT(transactions))
      MAX(sessions.MEAN(transactions.amount))
      MAX(sessions.MIN(transactions.amount))
      MAX(sessions.NUM_UNIQUE(transactions.product_id))
      MAX(sessions.SKEW(transactions.amount))
      MAX(sessions.STD(transactions.amount))
      MAX(sessions.SUM(transactions.amount))
      MEAN(sessions.COUNT(transactions))
      MEAN(sessions.MAX(transactions.amount))
      MEAN(sessions.MEAN(transactions.amount))
      MEAN(sessions.MIN(transactions.amount))
      MEAN(sessions.NUM_UNIQUE(transactions.product_id))
      MEAN(sessions.SKEW(transactions.amount))
      MEAN(sessions.STD(transactions.amount))
      MEAN(sessions.SUM(transactions.amount))
      MIN(sessions.COUNT(transactions))
      MIN(sessions.MAX(transactions.amount))
      MIN(sessions.MEAN(transactions.amount))
      MIN(sessions.NUM_UNIQUE(transactions.product_id))
      MIN(sessions.SKEW(transactions.amount))
      MIN(sessions.STD(transactions.amount))
      MIN(sessions.SUM(transactions.amount))
      MODE(sessions.DAY(session_start))
      MODE(sessions.MODE(transactions.product_id))
      MODE(sessions.MONTH(session_start))
      MODE(sessions.WEEKDAY(session_start))
      MODE(sessions.YEAR(session_start))
      NUM_UNIQUE(sessions.DAY(session_start))
      NUM_UNIQUE(sessions.MODE(transactions.product_id))
      NUM_UNIQUE(sessions.MONTH(session_start))
      NUM_UNIQUE(sessions.WEEKDAY(session_start))
      NUM_UNIQUE(sessions.YEAR(session_start))
      SKEW(sessions.COUNT(transactions))
      SKEW(sessions.MAX(transactions.amount))
      SKEW(sessions.MEAN(transactions.amount))
      SKEW(sessions.MIN(transactions.amount))
      SKEW(sessions.NUM_UNIQUE(transactions.product_id))
      SKEW(sessions.STD(transactions.amount))
      SKEW(sessions.SUM(transactions.amount))
      STD(sessions.COUNT(transactions))
      STD(sessions.MAX(transactions.amount))
      STD(sessions.MEAN(transactions.amount))
      STD(sessions.MIN(transactions.amount))
      STD(sessions.NUM_UNIQUE(transactions.product_id))
      STD(sessions.SKEW(transactions.amount))
      STD(sessions.SUM(transactions.amount))
      SUM(sessions.MAX(transactions.amount))
      SUM(sessions.MEAN(transactions.amount))
      SUM(sessions.MIN(transactions.amount))
      SUM(sessions.NUM_UNIQUE(transactions.product_id))
      SUM(sessions.SKEW(transactions.amount))
      SUM(sessions.STD(transactions.amount))
      MODE(transactions.sessions.device)
      NUM_UNIQUE(transactions.sessions.device)
      label
    
    
      customer_id
      time
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
    
  
  
    
      1
      2014-01-01 04:00:00
      60091
      2
      desktop
      2
      27
      139.09
      76.950370
      5.81
      4
      5
      -0.187686
      43.772157
      2077.66
      18
      17
      7
      4
      0
      6
      1994
      2011
      15.0
      85.469167
      6.78
      5.0
      0.226337
      46.905665
      1052.03
      13.500000
      135.905000
      77.802250
      6.295000
      5.000000
      -0.302319
      43.365457
      1038.830000
      12.0
      132.72
      70.135333
      5.0
      -0.830975
      39.825249
      1025.63
      1
      1
      1
      2
      2014
      1
      2
      1
      1
      1
      NaN
      NaN
      NaN
      NaN
      NaN
      NaN
      NaN
      2.121320
      4.504270
      10.842658
      0.685894
      0.000000
      0.747633
      18.667619
      271.81
      155.604500
      12.59
      10.0
      -0.604638
      86.730914
      desktop
      2
      True
    
    
      2
      2014-01-01 05:00:00
      13244
      3
      desktop
      2
      31
      146.81
      84.051935
      12.07
      4
      5
      -0.198611
      36.077146
      2605.61
      18
      15
      8
      4
      0
      6
      1986
      2012
      13.0
      96.581000
      56.46
      5.0
      0.130019
      47.935920
      1004.96
      10.333333
      134.680000
      84.413538
      30.116667
      5.000000
      -0.036670
      36.500062
      868.536667
      8.0
      118.85
      77.304615
      5.0
      -0.314918
      27.839228
      634.84
      1
      1
      1
      2
      2014
      1
      3
      1
      1
      1
      0.585583
      -1.083626
      1.659252
      1.397956
      0.000000
      1.121470
      -1.660092
      2.516611
      14.342521
      10.587085
      23.329038
      0.000000
      0.242542
      203.331699
      404.04
      253.240615
      90.35
      15.0
      -0.110009
      109.500185
      desktop
      2
      True
    
    
      3
      2014-01-01 06:00:00
      13244
      3
      desktop
      1
      29
      128.26
      66.407586
      6.65
      1
      5
      0.110145
      37.130891
      1925.82
      21
      13
      11
      8
      4
      5
      2003
      2011
      17.0
      91.760000
      91.76
      5.0
      0.531588
      36.167220
      944.85
      9.666667
      115.586667
      76.058895
      39.490000
      3.666667
      0.121061
      35.935950
      641.940000
      1.0
      91.76
      55.579412
      1.0
      -0.289466
      35.704680
      91.76
      1
      1
      1
      2
      2014
      1
      2
      1
      1
      1
      -0.722109
      -1.721498
      -1.081879
      1.566223
      -1.732051
      NaN
      -1.705607
      8.082904
      20.648490
      18.557570
      45.761028
      2.309401
      0.580573
      477.281339
      346.76
      228.176684
      118.47
      11.0
      0.242122
      71.871900
      desktop
      1
      False
    
    
      1
      2014-01-01 08:00:00
      60091
      3
      mobile
      2
      47
      139.43
      66.471277
      5.91
      4
      5
      0.047120
      38.952172
      3124.15
      18
      17
      7
      4
      0
      6
      1994
      2011
      16.0
      88.755625
      11.62
      5.0
      0.640252
      44.354104
      1420.09
      15.666667
      128.146667
      66.328250
      8.203333
      5.000000
      -0.001146
      35.709633
      1041.383333
      15.0
      118.90
      50.623125
      5.0
      -1.038434
      30.450261
      809.97
      1
      1
      1
      2
      2014
      1
      3
      1
      1
      1
      -1.732051
      0.846298
      1.344879
      1.443486
      0.000000
      1.612576
      1.606791
      0.577350
      10.415432
      19.935229
      3.016195
      0.000000
      0.906666
      330.655558
      384.44
      198.984750
      24.61
      15.0
      -0.003438
      107.128899
      mobile
      2
      True
    
  



我们可以看到，缩短训练窗口后，相同特征的计数降低了

[7]:


fm[["COUNT(transactions)"]]

window_fm[["COUNT(transactions)"]]




[7]:






  
    
      
      
      COUNT(transactions)
    
    
      customer_id
      time
      
    
  
  
    
      1
      2014-01-01 04:00:00
      27
    
    
      2
      2014-01-01 05:00:00
      31
    
    
      3
      2014-01-01 06:00:00
      29
    
    
      1
      2014-01-01 08:00:00
      47
    
  





