Sales-Analysis-in-Python

Requairments are as follow ,

1. Monthwise number of quantities sold
2. Category wise Qty sold
3. Sub-channel wise total sales
4. Highest sale in which month
5. Highest selling product

The Analysis Steps

Importing nessesary library, Importing the data by using pandas, Checking if there is any null values by .info(), Creating a Datafream by pandas

for Requariment 1

Created a new colom using dt,strftime for extracting date from the given date column,

Then creating new Datafream using groupby with Month-year column and sum mathod to sum the values of the Quantitys

for Requirement 2

Using pd.Groupby by Catagory with the value of Quantity and storing the dataframe in a variable

for Requirement 3

Creat a new Datafream of grouped data using groupby on Sub-channels with sum() of sales and storing it in a different Variable

for Requirement 4

By appling sort_values in desanding order on an new datafream made by grouping month-year with sum() of sales

For Requirement 5

Creating new Copy of original Datafream as we have to make a colom of product name that don't have any numarical value,

we creat a new colomn of productname in which,

first we replace the numerical values with "---" triple hifon then split the name with "---" and get the desired value,

then creat a new datafream grouping product name with the sum() of sales and sorting it in desending order by using Sort_values

For Requirement 6

Sorting the product name in decending order and storing it in a variable

For Requirement 7

Last save all the variables into a excel file using pd.Excelwriter giving the path of where to save the file and using .to_excel for creating new sheets