What is Featuretools?

Featuretools

Featuretools is a framework to perform automated feature engineering. It excels at transforming temporal and relational datasets into feature matrices for machine learning.

5 Minute Quick Start

Below is an example of using Deep Feature Synthesis (DFS) to perform automated feature engineering. In this example, we apply DFS to a multi-table dataset consisting of timestamped customer transactions.

In [1]: import featuretools as ft

Load Mock Data

In [2]: data = ft.demo.load_mock_customer()

Prepare data

In this toy dataset, there are 3 tables. Each table is called an entity in Featuretools.

  • customers: unique customers who had sessions

  • sessions: unique sessions and associated attributes

  • transactions: list of events in this session

In [3]: customers_df = data["customers"]

In [4]: customers_df
Out[4]: 
   customer_id zip_code           join_date date_of_birth
0            1    60091 2011-04-17 10:48:33    1994-07-18
1            2    13244 2012-04-15 23:31:04    1986-08-18
2            3    13244 2011-08-13 15:42:34    2003-11-21
3            4    60091 2011-04-08 20:08:14    2006-08-15
4            5    60091 2010-07-17 05:27:50    1984-07-28

In [5]: sessions_df = data["sessions"]

In [6]: sessions_df.sample(5)
Out[6]: 
    session_id  customer_id   device       session_start
13          14            1   tablet 2014-01-01 03:28:00
6            7            3   tablet 2014-01-01 01:39:40
1            2            5   mobile 2014-01-01 00:17:20
28          29            1   mobile 2014-01-01 07:10:05
24          25            3  desktop 2014-01-01 05:59:40

In [7]: transactions_df = data["transactions"]

In [8]: transactions_df.sample(5)
Out[8]: 
     transaction_id  session_id    transaction_time product_id  amount
74              232           5 2014-01-01 01:20:10          1  139.20
231              27          17 2014-01-01 04:10:15          2   90.79
434              36          31 2014-01-01 07:50:10          3   62.35
420              56          30 2014-01-01 07:35:00          3   72.70
54              444           4 2014-01-01 00:58:30          4   43.59

First, we specify a dictionary with all the entities in our dataset.

In [9]: entities = {
   ...:    "customers" : (customers_df, "customer_id"),
   ...:    "sessions" : (sessions_df, "session_id", "session_start"),
   ...:    "transactions" : (transactions_df, "transaction_id", "transaction_time")
   ...: }
   ...: 

Second, we specify how the entities are related. When two entities have a one-to-many relationship, we call the “one” enitity, the “parent entity”. A relationship between a parent and child is defined like this:

(parent_entity, parent_variable, child_entity, child_variable)

In this dataset we have two relationships

In [10]: relationships = [("sessions", "session_id", "transactions", "session_id"),
   ....:                  ("customers", "customer_id", "sessions", "customer_id")]
   ....: 

Note

To manage setting up entities and relationships, we recommend using the EntitySet class which offers convenient APIs for managing data like this. See Representing Data with EntitySets for more information.

Run Deep Feature Synthesis

A minimal input to DFS is a set of entities, a list of relationships, and the “target_entity” to calculate features for. The ouput of DFS is a feature matrix and the corresponding list of feature definitions.

Let’s first create a feature matrix for each customer in the data

In [11]: feature_matrix_customers, features_defs = ft.dfs(entities=entities,
   ....:                                                  relationships=relationships,
   ....:                                                  target_entity="customers")
   ....: 