设置最后时间索引#
Featuretools 中的训练窗口限制了计算特定特征向量时可以使用过去数据的数量。如果数据框中某行的时间索引值在训练窗口之前或之后，该行将被过滤掉。这适用于行发生在单一时间点的数据框。然而，有时一行可以存在一段持续时间。
例如，客户的会话可能包含多个交易，这些交易可能发生在不同的时间点。如果我们尝试计算用户在给定时间段内的会话数量，我们通常希望计算训练窗口期间发生过任何交易的所有会话。为了实现这一点，我们不仅需要知道会话何时开始，还需要知道何时结束。实例在数据中最后一次出现的时间存储在数据框的 _ft_last_time 列中。我们可以比较上面 sessions 数据框的时间索引和最后时间索引

[8]:


last_time_index_col = es["sessions"].ww.metadata.get("last_time_index")
es["sessions"][["session_start", last_time_index_col]].head()




[8]:






  
    
      
      session_start
      _ft_last_time
    
  
  
    
      1
      2014-01-01 00:00:00
      2014-01-01 00:16:15
    
    
      2
      2014-01-01 00:17:20
      2014-01-01 00:27:05
    
    
      3
      2014-01-01 00:28:10
      2014-01-01 00:43:20
    
    
      4
      2014-01-01 00:44:25
      2014-01-01 01:10:25
    
    
      5
      2014-01-01 01:11:30
      2014-01-01 01:22:20
    
  



通过运行 EntitySet.add_last_time_indexes()，Featuretools 可以自动为 Entityset 中的每个 DataFrame 添加最后时间索引。使用训练窗口时，如果设置了 last_time_index has，Featuretools 将检查 last_time_index 是否在训练窗口的开始时间之后。这与截止时间相结合，使得 DFS 能够发现哪些数据与给定的训练窗口相关。


排除截止时间点的数据#
cutoff_time 是数据可用于特征计算的最后时间点。如果你不想在特征计算中使用截止时间点的数据，可以在 featuretools.dfs() 或 featuretools.calculate_feature_matrix() 中将 include_cutoff_time 设置为 False 来排除这些数据。如果将其设置为 True（默认行为），将使用截止时间点的数据。

将 include_cutoff_time 设置为 False 也会影响训练窗口边缘数据是包含还是排除。以这段数据切片为例

[9]:


df = es["transactions"]
df[df["session_id"] == 1].head()




[9]:






  
    
      
      transaction_id
      session_id
      transaction_time
      product_id
      amount
      _ft_last_time
    
  
  
    
      10
      10
      1
      2014-01-01 00:00:00
      5
      127.64
      2014-01-01 00:00:00
    
    
      2
      2
      1
      2014-01-01 00:01:05
      2
      109.48
      2014-01-01 00:01:05
    
    
      438
      438
      1
      2014-01-01 00:02:10
      3
      95.06
      2014-01-01 00:02:10
    
    
      192
      192
      1
      2014-01-01 00:03:15
      4
      78.92
      2014-01-01 00:03:15
    
    
      271
      271
      1
      2014-01-01 00:04:20
      3
      31.54
      2014-01-01 00:04:20
    
  



查看数据可知，交易每 65 秒发生一次。为了检查 include_cutoff_time 如何影响训练窗口，我们可以在交易发生时计算特征，同时使用一个 65 秒的训练窗口。这将创建一个在窗口两端都有交易的训练窗口。对于此示例，我们将计算会话 ID 1 在训练窗口内的所有交易金额总和。

[10]:


from featuretools.primitives import Sum

sum_log = ft.Feature(
    es["transactions"].ww["amount"],
    parent_dataframe_name="sessions",
    primitive=Sum,
)
cutoff_time = pd.DataFrame(
    {
        "session_id": [1],
        "time": ["2014-01-01 00:04:20"],
    }
).astype({"time": "datetime64[ns]"})



当 include_cutoff_time=True 时，训练窗口中最旧的时间点 (2014-01-01 00:03:15) 被排除，而截止时间点被包含。这意味着训练窗口中只有交易 371，因此所有交易金额的总和为 31.54

[11]:


# Case1. include_cutoff_time = True
actual = ft.calculate_feature_matrix(
    features=[sum_log],
    entityset=es,
    cutoff_time=cutoff_time,
    cutoff_time_in_index=True,
    training_window="65 seconds",
    include_cutoff_time=True,
)
actual







/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(



[11]:






  
    
      
      
      SUM(transactions.amount)
    
    
      session_id
      time
      
    
  
  
    
      1
      2014-01-01 00:04:20
      31.54
    
  



而当 include_cutoff_time=False 时，训练窗口中最旧的时间点被包含，而截止时间点被排除。所以在这种情况下，交易 116 被包含，交易 371 被排除，总和为 78.92

[12]:


# Case2. include_cutoff_time = False
actual = ft.calculate_feature_matrix(
    features=[sum_log],
    entityset=es,
    cutoff_time=cutoff_time,
    cutoff_time_in_index=True,
    training_window="65 seconds",
    include_cutoff_time=False,
)
actual







/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(



[12]:






  
    
      
      
      SUM(transactions.amount)
    
    
      session_id
      time
      
    
  
  
    
      1
      2014-01-01 00:04:20
      78.92
    
  





通过舍入截止时间来近似特征#
对于每个唯一的截止时间，Featuretools 必须执行操作来选择用于计算的有效数据。如果唯一的截止时间数量相对于我们计算特征的实例数量来说非常多，那么过滤数据所花费的时间会累积起来。通过减少唯一的截止时间数量，我们可以最大程度地减少搜索和提取数据用于特征计算的开销。
减少唯一截止时间数量的一种方法是将截止时间舍入到更早的时间点。更早的截止时间对于预测建模始终是有效的——这只是意味着我们在计算该特征时没有使用所有潜在可用的数据。因此，我们通过损失少量信息来换取计算速度的提升。
为了理解何时近似有用，考虑为一个预测信用卡欺诈交易的模型计算特征。在这种情况下，一个重要的特征可能是“该卡过去平均交易金额”。虽然这个值在每次新交易发生时都会改变，但更新频率较低可能不会影响准确性。

注意
BBVA 银行在使用 Featuretools 构建信用卡欺诈预测模型时使用了近似。更多详细信息，请参阅描述相关工作的白皮书中的“实时部署注意事项”部分。

近似的频率由 featuretools.dfs() 或 featuretools.calculate_feature_matrix() 的 approximate 参数控制。例如，以下代码将以 1 天为间隔近似聚合特征

..


fm = ft.calculate_feature_matrix(features=features,
                                 entityset=es_transactions,
                                 cutoff_time=ct_transactions,
                                 approximate="1 day")


在此计算中，可以近似的特征将以 1 天为间隔计算，而不能近似的特征（例如“此交易发生在哪里？”）将在精确的截止时间计算。


辅助时间索引#
有时数据集中的信息会在创建行后进行更新或添加。这意味着某些列实际上可能在行的时间索引之后才变得已知。为了避免信息泄露，我们可以创建辅助时间索引来指示这些列何时变得已知。
Flights entityset 是一个很好的例子，说明了数据集中行中的列值在不同时间变得已知。每次行程都记录在 trip_logs 数据框中，并关联了许多时间。

[14]:


es_flight = ft.demo.load_flight(nrows=100)
es_flight
es_flight["trip_logs"].head(3)







Downloading data ...






