This repo is about creating a sales analysis report.
This repo is about analysing some sales data and assessing:
Most Sold Product
I generated some random sales data using libraries like Numpy and Random on VS Code.
Then, using Jupyter lab I was able to clean and organize the data using the pandas library to concatenate all the monthly data into one large CSV file containing all the data.
First, I wanted to see what was the best selling month. So I had to clean the data dropping the nan values and then convert the columns to strings to be able to perform multiplication between the Price and Quantity columns.
Second, I wanted to see which city sold the most in usd. So I created a “City” column, then used the groupby function to add up all the sales by city.
Third, I wanted to see what would be the best time to display ads based on the most common times products were being purchased.
For that I created new columns for hours and minutes, then I used the groupby function again to what were the most common hours for purchases.
Forth, I wanted to find out what items were most often sold together. I imported the Collections library so I could used the Counter function, then I created a new dataframe containing all the order ids, and created a new column to group the items being bought together with the same order id number.
Lastly, I wanted to know which item sold the most. I grouped the items by product and them added up the quantity ordered.
Best Selling month?
Best Selling City?
Products Most Often Sold Together
Most Sold Product