PYTHON CHARTS

by R CODER

Welcome! On this site you will learn data visualization with Python. You will find code examples of Python graphs made with matplotlib, seaborn, plotly and other packages

Python charts

CHART TYPES

Distribution

Distribution charts allow visualizing how the data distributes along the support and comparing several groups

Correlation

Correlation charts are useful for visualizing the relationship between two or more variables

Evolution

Evolution charts show how a variable or a set of variables evolve, generally over space or time

Spatial

These plots show geographical areas and their relations based on one or several variables associated with those areas

Part of a whole

Part of a whole charts summarize the data in portions or slices. These types of charts are very useful for representing counts or groups

Ranking

Ranking charts allow visualizing the classification between the observations of a variable or between different variables

See all the charts in the gallery

GRAPHICS LIBRARIES

matplotlib logo

Matplotlib

With a syntax similar to Matlab, matplotlib is the most used low-level charting library in Python

Seaborn logo

Seaborn

seaborn is a matplotlib wrapper. It makes it possible to create beautiful charts with a few lines of code

Plotly logo

Plotly

If you prefer dynamic charts over static, then plotly / plotly Express is your best choice