/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/demo/flight.py:291: PerformanceWarning: Adding/subtracting object-dtype array to TimedeltaArray not vectorized.
  clean_data.loc[:, "dep_time"] = clean_data["scheduled_dep_time"] + pd.to_timedelta(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/demo/flight.py:296: PerformanceWarning: Adding/subtracting object-dtype array to TimedeltaArray not vectorized.
  clean_data.loc[:, "arr_time"] = clean_data["dep_time"] + pd.to_timedelta(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/demo/flight.py:302: PerformanceWarning: Adding/subtracting object-dtype array to TimedeltaArray not vectorized.
  clean_data["scheduled_dep_time"] + clean_data["scheduled_elapsed_time"]
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/woodwork/type_sys/utils.py:33: UserWarning: Could not infer format, so each element will be parsed individually, falling back to `dateutil`. To ensure parsing is consistent and as-expected, please specify a format.
  pd.to_datetime(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/woodwork/type_sys/utils.py:33: UserWarning: Could not infer format, so each element will be parsed individually, falling back to `dateutil`. To ensure parsing is consistent and as-expected, please specify a format.
  pd.to_datetime(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/woodwork/logical_types.py:841: FutureWarning: Downcasting behavior in `replace` is deprecated and will be removed in a future version. To retain the old behavior, explicitly call `result.infer_objects(copy=False)`. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`
  series = series.replace(ww.config.get_option("nan_values"), np.nan)
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/woodwork/logical_types.py:841: FutureWarning: Downcasting behavior in `replace` is deprecated and will be removed in a future version. To retain the old behavior, explicitly call `result.infer_objects(copy=False)`. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`
  series = series.replace(ww.config.get_option("nan_values"), np.nan)
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/woodwork/type_sys/utils.py:33: UserWarning: Could not infer format, so each element will be parsed individually, falling back to `dateutil`. To ensure parsing is consistent and as-expected, please specify a format.
  pd.to_datetime(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/woodwork/type_sys/utils.py:33: UserWarning: Could not infer format, so each element will be parsed individually, falling back to `dateutil`. To ensure parsing is consistent and as-expected, please specify a format.
  pd.to_datetime(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/woodwork/type_sys/utils.py:33: UserWarning: Could not infer format, so each element will be parsed individually, falling back to `dateutil`. To ensure parsing is consistent and as-expected, please specify a format.
  pd.to_datetime(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/woodwork/type_sys/utils.py:33: UserWarning: Could not infer format, so each element will be parsed individually, falling back to `dateutil`. To ensure parsing is consistent and as-expected, please specify a format.
  pd.to_datetime(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/woodwork/type_sys/utils.py:33: UserWarning: Could not infer format, so each element will be parsed individually, falling back to `dateutil`. To ensure parsing is consistent and as-expected, please specify a format.
  pd.to_datetime(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/woodwork/type_sys/utils.py:33: UserWarning: Could not infer format, so each element will be parsed individually, falling back to `dateutil`. To ensure parsing is consistent and as-expected, please specify a format.
  pd.to_datetime(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/woodwork/type_sys/utils.py:33: UserWarning: Could not infer format, so each element will be parsed individually, falling back to `dateutil`. To ensure parsing is consistent and as-expected, please specify a format.
  pd.to_datetime(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/woodwork/type_sys/utils.py:33: UserWarning: Could not infer format, so each element will be parsed individually, falling back to `dateutil`. To ensure parsing is consistent and as-expected, please specify a format.
  pd.to_datetime(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/woodwork/type_sys/utils.py:33: UserWarning: Could not infer format, so each element will be parsed individually, falling back to `dateutil`. To ensure parsing is consistent and as-expected, please specify a format.
  pd.to_datetime(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/woodwork/type_sys/utils.py:33: UserWarning: Could not infer format, so each element will be parsed individually, falling back to `dateutil`. To ensure parsing is consistent and as-expected, please specify a format.
  pd.to_datetime(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/woodwork/type_sys/utils.py:33: UserWarning: Could not infer format, so each element will be parsed individually, falling back to `dateutil`. To ensure parsing is consistent and as-expected, please specify a format.
  pd.to_datetime(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/woodwork/type_sys/utils.py:33: UserWarning: Could not infer format, so each element will be parsed individually, falling back to `dateutil`. To ensure parsing is consistent and as-expected, please specify a format.
  pd.to_datetime(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/woodwork/logical_types.py:841: FutureWarning: Downcasting behavior in `replace` is deprecated and will be removed in a future version. To retain the old behavior, explicitly call `result.infer_objects(copy=False)`. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`
  series = series.replace(ww.config.get_option("nan_values"), np.nan)
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/woodwork/logical_types.py:841: FutureWarning: Downcasting behavior in `replace` is deprecated and will be removed in a future version. To retain the old behavior, explicitly call `result.infer_objects(copy=False)`. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`
  series = series.replace(ww.config.get_option("nan_values"), np.nan)



[14]:






  
    
      
      trip_log_id
      flight_id
      date_scheduled
      scheduled_dep_time
      scheduled_arr_time
      dep_time
      arr_time
      dep_delay
      taxi_out
      taxi_in
      arr_delay
      diverted
      scheduled_elapsed_time
      air_time
      distance
      carrier_delay
      weather_delay
      national_airspace_delay
      security_delay
      late_aircraft_delay
      canceled
    
  
  
    
      30
      30
      AA-494:RSW->CLT
      2016-09-03
      2017-01-01 13:14:00
      2017-01-01 15:05:00
      2017-01-01 13:03:00
      2017-01-01 14:53:00
      -11.0
      12.0
      10.0
      -12.0
      False
      0 days 01:51:00
      88.0
      600.0
      0.0
      0.0
      0.0
      0.0
      0.0
      False
    
    
      38
      38
      AA-495:ATL->PHX
      2016-09-03
      2017-01-01 11:30:00
      2017-01-01 15:40:00
      2017-01-01 11:24:00
      2017-01-01 15:41:00
      -6.0
      28.0
      5.0
      1.0
      False
      0 days 04:10:00
      224.0
      1587.0
      0.0
      0.0
      0.0
      0.0
      0.0
      False
    
    
      46
      46
      AA-495:CLT->ATL
      2016-09-03
      2017-01-01 09:25:00
      2017-01-01 10:42:00
      2017-01-01 09:23:00
      2017-01-01 10:39:00
      -2.0
      18.0
      8.0
      -3.0
      False
      0 days 01:17:00
      50.0
      226.0
      0.0
      0.0
      0.0
      0.0
      0.0
      False
    
  



对于每个行程日志，时间索引是 date_scheduled，这是航空公司确定计划的出发和到达时间以及飞行路线的时间。此时，我们不知道实际出发/到达时间以及任何延误细节的其他信息。然而，在航班抵达后，我们可以知道关于行程的一切情况，因此我们可以在航班降落后的任何时间使用该信息。
通过使用辅助时间索引，我们可以向 Featuretools 指出我们的飞行日志中哪些列在航班计划时已知，以及哪些列在航班降落时已知。

在 Featuretools 中，将数据框添加到 EntitySet 时，我们可以像这样将辅助时间索引设置为到达时间
es = ft.EntitySet('Flight Data')
arr_time_columns = ['arr_delay', 'dep_delay', 'carrier_delay', 'weather_delay',
                    'national_airspace_delay', 'security_delay',
                    'late_aircraft_delay', 'canceled', 'diverted',
                    'taxi_in', 'taxi_out', 'air_time', 'dep_time']

es.add_dataframe(
    dataframe_name='trip_logs',
    dataframe=data,
    index='trip_log_id',
    make_index=True,
    time_index='date_scheduled',
    secondary_time_index={'arr_time': arr_time_columns})


通过设置辅助时间索引，我们仍然可以使用行中的延误信息，但仅当该信息变得已知时。

提示
如果您的 entityset 包含内联标签，通常最好使用辅助时间索引。如果您知道标签何时有效可用，则可以使用历史标签自动创建非常有预测性的特征。



航班预测#
让我们使用上面描述的航班示例，在不同时间创建一些特征。行程 14 是 2017 年 1 月 31 日从 CLT 飞往 PHX 的航班，行程 92 是 1 月 1 日从 PIT 飞往 DFW 的航班。我们可以在航班预定起飞前的任何时间设置截止时间，模拟在该时间点进行预测。
我们为行程 14 设置了两个不同的截止时间：一个是在航班起飞前一个多月，另一个是仅在起飞前 5 天。对于行程 92，我们只设置一个截止时间，即预定起飞前三天。