In [12]: feature_matrix_customers
Out[12]: 
            zip_code  COUNT(sessions)  NUM_UNIQUE(sessions.device) MODE(sessions.device)  SUM(transactions.amount)  STD(transactions.amount)  MAX(transactions.amount)  SKEW(transactions.amount)  MIN(transactions.amount)  MEAN(transactions.amount)  COUNT(transactions)  NUM_UNIQUE(transactions.product_id)  MODE(transactions.product_id)  DAY(join_date)  DAY(date_of_birth)  YEAR(join_date)  YEAR(date_of_birth)  MONTH(join_date)  MONTH(date_of_birth)  WEEKDAY(join_date)  WEEKDAY(date_of_birth)  SUM(sessions.NUM_UNIQUE(transactions.product_id))  SUM(sessions.MIN(transactions.amount))  SUM(sessions.STD(transactions.amount))  SUM(sessions.MAX(transactions.amount))  SUM(sessions.MEAN(transactions.amount))  SUM(sessions.SKEW(transactions.amount))  STD(sessions.COUNT(transactions))  STD(sessions.SUM(transactions.amount))  STD(sessions.NUM_UNIQUE(transactions.product_id))  STD(sessions.MIN(transactions.amount))  STD(sessions.MAX(transactions.amount))  STD(sessions.MEAN(transactions.amount))  STD(sessions.SKEW(transactions.amount))  MAX(sessions.COUNT(transactions))  MAX(sessions.SUM(transactions.amount))  MAX(sessions.NUM_UNIQUE(transactions.product_id))  MAX(sessions.MIN(transactions.amount))  MAX(sessions.STD(transactions.amount))  MAX(sessions.MEAN(transactions.amount))  MAX(sessions.SKEW(transactions.amount))  SKEW(sessions.COUNT(transactions))  SKEW(sessions.SUM(transactions.amount))  SKEW(sessions.NUM_UNIQUE(transactions.product_id))  SKEW(sessions.MIN(transactions.amount))  SKEW(sessions.STD(transactions.amount))  SKEW(sessions.MAX(transactions.amount))  SKEW(sessions.MEAN(transactions.amount))  MIN(sessions.COUNT(transactions))  MIN(sessions.SUM(transactions.amount))  MIN(sessions.NUM_UNIQUE(transactions.product_id))  MIN(sessions.STD(transactions.amount))  MIN(sessions.MAX(transactions.amount))  MIN(sessions.MEAN(transactions.amount))  MIN(sessions.SKEW(transactions.amount))  MEAN(sessions.COUNT(transactions))  MEAN(sessions.SUM(transactions.amount))  MEAN(sessions.NUM_UNIQUE(transactions.product_id))  MEAN(sessions.MIN(transactions.amount))  MEAN(sessions.STD(transactions.amount))  MEAN(sessions.MAX(transactions.amount))  MEAN(sessions.MEAN(transactions.amount))  MEAN(sessions.SKEW(transactions.amount))  NUM_UNIQUE(sessions.DAY(session_start))  NUM_UNIQUE(sessions.MONTH(session_start))  NUM_UNIQUE(sessions.YEAR(session_start))  NUM_UNIQUE(sessions.WEEKDAY(session_start))  NUM_UNIQUE(sessions.MODE(transactions.product_id))  MODE(sessions.DAY(session_start))  MODE(sessions.MONTH(session_start))  MODE(sessions.YEAR(session_start))  MODE(sessions.WEEKDAY(session_start))  MODE(sessions.MODE(transactions.product_id))  NUM_UNIQUE(transactions.sessions.device)  NUM_UNIQUE(transactions.sessions.customer_id) MODE(transactions.sessions.device)  MODE(transactions.sessions.customer_id)
customer_id                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                          
1              60091                8                            3                mobile                   9025.62                 40.442059                    139.43                   0.019698                      5.81                  71.631905                  126                                    5                              4              17                  18             2011                 1994                 4                     7                   6                       0                                                 40                                   78.59                              312.745952                                 1057.97                               582.193117                                -0.476122                           4.062019                              279.510713                                           0.000000                                6.954507                                7.322191                                13.759314                                 0.589386                                 25                                 1613.93                                                  5                                   26.36                               46.905665                                88.755625                                 0.640252                            1.946018                                 0.778170                                           0.000000                                  2.440005                                -0.312355                                -0.780493                                 -0.424949                                 12                                  809.97                                                  5                               30.450261                                  118.90                                50.623125                                -1.038434                           15.750000                              1128.202500                                           5.000000                                  9.823750                                39.093244                               132.246250                                 72.774140                                 -0.059515                                        1                                          1                                         1                                            1                                                  4                                   1                                    1                                2014                                      2                                             4                                         3                                              1                             mobile                                        1
2              13244                7                            3               desktop                   7200.28                 37.705178                    146.81                   0.098259                      8.73                  77.422366                   93                                    5                              4              15                  18             2012                 1986                 4                     8                   6                       0                                                 35                                  154.60                              258.700528                                  931.63                               548.905851                                -0.277640                           3.450328                              251.609234                                           0.000000                               15.874374                               17.221593                                11.477071                                 0.509798                                 18                                 1320.64                                                  5                                   56.46                               47.935920                                96.581000                                 0.755711                           -0.303276                                -0.440929                                           0.000000                                  2.154929                                 0.013087                                -1.539467                                  0.235296                                  8                                  634.84                                                  5                               27.839228                                  100.04                                61.910000                                -0.763603                           13.285714                              1028.611429                                           5.000000                                 22.085714                                36.957218                               133.090000                                 78.415122                                 -0.039663                                        1                                          1                                         1                                            1                                                  4                                   1                                    1                                2014                                      2                                             3                                         3                                              1                            desktop                                        2
