Transactional Retail Dataset Of Electronics Store

Context

This dataset contains information about an online electronic store. The store has three warehouses from which goods are delivered to customers.

Columns Description

• order_id: A unique id for each order
• customer_id: A unique id for each customer
• date: The date the order was made, given in YYYY-MM-DD format
• nearest_warehouse: A string denoting the name of the nearest warehouse to the
  customer
• shopping_cart: A list of tuples representing the order items: the first element of
  the tuple is the item ordered, and the second element is the
  quantity ordered for such item.
• order_price: A float denoting the order price in USD. The order price is the
  price of items before any discounts and/or delivery charges
  are applied.
• delivery_charges: A float representing the delivery charges of the order
• customer_lat: Latitude of the customer’s location
• customer_long: Longitude of the customer’s location
• coupon_discount: An integer denoting the percentage discount to be applied to
  the order_price.
• order_total: A float denoting the total of the order in USD after all
  discounts and/or delivery charges are applied.
• season: A string denoting the season in which the order was placed.
• is_expedited_delivery: A boolean denoting whether the customer has requested an
  expedited delivery
• distance_to_nearest_warehouse: A float representing the arc distance, in kilometres, between
  the customer and the nearest warehouse to him/her.
• latest_customer_review: A string representing the latest customer review on his/her
  most recent order
• is_happy_customer: A boolean denoting whether the customer is a happy
  customer or had an issue with his/her last order.

Inspiration

Use this dataset to perform graphical and/or non-graphical EDA methods to understand
the data first and then find and fix the data problems.

• Detect and fix errors in dirty_data.csv
• Impute the missing values in missing_data.csv
• Detect and remove Anolamies
• To check whether a customer is happy with their last order

All the Best