我们的截止时间数据框如下所示

[15]:


ct_flight = pd.DataFrame()
ct_flight["trip_log_id"] = [14, 14, 92]
ct_flight["time"] = pd.to_datetime(["2016-12-28", "2017-1-25", "2016-12-28"])
ct_flight["label"] = [True, True, False]
ct_flight




[15]:






  
    
      
      trip_log_id
      time
      label
    
  
  
    
      0
      14
      2016-12-28
      True
    
    
      1
      14
      2017-01-25
      True
    
    
      2
      92
      2016-12-28
      False
    
  



现在，让我们计算特征矩阵

[16]:


fm, features = ft.dfs(
    entityset=es_flight,
    target_dataframe_name="trip_logs",
    cutoff_time=ct_flight,
    cutoff_time_in_index=True,
    agg_primitives=["max"],
    trans_primitives=["month"],
)
fm[
    [
        "flights.origin",
        "flights.dest",
        "label",
        "flights.MAX(trip_logs.arr_delay)",
        "MONTH(scheduled_dep_time)",
    ]
]







/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/entityset/entityset.py:1455: FutureWarning: Setting an item of incompatible dtype is deprecated and will raise an error in a future version of pandas. Value 'nan' has dtype incompatible with bool, please explicitly cast to a compatible dtype first.
  df.loc[mask, columns] = np.nan
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/entityset/entityset.py:1455: FutureWarning: Setting an item of incompatible dtype is deprecated and will raise an error in a future version of pandas. Value 'nan' has dtype incompatible with bool, please explicitly cast to a compatible dtype first.
  df.loc[mask, columns] = np.nan
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/entityset/entityset.py:1455: FutureWarning: Setting an item of incompatible dtype is deprecated and will raise an error in a future version of pandas. Value 'nan' has dtype incompatible with bool, please explicitly cast to a compatible dtype first.
  df.loc[mask, columns] = np.nan
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/entityset/entityset.py:1455: FutureWarning: Setting an item of incompatible dtype is deprecated and will raise an error in a future version of pandas. Value 'nan' has dtype incompatible with bool, please explicitly cast to a compatible dtype first.
  df.loc[mask, columns] = np.nan
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function max at 0x7f99e0108790> is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "max" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/entityset/entityset.py:1455: FutureWarning: Setting an item of incompatible dtype is deprecated and will raise an error in a future version of pandas. Value 'nan' has dtype incompatible with bool, please explicitly cast to a compatible dtype first.
  df.loc[mask, columns] = np.nan
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/entityset/entityset.py:1455: FutureWarning: Setting an item of incompatible dtype is deprecated and will raise an error in a future version of pandas. Value 'nan' has dtype incompatible with bool, please explicitly cast to a compatible dtype first.
  df.loc[mask, columns] = np.nan
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/entityset/entityset.py:1455: FutureWarning: Setting an item of incompatible dtype is deprecated and will raise an error in a future version of pandas. Value 'nan' has dtype incompatible with bool, please explicitly cast to a compatible dtype first.
  df.loc[mask, columns] = np.nan
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/entityset/entityset.py:1455: FutureWarning: Setting an item of incompatible dtype is deprecated and will raise an error in a future version of pandas. Value 'nan' has dtype incompatible with bool, please explicitly cast to a compatible dtype first.
  df.loc[mask, columns] = np.nan
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function max at 0x7f99e0108790> is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "max" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/woodwork/logical_types.py:841: FutureWarning: Downcasting behavior in `replace` is deprecated and will be removed in a future version. To retain the old behavior, explicitly call `result.infer_objects(copy=False)`. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`
  series = series.replace(ww.config.get_option("nan_values"), np.nan)
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/woodwork/logical_types.py:841: FutureWarning: Downcasting behavior in `replace` is deprecated and will be removed in a future version. To retain the old behavior, explicitly call `result.infer_objects(copy=False)`. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`
  series = series.replace(ww.config.get_option("nan_values"), np.nan)
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/woodwork/logical_types.py:841: FutureWarning: Downcasting behavior in `replace` is deprecated and will be removed in a future version. To retain the old behavior, explicitly call `result.infer_objects(copy=False)`. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`
  series = series.replace(ww.config.get_option("nan_values"), np.nan)
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/woodwork/logical_types.py:841: FutureWarning: Downcasting behavior in `replace` is deprecated and will be removed in a future version. To retain the old behavior, explicitly call `result.infer_objects(copy=False)`. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`
  series = series.replace(ww.config.get_option("nan_values"), np.nan)



[16]:






  
    
      
      
      flights.origin
      flights.dest
      label
      flights.MAX(trip_logs.arr_delay)
      MONTH(scheduled_dep_time)
    
    
      trip_log_id
      time
      
      
      
      
      
    
  
  
    
      14
      2016-12-28
      CLT
      PHX
      True
      NaN
      1
    
    
      2017-01-25
      CLT
      PHX
      True
      33.0
      1
    
    
      92
      2016-12-28
      PIT
      DFW
      False
      NaN
      1
    
  



让我们理解输出

ct_flight 中的每个 ID-时间对都生成了一行，作为特征矩阵的索引返回。
输出按截止时间排序。由于排序的原因，通常最好在传递截止时间数据框时包含一个标签，以便它能与特征矩阵保持相同的排序方式。除了 id 和 cutoff_time 之外的任何额外列都不会用于生成特征。
列 flights.MAX(trip_logs.arr_delay) 并非总是定义。只有当存在可聚合的历史航班时，它才可能具有任何实际值。请注意，对于行程 14，我们在提前一个月创建特征时没有任何历史数据，但在缩短至 5 天时有航班可以聚合。这些是强大的特征，在手动处理中通常被排除，因为它们很难创建。



创建和展平特征张量#
featuretools.make_temporal_cutoffs() 函数根据给定的一组截止时间和实例 ID 生成一系列等间隔的截止时间。
此函数可以与 DFS 配合使用，以创建和展平特征张量，而不是在不同延迟下创建多个特征矩阵。
此函数接受以下参数

instance_ids (list, pd.Series, or np.ndarray): 实例列表。
cutoffs (list, pd.Series, or np.ndarray): 相关的截止时间列表。
window_size (str or pandas.DateOffset): 创建的时间序列中每个截止时间之间的时间间隔。
start (datetime.datetime or pd.Timestamp): 创建的时间序列中的第一个截止时间。
num_windows (int): 在创建的时间序列中要创建的截止时间数量。

只需要指定 window_size、start 和 num_windows 这三个选项中的任意两个，即可唯一确定一组等间隔的截止时间，用于计算每个实例。
如果您的截止时间是上面使用的那些

[17]:


cutoff_times




[17]:






  
    
      
      customer_id
      time
      label
    
  
  
    
      0
      1
      2014-01-01 04:00:00
      True
    
    
      1
      2
      2014-01-01 05:00:00
      True
    
    
      2
      3
      2014-01-01 06:00:00
      False
    
    
      3
      1
      2014-01-01 08:00:00
      True
    
  



然后传入 window_size='1h' 和 num_windows=2 会在过去两小时内每小时生成一行，产生以下新的数据框。结果可以直接传递给 DFS 以在不同时间点生成特征。

[18]:


temporal_cutoffs = ft.make_temporal_cutoffs(
    cutoff_times["customer_id"], cutoff_times["time"], window_size="1h", num_windows=2
)
temporal_cutoffs
fm, features = ft.dfs(
    entityset=es,
    target_dataframe_name="customers",
    cutoff_time=temporal_cutoffs,
    cutoff_time_in_index=True,
)
fm







