Set of real world data science tasks completed using the Python Pandas library.
To access all of the files I recommend you fork this repo and then clone it locally. Instructions on how to do this can be found here: https://help.github.com/en/github/getting-started-with-github/fork-a-repo
The other option is to click the green "clone or download" button and then click "Download ZIP". You then should extract all of the files to the location you want to edit your code.
Installing Jupyter Notebook: https://jupyter.readthedocs.io/en/latest/install.html
Installing Pandas library: https://pandas.pydata.org/pandas-docs/stable/install.html
In this video we use Python Pandas & Python Matplotlib to analyze and answer business questions about 3 years worth of sales data. The data contains thousands of store purchases broken down by month, product type, cost, purchase address, etc.
We have answered these 5 questions through our data analysis mainly using pandas and matplotlib library.
Q1. What is the overall sales trend?
Q2. Which are the Top 10 products by sales?
Q3. Which are the Most Selling Products?
Q4. Which is the most preferred Ship Mode?
Q5. Which are the Most Profitable Category and Sub-Category?