This repository contains a collection of Python notebooks focused on univariate, bivariate, and multivariate analysis visualizations.
The purpose of this project is to provide a cheat sheet for visualizations in Python using various libraries, such as matplotlib and seaborn. These visualizations contain different analyses that provide users with insights about various datasets. I tried to make a cheat sheet from what I learned from Udacity Data Analysis Nanodegree.
These visualizations display a single variable and the distribution of data points in a given dataset. The following types of visualizations have been included:
- Histograms
- Density plots
- Box plots
- Violin plots
These visualizations display the relationship between two variables in a given dataset. The following types of visualizations have been included :- Scatter plots
- Line plots
- Bar plots
These visualizations display the relationship between multiple variables in a given dataset. The following types of visualizations have been included:
- Heatmaps
- Correlation plots
- Pair plots
- 3D plots
To use this cheat sheet, simply run any of the notebooks provided and observe the visualizations generated. Additional explanations and notes are also provided in each notebook for context and understanding.
Contributions are welcome! If you find any errors or want to add additional visualizations, please submit a pull request.