/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function max at 0x7f99e0108790> is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "max" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function max at 0x7f99e0108790> is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "max" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function max at 0x7f99e0108790> is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "max" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function max at 0x7f99e0108790> is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "max" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function max at 0x7f99e0108790> is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "max" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function max at 0x7f99e0108790> is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "max" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function max at 0x7f99e0108790> is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "max" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function max at 0x7f99e0108790> is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "max" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function max at 0x7f99e0108790> is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "max" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function max at 0x7f99e0108790> is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "max" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function max at 0x7f99e0108790> is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "max" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function max at 0x7f99e0108790> is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "max" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function max at 0x7f99e0108790> is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "max" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function max at 0x7f99e0108790> is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "max" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function max at 0x7f99e0108790> is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "max" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function max at 0x7f99e0108790> is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "max" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function max at 0x7f99e0108790> is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "max" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function max at 0x7f99e0108790> is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "max" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function max at 0x7f99e0108790> is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "max" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function max at 0x7f99e0108790> is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "max" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function max at 0x7f99e0108790> is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "max" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function max at 0x7f99e0108790> is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "max" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function max at 0x7f99e0108790> is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "max" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function max at 0x7f99e0108790> is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "max" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function sum at 0x7f99e0108160> is currently using SeriesGroupBy.sum. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "sum" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function std at 0x7f99e010d1f0> is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "std" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function mean at 0x7f99e010d0d0> is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "mean" instead.
  to_merge = base_frame.groupby(
/home/docs/checkouts/readthedocs.org/user_builds/feature-labs-inc-featuretools/envs/stable/lib/python3.9/site-packages/featuretools/computational_backends/feature_set_calculator.py:781: FutureWarning: The provided callable <function min at 0x7f99e01088b0> is currently using SeriesGroupBy.min. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string "min" instead.
  to_merge = base_frame.groupby(



[18]:






  
    
      
      
      zip_code
      COUNT(sessions)
      MODE(sessions.device)
      NUM_UNIQUE(sessions.device)
      COUNT(transactions)
      MAX(transactions.amount)
      MEAN(transactions.amount)
      MIN(transactions.amount)
      MODE(transactions.product_id)
      NUM_UNIQUE(transactions.product_id)
      SKEW(transactions.amount)
      STD(transactions.amount)
      SUM(transactions.amount)
      DAY(birthday)
      DAY(join_date)
      MONTH(birthday)
      MONTH(join_date)
      WEEKDAY(birthday)
      WEEKDAY(join_date)
      YEAR(birthday)
      YEAR(join_date)
      MAX(sessions.COUNT(transactions))
      MAX(sessions.MEAN(transactions.amount))
      MAX(sessions.MIN(transactions.amount))
      MAX(sessions.NUM_UNIQUE(transactions.product_id))
      MAX(sessions.SKEW(transactions.amount))
      MAX(sessions.STD(transactions.amount))
      MAX(sessions.SUM(transactions.amount))
      MEAN(sessions.COUNT(transactions))
      MEAN(sessions.MAX(transactions.amount))
      MEAN(sessions.MEAN(transactions.amount))
      MEAN(sessions.MIN(transactions.amount))
      MEAN(sessions.NUM_UNIQUE(transactions.product_id))
      MEAN(sessions.SKEW(transactions.amount))
      MEAN(sessions.STD(transactions.amount))
      MEAN(sessions.SUM(transactions.amount))
      MIN(sessions.COUNT(transactions))
      MIN(sessions.MAX(transactions.amount))
      MIN(sessions.MEAN(transactions.amount))
      MIN(sessions.NUM_UNIQUE(transactions.product_id))
      MIN(sessions.SKEW(transactions.amount))
      MIN(sessions.STD(transactions.amount))
      MIN(sessions.SUM(transactions.amount))
      MODE(sessions.DAY(session_start))
      MODE(sessions.MODE(transactions.product_id))
      MODE(sessions.MONTH(session_start))
      MODE(sessions.WEEKDAY(session_start))
      MODE(sessions.YEAR(session_start))
      NUM_UNIQUE(sessions.DAY(session_start))
      NUM_UNIQUE(sessions.MODE(transactions.product_id))
      NUM_UNIQUE(sessions.MONTH(session_start))
      NUM_UNIQUE(sessions.WEEKDAY(session_start))
      NUM_UNIQUE(sessions.YEAR(session_start))
      SKEW(sessions.COUNT(transactions))
      SKEW(sessions.MAX(transactions.amount))
      SKEW(sessions.MEAN(transactions.amount))
      SKEW(sessions.MIN(transactions.amount))
      SKEW(sessions.NUM_UNIQUE(transactions.product_id))
      SKEW(sessions.STD(transactions.amount))
      SKEW(sessions.SUM(transactions.amount))
      STD(sessions.COUNT(transactions))
      STD(sessions.MAX(transactions.amount))
      STD(sessions.MEAN(transactions.amount))
      STD(sessions.MIN(transactions.amount))
      STD(sessions.NUM_UNIQUE(transactions.product_id))
      STD(sessions.SKEW(transactions.amount))
      STD(sessions.SUM(transactions.amount))
      SUM(sessions.MAX(transactions.amount))
      SUM(sessions.MEAN(transactions.amount))
      SUM(sessions.MIN(transactions.amount))
      SUM(sessions.NUM_UNIQUE(transactions.product_id))
      SUM(sessions.SKEW(transactions.amount))
      SUM(sessions.STD(transactions.amount))
      MODE(transactions.sessions.device)
      NUM_UNIQUE(transactions.sessions.device)
    
    
      customer_id
      time
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
    
  
  
    
      1
      2014-01-01 03:00:00
      60091
      3
      desktop
      3
      55
      139.23
      71.501091
      5.81
      1
      5
      0.140387
      42.769602
      3932.56
      18
      17
      7
      4
      0
      6
      1994
      2011
      25.0
      84.440000
      8.74
      5.0
      0.234349
      46.905665
      1613.93
      18.333333
      133.650000
      73.044178
      6.946667
      5.0
      0.108644
      43.249208
      1310.853333
      15.0
      129.00
      64.557200
      5.0
      -0.134754
      40.187205
      1052.03
      1
      1
      1
      2
      2014
      1
      3
      1
      1
      1
      1.732051
      0.782152
      1.173675
      1.552040
      0.0
      0.763052
      0.685199
      5.773503
      5.178021
      10.255607
      1.571507
      0.0
      0.210827
      283.551883
      400.95
      219.132533
      20.84
      15.0
      0.325932
      129.747625
      mobile
      3
    
    
      2014-01-01 04:00:00
      60091
      4
      tablet
      3
      67
      139.23
      74.002836
      5.81
      4
      5
      -0.006928
      42.309717
      4958.19
      18
      17
      7
      4
      0
      6
      1994
      2011
      25.0
      85.469167
      8.74
      5.0
      0.234349
      46.905665
      1613.93
      16.750000
      135.010000
      76.150425
      6.905000
      5.0
      -0.126261
      42.393218
      1239.547500
      12.0
      129.00
      64.557200
      5.0
      -0.830975
      39.825249
      1025.63
      1
      4
      1
      2
      2014
      1
      3
      1
      1
      1
      1.614843
      -0.451371
      -0.233453
      1.452325
      0.0
      1.235445
      1.197406
      5.678908
      5.027226
      10.426572
      1.285833
      0.0
      0.500353
      271.917637
      540.04
      304.601700
      27.62
      20.0
      -0.505043
      169.572874
      tablet
      3
    
