VW used cars analysis towards data visualization with python. Analysis of the data set through comparison of different columns with one another, using Bar Plot, Scatter Plot, Histogram, Distribution Plot, ECDF Plot, Violin Plot and Box Plot.

Objective:

1. Data Visualization using NumPy and Pandas
2. Importing necessary python packages
3. Reading excel (.csv) file
4. Finding number of unique values present in the DataFrame
5. Writing functions in Python
6. Data Visualization by using Bar Plot
7. Changing the context of a plot
8. Creating subplots
9. Histogramic Analysis for VW Used Cars Based on Year, Price, Mileage and mpg
10. Probabilistic Analysis of VW used Cars for Price and Mileage
11. Distributive Analysis of VW used cars Price for fuelType 12.Boxplot for VW cars price and mileage analysis based on fuelType and transmission respectively

Visualizing of the dataset:

1. Visualizing the dataset through different plots.
2. Top 5 selling cars in the dataset
3. The average selling price of the top 5 selling car models
4. The toatl sell of the top 5 selling car models
5. Data set Aggregation and exploratory data analysis based on model, transmission and fuel type of the VW cars.

Data Visualization: In this project, the dataset has been visualized through observation, using Bar Plot, Scatter Plot, Histogram, Distribution Plot, ECDF Plot, Violin Plot and Box Plot.

Machine Learning:

1. One-hot encoding
2. Linear Regression
3. Model training result prediction
4. Comparison of actual and predicted target variable

Dataset Source: https://www.kaggle.com/aishwaryamuthukumar/cars-dataset-audi-bmw-ford-hyundai-skoda-vw