3              13244                6                            3               desktop                   6236.62                 43.683296                    149.15                   0.418230                      5.89                  67.060430                   93                                    5                              1              13                  21             2011                 2003                 8                    11                   5                       4                                                 29                                   66.21                              257.299895                                  847.63                               405.237462                                 2.286086                           2.428992                              219.021420                                           0.408248                                5.424407                               10.724241                                11.174282                                 0.429374                                 18                                 1477.97                                                  5                                   20.06                               50.110120                                82.109444                                 0.854976                           -1.507217                                 2.246479                                          -2.449490                                  1.000771                                -0.245703                                -0.941078                                  0.678544                                 11                                  889.21                                                  4                               35.704680                                  126.74                                55.579412                                -0.289466                           15.500000                              1039.436667                                           4.833333                                 11.035000                                42.883316                               141.271667                                 67.539577                                  0.381014                                        1                                          1                                         1                                            1                                                  4                                   1                                    1                                2014                                      2                                             1                                         3                                              1                            desktop                                        3
4              60091                8                            3                mobile                   8727.68                 45.068765                    149.95                  -0.036348                      5.73                  80.070459                  109                                    5                              2               8                  15             2011                 2006                 4                     8                   4                       1                                                 37                                  131.51                              356.125829                                 1157.99                               649.657515                                 0.002764                           3.335416                              235.992478                                           0.517549                               16.960575                                3.514421                                13.027258                                 0.387884                                 18                                 1351.46                                                  5                                   54.83                               54.293903                               110.450000                                 0.382868                            0.282488                                -0.391805                                          -0.644061                                  2.103510                                -1.065663                                 0.027256                                  1.980948                                 10                                  771.68                                                  4                               29.026424                                  139.20                                70.638182                                -0.711744                           13.625000                              1090.960000                                           4.625000                                 16.438750                                44.515729                               144.748750                                 81.207189                                  0.000346                                        1                                          1                                         1                                            1                                                  5                                   1                                    1                                2014                                      2                                             1                                         3                                              1                             mobile                                        4
5              60091                6                            3                mobile                   6349.66                 44.095630                    149.02                  -0.025941                      7.55                  80.375443                   79                                    5                              5              17                  28             2010                 1984                 7                     7                   5                       5                                                 30                                   86.49                              259.873954                                  839.76                               472.231119                                 0.014384                           3.600926                              402.775486                                           0.000000                                4.961414                                7.928001                                11.007471                                 0.415426                                 18                                 1700.67                                                  5                                   20.65                               51.149250                                94.481667                                 0.602209                           -0.317685                                 0.472342                                           0.000000                                 -0.470410                                 0.204548                                -0.333796                                  0.335175                                  8                                  543.18                                                  5                               36.734681                                  128.51                                66.666667                                -0.539060                           13.166667                              1058.276667                                           5.000000                                 14.415000                                43.312326                               139.960000                                 78.705187                                  0.002397                                        1                                          1                                         1                                            1                                                  5                                   1                                    1                                2014                                      2                                             3                                         3                                              1                             mobile                                        5

