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Merge branch 'dev' of github.com:maks-sh/scikit-uplift into dev
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‎docs/api/datasets/fetch_criteo.rst‎

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.. autofunction:: sklift.datasets.datasets.fetch_criteo
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About the company
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##################
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.. include:: ../../../sklift/datasets/descr/criteo.rst
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Criteo is an advertising company that provides online display advertisements.
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The company was founded and is headquartered in Paris, France. Criteo's product is a form of display advertising,
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which displays interactive banner advertisements, generated based on the online browsing preferences and behaviour for each customer.
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The solution operates on a pay per click/cost per click (CPC) basis.
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About Criteo
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##################
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.. figure:: https://upload.wikimedia.org/wikipedia/commons/d/d2/Criteo_logo21.svg
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Link to the company's website: https://www.criteo.com/
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`Criteo <https://en.wikipedia.org/wiki/Criteo>`__ is an advertising company that provides online display advertisements.
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The company was founded and is headquartered in Paris, France. Criteo's product is a form of display advertising,
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which displays interactive banner advertisements, generated based on the online browsing preferences and behaviour for each customer.
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The solution operates on a pay per click/cost per click (CPC) basis.
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.. include:: ../../../sklift/datasets/descr/criteo.rst
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Link to the company's website: https://www.criteo.com/

‎docs/api/datasets/fetch_hillstrom.rst‎

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.. autofunction:: sklift.datasets.datasets.fetch_hillstrom
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About the company
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.. include:: ../../../sklift/datasets/descr/hillstrom.rst
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About Hillstrom
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##################
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The dataset was provided by Kevin Hillstorm.
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The dataset was provided by Kevin Hillstorm.
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Kevin is President of MineThatData, a consultancy that helps CEOs understand the complex relationship between Customers, Advertising, Products, Brands, and Channels.
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Link to the blog website: https://blog.minethatdata.com/
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.. include:: ../../../sklift/datasets/descr/hillstrom.rst
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Link to the blog: https://blog.minethatdata.com/

‎docs/api/datasets/fetch_lenta.rst‎

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.. autofunction:: sklift.datasets.datasets.fetch_lenta
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About the company
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##################
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.. include:: ../../../sklift/datasets/descr/lenta.rst
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Lenta (Russian: Лентa) is a Russian super - and hypermarket chain. With 149 locations across the country,
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it is one of Russia's largest retail chains in addition to being the country's second largest hypermarket chain.
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About Lenta
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##################
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.. figure:: https://upload.wikimedia.org/wikipedia/commons/7/73/Lenta_logo.svg
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Link to the company's website: https://www.lenta.com/
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`Lenta (Russian: Лентa) <https://en.wikipedia.org/wiki/Lenta_(retail)>`__ is a Russian super - and hypermarket chain. With 149 locations across the country,
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it is one of Russia's largest retail chains in addition to being the country's second largest hypermarket chain.
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.. include:: ../../../sklift/datasets/descr/lenta.rst
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Link to the company's website: https://www.lenta.com/

‎docs/api/datasets/fetch_megafon.rst‎

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.. autofunction:: sklift.datasets.datasets.fetch_megafon
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About the company
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##################
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.. include:: ../../../sklift/datasets/descr/megafon.rst
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MegaFon (Russian: МегаФон), previously known as North-West GSM, is the second largest mobile phone operator and the third largest telecom operator in Russia.
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It works in the GSM, UMTS and LTE standard. As of June 2012, the company serves 62.1 million subscribers in Russia and 1.6 million in Tajikistan. It is headquartered in Moscow.
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About MegaFon
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##################
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.. figure:: https://upload.wikimedia.org/wikipedia/commons/9/9e/MegaFon_logo.svg
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Link to the company's website: https://megafon.ru/
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`MegaFon (Russian: МегаФон) <https://en.wikipedia.org/wiki/MegaFon>`__ , previously known as North-West GSM, is the second largest mobile phone operator and the third largest telecom operator in Russia.
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It works in the GSM, UMTS and LTE standard. As of June 2012, the company serves 62.1 million subscribers in Russia and 1.6 million in Tajikistan. It is headquartered in Moscow.
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.. include:: ../../../sklift/datasets/descr/megafon.rst
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Link to the company's website: https://megafon.ru/

‎docs/api/datasets/fetch_x5.rst‎

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.. autofunction:: sklift.datasets.datasets.fetch_x5
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About the company
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.. include:: ../../../sklift/datasets/descr/x5.rst
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About X5
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##################
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X5 Group is a leading Russian food retailer.
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.. figure:: https://upload.wikimedia.org/wikipedia/en/8/83/X5_Retail_Group_logo_2015.png
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`X5 Group <https://en.wikipedia.org/wiki/X5_Retail_Group>`__ is a leading Russian food retailer.
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The Company operates several retail formats: proximity stores under the Pyaterochka brand,
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supermarkets under the Perekrestok brand and hypermarkets under the Karusel brand, as well as the Perekrestok.ru online market,
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the 5Post parcel and Dostavka.Pyaterochka and Perekrestok. Bystro food delivery services.
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.. figure:: https://upload.wikimedia.org/wikipedia/en/8/83/X5_Retail_Group_logo_2015.png
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Link to the company's website: https://www.x5.ru/
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.. include:: ../../../sklift/datasets/descr/x5.rst
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Link to the company's website: https://www.x5.ru/

‎sklift/datasets/datasets.py‎

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:func:`.fetch_megafon`: Load and return the MegaFon Uplift Competition dataset (classification).
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"""
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url_train = 'https://timds.s3.eu-central-1.amazonaws.com/uplift_train.csv.gz'
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url_train = 'https://sklift.s3.eu-west-2.amazonaws.com/uplift_train.csv.gz'
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file_train = url_train.split('/')[-1]
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csv_train_path = _get_data(data_home=data_home, url=url_train, dest_subdir=dest_subdir,
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dest_filename=file_train,
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train = train.drop([target_col, treatment_col], axis=1)
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url_clients = 'https://timds.s3.eu-central-1.amazonaws.com/clients.csv.gz'
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url_clients = 'https://sklift.s3.eu-west-2.amazonaws.com/clients.csv.gz'
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file_clients = url_clients.split('/')[-1]
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csv_clients_path = _get_data(data_home=data_home, url=url_clients, dest_subdir=dest_subdir,
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dest_filename=file_clients,
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download_if_missing=download_if_missing)
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clients = pd.read_csv(csv_clients_path)
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clients_features = list(clients.columns)
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url_purchases = 'https://timds.s3.eu-central-1.amazonaws.com/purchases.csv.gz'
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url_purchases = 'https://sklift.s3.eu-west-2.amazonaws.com/purchases.csv.gz'
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file_purchases = url_purchases.split('/')[-1]
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csv_purchases_path = _get_data(data_home=data_home, url=url_purchases, dest_subdir=dest_subdir,
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dest_filename=file_purchases,

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