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Add zipcode to mock_customer and docs #417

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merged 11 commits into from Feb 8, 2019
Merged

Add zipcode to mock_customer and docs #417

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d671276
changed to zipcode type
gsheni Feb 7, 2019
8d731b7
fix in docs
gsheni Feb 7, 2019
7f4c318
remove suppress
gsheni Feb 7, 2019
fbae375
change docs back
gsheni Feb 7, 2019
5b60735
Merge branch 'master' into add_zipcode
gsheni Feb 7, 2019
95b8daf
Merge branch 'master' into add_zipcode
gsheni Feb 8, 2019
0b3b6aa
Merge branch 'master' into add_zipcode
gsheni Feb 8, 2019
badc5be
Merge branch 'master' into add_zipcode
gsheni Feb 8, 2019
b88b721
Merge branch 'master' into add_zipcode
gsheni Feb 8, 2019
694f3e3
Merge branch 'master' into add_zipcode
kmax12 Feb 8, 2019
153ff6d
Merge branch 'master' into add_zipcode
gsheni Feb 8, 2019
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3 changes: 2 additions & 1 deletion docs/source/loading_data/using_entitysets.rst
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Expand Up @@ -49,7 +49,8 @@ To get started, we load the transactions dataframe as an entity.
dataframe=transactions_df,
index="transaction_id",
time_index="transaction_time",
variable_types={"product_id": ft.variable_types.Categorical})
variable_types={"product_id": ft.variable_types.Categorical,
"zip_code": ft.variable_types.ZIPCode})
es

.. note ::
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5 changes: 2 additions & 3 deletions featuretools/demo/mock_customer.py
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Expand Up @@ -7,7 +7,7 @@
from numpy.random import choice

import featuretools as ft
from featuretools.variable_types import Categorical
from featuretools.variable_types import ZIPCode


def load_mock_customer(n_customers=5, n_products=5, n_sessions=35, n_transactions=500,
Expand Down Expand Up @@ -50,7 +50,6 @@ def load_mock_customer(n_customers=5, n_products=5, n_sessions=35, n_transaction

if return_single_table:
return transactions_df.merge(sessions_df).merge(customers_df).merge(products_df).reset_index(drop=True)

elif return_entityset:
es = ft.EntitySet(id="transactions")
es = es.entity_from_dataframe(entity_id="transactions",
Expand All @@ -72,7 +71,7 @@ def load_mock_customer(n_customers=5, n_products=5, n_sessions=35, n_transaction
dataframe=customers_df,
index="customer_id",
time_index="join_date",
variable_types={"zip_code": Categorical})
variable_types={"zip_code": ZIPCode})

rels = [ft.Relationship(es["products"]["product_id"],
es["transactions"]["product_id"]),
Expand Down