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You have a DataFrame called ecommerce with data on customer orders: OrderID (integer) CustomerID (integer) OrderDate (string in format ‘dd/mm/yyyy’) OrderAmount (float) ShipDate (string in format ‘dd/mm/yyyy’) ShipMode (categories: Regular/Express/Priority) Product (text) Category (text) Quantity (integer) Discount (float) Profit (float) Perform the following data manipulation step: Filter the data to only include Category = ‘Electronics’.

You have a DataFrame called ecommerce with data on customer orders: OrderID (integer) CustomerID (integer) OrderDate (string in format ‘dd/mm/yyyy’) OrderAmount (float) ShipDate (string in format ‘dd/mm/yyyy’) ShipMode (categories: Regular/Express/Priority) Product (text) Category (text) Quantity (integer) Discount (float) Profit (float) Perform the following data manipulation step: Write the transformed DataFrame to an Excel file called customer_sales.xlsx.

You have a DataFrame called ecommerce with data on customer orders: OrderID (integer) CustomerID (integer) OrderDate (string in format ‘dd/mm/yyyy’) OrderAmount (float) ShipDate (string in format ‘dd/mm/yyyy’) ShipMode (categories: Regular/Express/Priority) Product (text) Category (text) Quantity (integer) Discount (float) Profit (float) Perform the following data manipulation step: Create a datetime index using the OrderDate column.

You have a DataFrame called ecommerce with data on customer orders: OrderID (integer) CustomerID (integer) OrderDate (string in format ‘dd/mm/yyyy’) OrderAmount (float) ShipDate (string in format ‘dd/mm/yyyy’) ShipMode (categories: Regular/Express/Priority) Product (text) Category (text) Quantity (integer) Discount (float) Profit (float) Perform the following data manipulation step: Group the filtered data by CustomerID and OrderDate, getting max TotalAmount.

You have a DataFrame called ecommerce with data on customer orders: OrderID (integer) CustomerID (integer) OrderDate (string in format ‘dd/mm/yyyy’) OrderAmount (float) ShipDate (string in format ‘dd/mm/yyyy’) ShipMode (categories: Regular/Express/Priority) Product (text) Category (text) Quantity (integer) Discount (float) Profit (float) Perform the following data manipulation step: Group the filtered data by Product and aggregate Quantity sum and TotalAmount mean.

You have a DataFrame called ecommerce with data on customer orders: OrderID (integer) CustomerID (integer) OrderDate (string in format ‘dd/mm/yyyy’) OrderAmount (float) ShipDate (string in format ‘dd/mm/yyyy’) ShipMode (categories: Regular/Express/Priority) Product (text) Category (text) Quantity (integer) Discount (float) Profit (float) Perform the following data manipulation step: Group the filtered data by Category and Product, calculating mean Quantity and sum of TotalAmount.

You have a DataFrame called ecommerce with data on customer orders: OrderID (integer) CustomerID (integer) OrderDate (string in format ‘dd/mm/yyyy’) OrderAmount (float) ShipDate (string in format ‘dd/mm/yyyy’) ShipMode (categories: Regular/Express/Priority) Product (text) Category (text) Quantity (integer) Discount (float) Profit (float) Perform the following data manipulation step: Add a SalesTax column with a 5% tax on TotalAmount.

You have a DataFrame called ecommerce with data on customer orders: OrderID (integer) CustomerID (integer) OrderDate (string in format ‘dd/mm/yyyy’) OrderAmount (float) ShipDate (string in format ‘dd/mm/yyyy’) ShipMode (categories: Regular/Express/Priority) Product (text) Category (text) Quantity (integer) Discount (float) Profit (float) Perform the following data manipulation step: Sort the grouped data by total Quantity shipped descending.

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