We now have dozens of new features to describe a customer’s behavior.

Change target entity

One of the reasons DFS is so powerful is that it can create a feature matrix for any entity in our data. For example, if we wanted to build features for sessions.

In [13]: feature_matrix_sessions, features_defs = ft.dfs(entities=entities,
   ....:                                                 relationships=relationships,
   ....:                                                 target_entity="sessions")
   ....: 

In [14]: feature_matrix_sessions.head(5)
Out[14]: 
            customer_id   device  SUM(transactions.amount)  STD(transactions.amount)  MAX(transactions.amount)  SKEW(transactions.amount)  MIN(transactions.amount)  MEAN(transactions.amount)  COUNT(transactions)  NUM_UNIQUE(transactions.product_id)  MODE(transactions.product_id)  DAY(session_start)  YEAR(session_start)  MONTH(session_start)  WEEKDAY(session_start) customers.zip_code  NUM_UNIQUE(transactions.DAY(transaction_time))  NUM_UNIQUE(transactions.YEAR(transaction_time))  NUM_UNIQUE(transactions.MONTH(transaction_time))  NUM_UNIQUE(transactions.WEEKDAY(transaction_time))  MODE(transactions.DAY(transaction_time))  MODE(transactions.YEAR(transaction_time))  MODE(transactions.MONTH(transaction_time))  MODE(transactions.WEEKDAY(transaction_time))  customers.COUNT(sessions)  customers.NUM_UNIQUE(sessions.device) customers.MODE(sessions.device)  customers.SUM(transactions.amount)  customers.STD(transactions.amount)  customers.MAX(transactions.amount)  customers.SKEW(transactions.amount)  customers.MIN(transactions.amount)  customers.MEAN(transactions.amount)  customers.COUNT(transactions)  customers.NUM_UNIQUE(transactions.product_id)  customers.MODE(transactions.product_id)  customers.DAY(join_date)  customers.DAY(date_of_birth)  customers.YEAR(join_date)  customers.YEAR(date_of_birth)  customers.MONTH(join_date)  customers.MONTH(date_of_birth)  customers.WEEKDAY(join_date)  customers.WEEKDAY(date_of_birth)
session_id                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                              
1                     2  desktop                   1229.01                 41.600976                    141.66                   0.295458                     20.91                  76.813125                   16                                    5                              3                   1                 2014                     1                       2              13244                                               1                                                1                                                 1                                                  1                                          1                                       2014                                           1                                             2                          7                                      3                         desktop                             7200.28                           37.705178                              146.81                             0.098259                                8.73                            77.422366                             93                                              5                                        4                        15                            18                       2012                           1986                           4                               8                             6                                 0
2                     5   mobile                    746.96                 45.893591                    135.25                  -0.160550                      9.32                  74.696000                   10                                    5                              5                   1                 2014                     1                       2              60091                                               1                                                1                                                 1                                                  1                                          1                                       2014                                           1                                             2                          6                                      3                          mobile                             6349.66                           44.095630                              149.02                            -0.025941                                7.55                            80.375443                             79                                              5                                        5                        17                            28                       2010                           1984                           7                               7                             5                                 5
3                     4   mobile                   1329.00                 46.240016                    147.73                  -0.324012                      8.70                  88.600000                   15                                    5                              1                   1                 2014                     1                       2              60091                                               1                                                1                                                 1                                                  1                                          1                                       2014                                           1                                             2                          8                                      3                          mobile                             8727.68                           45.068765                              149.95                            -0.036348                                5.73                            80.070459                            109                                              5                                        2                         8                            15                       2011                           2006                           4                               8                             4                                 1
4                     1   mobile                   1613.93                 40.187205                    129.00                   0.234349                      6.29                  64.557200                   25                                    5                              5                   1                 2014                     1                       2              60091                                               1                                                1                                                 1                                                  1                                          1                                       2014                                           1                                             2                          8                                      3                          mobile                             9025.62                           40.442059                              139.43                             0.019698                                5.81                            71.631905                            126                                              5                                        4                        17                            18                       2011                           1994                           4                               7                             6                                 0
5                     4   mobile                    777.02                 48.918663                    139.20                   0.336381                      7.43                  70.638182                   11                                    5                              5                   1                 2014                     1                       2              60091                                               1                                                1                                                 1                                                  1                                          1                                       2014                                           1                                             2                          8                                      3                          mobile                             8727.68                           45.068765                              149.95                            -0.036348                                5.73                            80.070459                            109                                              5                                        2                         8                            15                       2011                           2006                           4                               8                             4                                 1

What’s next?