    
      2
      2014-01-01 04:00:00
      13244
      4
      desktop
      2
      49
      146.81
      84.700000
      12.07
      4
      5
      -0.134786
      39.289512
      4150.30
      18
      15
      8
      4
      0
      6
      1986
      2012
      16.0
      96.581000
      56.46
      5.0
      0.295458
      47.935920
      1320.64
      12.250000
      142.322500
      85.197948
      26.310000
      5.0
      0.011293
      39.315685
      1037.575000
      8.0
      138.38
      76.813125
      5.0
      -0.455197
      27.839228
      634.84
      1
      2
      1
      2
      2014
      1
      3
      1
      1
      1
      -0.169238
      0.459305
      0.651941
      1.815491
      0.0
      -0.966834
      -0.823347
      3.862210
      3.470527
      8.983533
      20.424007
      0.0
      0.324809
      307.743859
      569.29
      340.791792
      105.24
      20.0
      0.045171
      157.262738
      desktop
      2
    
    
      2014-01-01 05:00:00
      13244
      5
      desktop
      2
      62
      146.81
      83.149355
      12.07
      4
      5
      -0.121811
      38.047944
      5155.26
      18
      15
      8
      4
      0
      6
      1986
      2012
      16.0
      96.581000
      56.46
      5.0
      0.295458
      47.935920
      1320.64
      12.400000
      137.628000
      83.619281
      25.412000
      5.0
      -0.053949
      38.197555
      1031.052000
      8.0
      118.85
      76.813125
      5.0
      -0.455197
      27.839228
      634.84
      1
      2
      1
      2
      2014
      1
      4
      1
      1
      1
      -0.379092
      -1.814717
      1.082192
      1.959531
      0.0
      -0.213518
      -0.667256
      3.361547
      10.919023
      8.543351
      17.801322
      0.0
      0.316873
      266.912832
      688.14
      418.096407
      127.06
      25.0
      -0.269747
      190.987775
      desktop
      2
    
    
      3
      2014-01-01 05:00:00
      13244
      2
      desktop
      2
      32
      146.31
      58.960000
      6.65
      1
      5
      0.637074
      41.199361
      1886.72
      21
      13
      11
      8
      4
      5
      2003
      2011
      17.0
      62.791333
      8.19
      5.0
      0.618455
      47.264797
      944.85
      16.000000
      136.525000
      59.185373
      7.420000
      5.0
      0.575022
      41.716008
      943.360000
      15.0
      126.74
      55.579412
      5.0
      0.531588
      36.167220
      941.87
      1
      1
      1
      2
      2014
      1
      1
      1
      1
      1
      NaN
      NaN
      NaN
      NaN
      NaN
      NaN
      NaN
      1.414214
      13.838080
      5.099599
      1.088944
      0.0
      0.061424
      2.107178
      273.05
      118.370745
      14.84
      10.0
      1.150043
      83.432017
      desktop
      2
    
    
      2014-01-01 06:00:00
      13244
      4
      desktop
      2
      44
      146.31
      65.174773
      6.65
      1
      5
      0.318315
      40.349758
      2867.69
      21
      13
      11
      8
      4
      5
      2003
      2011
      17.0
      91.760000
      91.76
      5.0
      0.618455
      47.264797
      944.85
      11.000000
      123.267500
      72.742004
      31.665000
      4.0
      0.286859
      39.712232
      716.922500
      1.0
      91.76
      55.579412
      1.0
      -0.289466
      35.704680
      91.76
      1
      1
      1
      2
      2014
      1
      2
      1
      1
      1
      -1.330938
      -1.060639
      0.201588
      1.874170
      -2.0
      1.722323
      -1.977878
      7.118052
      22.808351
      16.540737
      40.508892
      2.0
      0.500999
      417.557763
      493.07
      290.968018
      126.66
      16.0
      0.860577
      119.136697
      desktop
      2
    
    
      1
      2014-01-01 07:00:00
      60091
      7
      tablet
      3
      110
      139.43
      69.141182
      5.81
      4
      5
      0.149908
      41.018896
      7605.53
      18
      17
      7
      4
      0
      6
      1994
      2011
      25.0
      85.469167
      26.36
      5.0
      0.640252
      46.905665
      1613.93
      15.714286
      133.122857
      70.491070
      9.567143
      5.0
      0.080330
      40.060203
      1086.504286
      12.0
      118.90
      50.623125
      5.0
      -0.830975
      30.450261
      809.97
      1
      1
      1
      2
      2014
      1
      4
      1
      1
      1
      1.927658
      -1.277394
      -0.282093
      2.552328
      0.0
      -0.755846
      1.377768
      4.386125
      7.441648
      13.123365
      7.470707
      0.0
      0.471955
      273.713405
      931.86
      493.437492
      66.97
      35.0
      0.562312
      280.421418
      tablet
      3
    
    
      2014-01-01 08:00:00
      60091
      8
      mobile
      3
      126
      139.43
      71.631905
      5.81
      4
      5
      0.019698
      40.442059
      9025.62
      18
      17
      7
      4
      0
      6
      1994
      2011
      25.0
      88.755625
      26.36
      5.0
      0.640252
      46.905665
      1613.93
      15.750000
      132.246250
      72.774140
      9.823750
      5.0
      -0.059515
      39.093244
      1128.202500
      12.0
      118.90
      50.623125
      5.0
      -1.038434
      30.450261
      809.97
      1
      4
      1
      2
      2014
      1
      4
      1
      1
      1
      1.946018
      -0.780493
      -0.424949
      2.440005
      0.0
      -0.312355
      0.778170
      4.062019
      7.322191
      13.759314
      6.954507
      0.0
      0.589386
      279.510713
      1057.97
      582.193117
      78.59
      40.0
      -0.476122
      312.745952
      mobile
      3

