sales_data_analysis_visualization

Data analysis & visualization sales dataset with Python using Matplotlib, Pandas.

Dataset source:

https://www.ibm.com/communities/analytics/watson-analytics-blog/sales-products-sample-data/

Objective:

• Read dataset from csv file and generate pandas dataframes.
• Get information about the dataset using describe() & info().
• Check how much 'Revenue' is being generated by each product.
• Use groupby() to display all products. Also display sum of their revenue.
• Generate a bar graph of 'Product line' & mean of the 'Revenue'.
• Generate a bar graph of 'Product type' & mean of the 'Quantity'.
• Display the sales break down by category.
• Finally bar and pie graph of 'Product line','Product type', 'Quantity'.

Steps To Run:

For this demonstration, I am using the Jupyter Notebook, open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text.

Step 1:

Create a virtual enviroment and install dependencies by running requirements.txt.

$ pip install virtualenv env

$ source env/bin/activate

$ pip install -r requirements.txt

Step 2:

Run the script.

$ jupyter notebook

Bar graph of 'Product line','Product type', 'Quantity'.

Pie graph of 'Product line','Product type', 'Quantity'.