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Target

Analyzing the given dataset to extract valuable insights and provide actionable recommendations.

#Key Features:

1)Import the dataset and do usual exploratory analysis steps like checking the structure & characteristics of the dataset:

 - Data type of all columns in the "customers" table.
 - Get the time range between which the orders were placed.
 - Count the Cities & States of customers who ordered during the given period.

2)In-depth Exploration:

 - Is there a growing trend in the no. of orders placed over the past years?
 - Can we see some kind of monthly seasonality in terms of the no. of orders being placed?
 - During what time of the day, do the Brazilian customers mostly place their orders? (Dawn, Morning, Afternoon or Night)
      0-6 hrs : Dawn
      7-12 hrs : Mornings
      13-18 hrs : Afternoon
      19-23 hrs : Night

3)Evolution of E-commerce orders in the Brazil region:

  - Get the month on month no. of orders placed in each state.
  - How are the customers distributed across all the states?

4)Impact on Economy: Analyze the money movement by e-commerce by looking at order prices, freight and others.

   - Get the % increase in the cost of orders from year 2017 to 2018 (include months between Jan to Aug only).
   - You can use the "payment_value" column in the payments table to get the cost of orders.
   - Calculate the Total & Average value of order price for each state.
   - Calculate the Total & Average value of order freight for each state.

5)Analysis based on sales, freight and delivery time.

   - Find the no. of days taken to deliver each order from the order’s purchase date as delivery time.
   - Also, calculate the difference (in days) between the estimated & actual delivery date of an order.
   - You can calculate the delivery time and the difference between the estimated & actual delivery date using the given 
         formula:
        time_to_deliver = order_delivered_customer_date - order_purchase_timestamp
        diff_estimated_delivery = order_delivered_customer_date - order_estimated_delivery_date
   - Find out the top 5 states with the highest & lowest average freight value.
   - Find out the top 5 states with the highest & lowest average delivery time.
    -Find out the top 5 states where the order delivery is really fast as compared to the estimated date of delivery.
    You can use the difference between the averages of actual & estimated delivery date to figure out how fast the 
     delivery was for each state.

6)Analysis based on the payments:

  -  Find the month on month no. of orders placed using different payment types.
  - Find the no. of orders placed on the basis of the payment installments that have been paid.

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