目录

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处理时间#

什么是时间索引？#

什么是截止时间？#

使用截止时间 DataFrame#

训练窗口#

设置最后时间索引#

排除截止时间点的数据#

通过舍入截止时间来近似特征#

辅助时间索引#

航班预测#

创建和展平特征张量#

		zip_code	COUNT(sessions)	MODE(sessions.device)	NUM_UNIQUE(sessions.device)	COUNT(transactions)	MAX(transactions.amount)	MEAN(transactions.amount)	MIN(transactions.amount)	MODE(transactions.product_id)	NUM_UNIQUE(transactions.product_id)	SKEW(transactions.amount)	STD(transactions.amount)	SUM(transactions.amount)	DAY(birthday)	DAY(join_date)	MONTH(birthday)	MONTH(join_date)	WEEKDAY(birthday)	WEEKDAY(join_date)	YEAR(birthday)	YEAR(join_date)	MAX(sessions.COUNT(transactions))	MAX(sessions.MEAN(transactions.amount))	MAX(sessions.MIN(transactions.amount))	MAX(sessions.NUM_UNIQUE(transactions.product_id))	MAX(sessions.SKEW(transactions.amount))	MAX(sessions.STD(transactions.amount))	MAX(sessions.SUM(transactions.amount))	MEAN(sessions.COUNT(transactions))	MEAN(sessions.MAX(transactions.amount))	MEAN(sessions.MEAN(transactions.amount))	MEAN(sessions.MIN(transactions.amount))	MEAN(sessions.NUM_UNIQUE(transactions.product_id))	MEAN(sessions.SKEW(transactions.amount))	MEAN(sessions.STD(transactions.amount))	MEAN(sessions.SUM(transactions.amount))	MIN(sessions.COUNT(transactions))	MIN(sessions.MAX(transactions.amount))	MIN(sessions.MEAN(transactions.amount))	MIN(sessions.NUM_UNIQUE(transactions.product_id))	MIN(sessions.SKEW(transactions.amount))	MIN(sessions.STD(transactions.amount))	MIN(sessions.SUM(transactions.amount))	MODE(sessions.DAY(session_start))	MODE(sessions.MODE(transactions.product_id))	MODE(sessions.MONTH(session_start))	MODE(sessions.WEEKDAY(session_start))	MODE(sessions.YEAR(session_start))	NUM_UNIQUE(sessions.DAY(session_start))	NUM_UNIQUE(sessions.MODE(transactions.product_id))	NUM_UNIQUE(sessions.MONTH(session_start))	NUM_UNIQUE(sessions.WEEKDAY(session_start))	NUM_UNIQUE(sessions.YEAR(session_start))	SKEW(sessions.COUNT(transactions))	SKEW(sessions.MAX(transactions.amount))	SKEW(sessions.MEAN(transactions.amount))	SKEW(sessions.MIN(transactions.amount))	SKEW(sessions.NUM_UNIQUE(transactions.product_id))	SKEW(sessions.STD(transactions.amount))	SKEW(sessions.SUM(transactions.amount))	STD(sessions.COUNT(transactions))	STD(sessions.MAX(transactions.amount))	STD(sessions.MEAN(transactions.amount))	STD(sessions.MIN(transactions.amount))	STD(sessions.NUM_UNIQUE(transactions.product_id))	STD(sessions.SKEW(transactions.amount))	STD(sessions.SUM(transactions.amount))	SUM(sessions.MAX(transactions.amount))	SUM(sessions.MEAN(transactions.amount))	SUM(sessions.MIN(transactions.amount))	SUM(sessions.NUM_UNIQUE(transactions.product_id))	SUM(sessions.SKEW(transactions.amount))	SUM(sessions.STD(transactions.amount))	MODE(transactions.sessions.device)	NUM_UNIQUE(transactions.sessions.device)
customer_id	time
1	2014-01-01 04:00:00	60091	4	tablet	3	67	139.23	74.002836	5.81	4	5	-0.006928	42.309717	4958.19	18	17	7	4	0	6	1994	2011	25.0	85.469167	8.74	5.0	0.234349	46.905665	1613.93	16.75	135.0100	76.150425	6.905	5.0	-0.126261	42.393218	1239.5475	12.0	129.00	64.557200	5.0	-0.830975	39.825249	1025.63	1	4	1	2	2014	1	3	1	1	1	1.614843	-0.451371	-0.233453	1.452325	0.0	1.235445	1.197406	5.678908	5.027226	10.426572	1.285833	0.0	0.500353	271.917637	540.04	304.601700	27.62	20.0	-0.505043	169.572874	tablet	3
2	2014-01-01 04:00:00	13244	4	desktop	2	49	146.81	84.700000	12.07	4	5	-0.134786	39.289512	4150.30	18	15	8	4	0	6	1986	2012	16.0	96.581000	56.46	5.0	0.295458	47.935920	1320.64	12.25	142.3225	85.197948	26.310	5.0	0.011293	39.315685	1037.5750	8.0	138.38	76.813125	5.0	-0.455197	27.839228	634.84	1	2	1	2	2014	1	3	1	1	1	-0.169238	0.459305	0.651941	1.815491	0.0	-0.966834	-0.823347	3.862210	3.470527	8.983533	20.424007	0.0	0.324809	307.743859	569.29	340.791792	105.24	20.0	0.045171	157.262738	desktop	2
3	2014-01-01 04:00:00	13244	1	tablet	1	15	146.31	62.791333	8.19	1	5	0.618455	47.264797	941.87	21	13	11	8	4	5	2003	2011	15.0	62.791333	8.19	5.0	0.618455	47.264797	941.87	15.00	146.3100	62.791333	8.190	5.0	0.618455	47.264797	941.8700	15.0	146.31	62.791333	5.0	0.618455	47.264797	941.87	1	1	1	2	2014	1	1	1	1	1	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	146.31	62.791333	8.19	5.0	0.618455	47.264797	tablet	1

	session_start	_ft_last_time
1	2014-01-01 00:00:00	2014-01-01 00:16:15
2	2014-01-01 00:17:20	2014-01-01 00:27:05
3	2014-01-01 00:28:10	2014-01-01 00:43:20
4	2014-01-01 00:44:25	2014-01-01 01:10:25
5	2014-01-01 01:11:30	2014-01-01 01:22:20

	trip_log_id	flight_id	date_scheduled	scheduled_dep_time	scheduled_arr_time	dep_time	arr_time	dep_delay	taxi_out	taxi_in	arr_delay	diverted	scheduled_elapsed_time	air_time	distance	canceled
30	30	AA-494:RSW->CLT	2016-09-03	2017-01-01 13:14:00	2017-01-01 15:05:00	2017-01-01 13:03:00	2017-01-01 14:53:00	-11.0	12.0	10.0	-12.0	False	0 days 01:51:00	88.0	600.0	False
38	38	AA-495:ATL->PHX	2016-09-03	2017-01-01 11:30:00	2017-01-01 15:40:00	2017-01-01 11:24:00	2017-01-01 15:41:00	-6.0	28.0	5.0	1.0	False	0 days 04:10:00	224.0	1587.0	False
46	46	AA-495:CLT->ATL	2016-09-03	2017-01-01 09:25:00	2017-01-01 10:42:00	2017-01-01 09:23:00	2017-01-01 10:39:00	-2.0	18.0	8.0	-3.0	False	0 days 01:17:00	50.0	226.0	False

		flights.origin	flights.dest	label	flights.MAX(trip_logs.arr_delay)	MONTH(scheduled_dep_time)
trip_log_id	time
14	2016-12-28	CLT	PHX	True	NaN	1
14	2017-01-25	CLT	PHX	True	33.0	1
92	2016-12-28	PIT	DFW	False	NaN	1

	customer_id	time	label
0	1	2014-01-01 04:00:00	True
1	2	2014-01-01 05:00:00	True
2	3	2014-01-01 06:00:00	False
3	1	2014-01-01 08:00:00	True

