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ecommerce-big-data's Introduction

eCommerce behavior data from multi category store

This dataset contains 67 million users' events from eCommerce website

How to read it

There are different types of events. See below.

Property Description
event_time Time when event happened at (in UTC).
event_type Only one kind of event: purchase.
product_id ID of a product
category_id Product's category ID
category_code Product's category taxonomy (code name) if it was possible to make it. Usually present for meaningful categories and skipped for different kinds of accessories.
brand Downcased string of brand name. Can be missed.
price Float price of a product.
user_id permanent user ID.

user_session Temporary user's session ID. Same for each user's session. Is changed every time user come back to online store from a long pause.

Event types

Events can be:

view - a user viewed a product

cart - a user added a product to shopping cart

remove_from_cart - a user removed a product from shopping cart

purchase - a user purchased a product

Multiple purchases per session

A session can have multiple purchase events. It's ok, because it's a single order.

Many thanks

Thanks to REES46 Marketing Platform for this dataset.

Tools:

python ai notebook in GCP

Libraries:

import numpy as np # linear algebra
import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)
pd.options.display.float_format = "{:,.2f}".format
import seaborn as sns
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
import datetime as dt
import warnings
warnings.simplefilter("ignore")

huge thanks to the steps followed, also good doing the notes : @adilemre

PRESENTATION IN PREZI:

https://prezi.com/view/hDBtuNflfYB1WtaBNniS

https://www.youtube.com/watch?v=PCnNCXMYDNg&lc=UgxCSzwC7YvDi7rQQNp4AaABAg

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