Car Sales Performance Analysis with the Python Libraries Pandas, Matplotlib and Seaborn (on Open Data)

Goal

 
  • Analyzing in Detail Car Sales Performance (from open data), from Data Processing and Cleaning to Data Visualization, with the Python libraries Pandas, Matplotlib and Seaborn.

Result

  • Several Visualization Charts (Histogrammes, Pie charts, Boxplots ect) analyzing in detail Car Sales Performance:

           * Gross Sales in the last 20 Years

           * Number of Sold Cars in the last 20 Years

           * Average Price of Sold Vehicles by Body Type and Fuel Type

           * Average Price of Sold Vehicles by Fuel Type and Mileage Level

           * Pie Charts on several Car Sales Statistics

           * Average Price of Sold Vehicles by Body Type and Mileage Level

           * Top 20 Car Makers‘ Gross Sales (in all years)

           * Top 20 Car Makers’ Number of Sold Cars (in all years)

           * Volkswagen’s Number of Sold Cars (in all years) by Type of Engine

           * Top 20 Mercedes-Benz’s Models Sold (in all years)

           Ect.

Examples of the work done
Sales Performance in the last 20 Years
Number of Sold Cars in the last 20 Years
Average Price of Sold Vehicles by body Type and Fuel Type
Average Price of Sold Vehicles by Fuel Type and Mileage Level
Pie Charts on several Car Sales Statistics
Average Price of Sold Vehicles by Body Type and Mileage Level
Top 20 Car Makers' Gross Sales
Top 20 Car Makers' Number of Sold Cars
Volkswagen's Number of Sold Cars (in all years) by Type of Engine
Top 20 Mercedes-Benz's Models Sold (in all years)

Details

Data Bring & Data Discovery
  • Car Sales Data file downloaded from Github site.
Data Analysis & Data Cleaning
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