		zip_code	COUNT(sessions)	MODE(sessions.device)	NUM_UNIQUE(sessions.device)	COUNT(transactions)	MAX(transactions.amount)	MEAN(transactions.amount)	MIN(transactions.amount)	MODE(transactions.product_id)	NUM_UNIQUE(transactions.product_id)	SKEW(transactions.amount)	STD(transactions.amount)	SUM(transactions.amount)	DAY(birthday)	DAY(join_date)	MONTH(birthday)	MONTH(join_date)	WEEKDAY(birthday)	WEEKDAY(join_date)	YEAR(birthday)	YEAR(join_date)	MAX(sessions.COUNT(transactions))	MAX(sessions.MEAN(transactions.amount))	MAX(sessions.MIN(transactions.amount))	MAX(sessions.NUM_UNIQUE(transactions.product_id))	MAX(sessions.SKEW(transactions.amount))	MAX(sessions.STD(transactions.amount))	MAX(sessions.SUM(transactions.amount))	MEAN(sessions.COUNT(transactions))	MEAN(sessions.MAX(transactions.amount))	MEAN(sessions.MEAN(transactions.amount))	MEAN(sessions.MIN(transactions.amount))	MEAN(sessions.NUM_UNIQUE(transactions.product_id))	MEAN(sessions.SKEW(transactions.amount))	MEAN(sessions.STD(transactions.amount))	MEAN(sessions.SUM(transactions.amount))	MIN(sessions.COUNT(transactions))	MIN(sessions.MAX(transactions.amount))	MIN(sessions.MEAN(transactions.amount))	MIN(sessions.NUM_UNIQUE(transactions.product_id))	MIN(sessions.SKEW(transactions.amount))	MIN(sessions.STD(transactions.amount))	MIN(sessions.SUM(transactions.amount))	MODE(sessions.DAY(session_start))	MODE(sessions.MODE(transactions.product_id))	MODE(sessions.MONTH(session_start))	MODE(sessions.WEEKDAY(session_start))	MODE(sessions.YEAR(session_start))	NUM_UNIQUE(sessions.DAY(session_start))	NUM_UNIQUE(sessions.MODE(transactions.product_id))	NUM_UNIQUE(sessions.MONTH(session_start))	NUM_UNIQUE(sessions.WEEKDAY(session_start))	NUM_UNIQUE(sessions.YEAR(session_start))	SKEW(sessions.COUNT(transactions))	SKEW(sessions.MAX(transactions.amount))	SKEW(sessions.MEAN(transactions.amount))	SKEW(sessions.MIN(transactions.amount))	SKEW(sessions.NUM_UNIQUE(transactions.product_id))	SKEW(sessions.STD(transactions.amount))	SKEW(sessions.SUM(transactions.amount))	STD(sessions.COUNT(transactions))	STD(sessions.MAX(transactions.amount))	STD(sessions.MEAN(transactions.amount))	STD(sessions.MIN(transactions.amount))	STD(sessions.NUM_UNIQUE(transactions.product_id))	STD(sessions.SKEW(transactions.amount))	STD(sessions.SUM(transactions.amount))	SUM(sessions.MAX(transactions.amount))	SUM(sessions.MEAN(transactions.amount))	SUM(sessions.MIN(transactions.amount))	SUM(sessions.NUM_UNIQUE(transactions.product_id))	SUM(sessions.SKEW(transactions.amount))	SUM(sessions.STD(transactions.amount))	MODE(transactions.sessions.device)	NUM_UNIQUE(transactions.sessions.device)
customer_id	time
1	2014-01-01 03:00:00	60091	3	desktop	3	55	139.23	71.501091	5.81	1	5	0.140387	42.769602	3932.56	18	17	7	4	0	6	1994	2011	25.0	84.440000	8.74	5.0	0.234349	46.905665	1613.93	18.333333	133.650000	73.044178	6.946667	5.0	0.108644	43.249208	1310.853333	15.0	129.00	64.557200	5.0	-0.134754	40.187205	1052.03	1	1	1	2	2014	1	3	1	1	1	1.732051	0.782152	1.173675	1.552040	0.0	0.763052	0.685199	5.773503	5.178021	10.255607	1.571507	0.0	0.210827	283.551883	400.95	219.132533	20.84	15.0	0.325932	129.747625	mobile	3
1	2014-01-01 04:00:00	60091	4	tablet	3	67	139.23	74.002836	5.81	4	5	-0.006928	42.309717	4958.19	18	17	7	4	0	6	1994	2011	25.0	85.469167	8.74	5.0	0.234349	46.905665	1613.93	16.750000	135.010000	76.150425	6.905000	5.0	-0.126261	42.393218	1239.547500	12.0	129.00	64.557200	5.0	-0.830975	39.825249	1025.63	1	4	1	2	2014	1	3	1	1	1	1.614843	-0.451371	-0.233453	1.452325	0.0	1.235445	1.197406	5.678908	5.027226	10.426572	1.285833	0.0	0.500353	271.917637	540.04	304.601700	27.62	20.0	-0.505043	169.572874	tablet	3
2	2014-01-01 04:00:00	13244	4	desktop	2	49	146.81	84.700000	12.07	4	5	-0.134786	39.289512	4150.30	18	15	8	4	0	6	1986	2012	16.0	96.581000	56.46	5.0	0.295458	47.935920	1320.64	12.250000	142.322500	85.197948	26.310000	5.0	0.011293	39.315685	1037.575000	8.0	138.38	76.813125	5.0	-0.455197	27.839228	634.84	1	2	1	2	2014	1	3	1	1	1	-0.169238	0.459305	0.651941	1.815491	0.0	-0.966834	-0.823347	3.862210	3.470527	8.983533	20.424007	0.0	0.324809	307.743859	569.29	340.791792	105.24	20.0	0.045171	157.262738	desktop	2
2	2014-01-01 05:00:00	13244	5	desktop	2	62	146.81	83.149355	12.07	4	5	-0.121811	38.047944	5155.26	18	15	8	4	0	6	1986	2012	16.0	96.581000	56.46	5.0	0.295458	47.935920	1320.64	12.400000	137.628000	83.619281	25.412000	5.0	-0.053949	38.197555	1031.052000	8.0	118.85	76.813125	5.0	-0.455197	27.839228	634.84	1	2	1	2	2014	1	4	1	1	1	-0.379092	-1.814717	1.082192	1.959531	0.0	-0.213518	-0.667256	3.361547	10.919023	8.543351	17.801322	0.0	0.316873	266.912832	688.14	418.096407	127.06	25.0	-0.269747	190.987775	desktop	2
3	2014-01-01 05:00:00	13244	2	desktop	2	32	146.31	58.960000	6.65	1	5	0.637074	41.199361	1886.72	21	13	11	8	4	5	2003	2011	17.0	62.791333	8.19	5.0	0.618455	47.264797	944.85	16.000000	136.525000	59.185373	7.420000	5.0	0.575022	41.716008	943.360000	15.0	126.74	55.579412	5.0	0.531588	36.167220	941.87	1	1	1	2	2014	1	1	1	1	1	NaN	NaN	NaN	NaN	NaN	NaN	NaN	1.414214	13.838080	5.099599	1.088944	0.0	0.061424	2.107178	273.05	118.370745	14.84	10.0	1.150043	83.432017	desktop	2
3	2014-01-01 06:00:00	13244	4	desktop	2	44	146.31	65.174773	6.65	1	5	0.318315	40.349758	2867.69	21	13	11	8	4	5	2003	2011	17.0	91.760000	91.76	5.0	0.618455	47.264797	944.85	11.000000	123.267500	72.742004	31.665000	4.0	0.286859	39.712232	716.922500	1.0	91.76	55.579412	1.0	-0.289466	35.704680	91.76	1	1	1	2	2014	1	2	1	1	1	-1.330938	-1.060639	0.201588	1.874170	-2.0	1.722323	-1.977878	7.118052	22.808351	16.540737	40.508892	2.0	0.500999	417.557763	493.07	290.968018	126.66	16.0	0.860577	119.136697	desktop	2
1	2014-01-01 07:00:00	60091	7	tablet	3	110	139.43	69.141182	5.81	4	5	0.149908	41.018896	7605.53	18	17	7	4	0	6	1994	2011	25.0	85.469167	26.36	5.0	0.640252	46.905665	1613.93	15.714286	133.122857	70.491070	9.567143	5.0	0.080330	40.060203	1086.504286	12.0	118.90	50.623125	5.0	-0.830975	30.450261	809.97	1	1	1	2	2014	1	4	1	1	1	1.927658	-1.277394	-0.282093	2.552328	0.0	-0.755846	1.377768	4.386125	7.441648	13.123365	7.470707	0.0	0.471955	273.713405	931.86	493.437492	66.97	35.0	0.562312	280.421418	tablet	3
1	2014-01-01 08:00:00	60091	8	mobile	3	126	139.43	71.631905	5.81	4	5	0.019698	40.442059	9025.62	18	17	7	4	0	6	1994	2011	25.0	88.755625	26.36	5.0	0.640252	46.905665	1613.93	15.750000	132.246250	72.774140	9.823750	5.0	-0.059515	39.093244	1128.202500	12.0	118.90	50.623125	5.0	-1.038434	30.450261	809.97	1	4	1	2	2014	1	4	1	1	1	1.946018	-0.780493	-0.424949	2.440005	0.0	-0.312355	0.778170	4.062019	7.322191	13.759314	6.954507	0.0	0.589386	279.510713	1057.97	582.193117	78.59	40.0	-0.476122	312.745952	mobile	3

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