Here is my list of top 10 Python libraries that you can use to plot the data graphs.
MATPLOTLIB
This is a widely-used library for creating static, animated, and interactive visualizations in Python. It is highly customizable and provides a wide range of options for creating a variety of plots and charts.
SEABORN
This library is built on top of Matplotlib and provides a high-level interface for creating beautiful and informative statistical graphics. It is particularly useful for creating visualizations for statistical analysis.
BOKEH
This library is designed for creating interactive visualizations that can be displayed in a web browser. It is particularly useful for creating complex and responsive visualizations for data exploration.
PLOTLY
This library allows you to create a wide range of interactive and animated visualizations in Python. It is particularly useful for creating visualizations for Data Science applications, as it includes features such as statistical transformations and data filtering.
ALTAIR
This library is designed for creating statistical visualizations in Python. It is built on top of the Vega-Lite visualization grammar, which allows you to create concise and declarative visualizations with minimal code.
FOLIUM
This library is designed for creating interactive maps in Python. It is particularly useful for creating visualizations of spatial data and is built on top of the leaflet.js library.
GGPLOT
This library is inspired by the ggplot2 library in R and allows you to create a wide range of statistical graphics in Python. It is particularly useful for creating visualizations for statistical analysis and is known for its ability to create highly customizable plots.
PYGAL
This library is designed for creating static and interactive visualizations in Python. It is particularly useful for creating simple and clean visualizations for data exploration and is known for its ability to create interactive SVG charts.
GLEAM
This library is designed for creating interactive visualizations in Python. It is built on top of the Bokeh library and is particularly useful for creating visualizations for data exploration and dashboard applications.
GEOPLOTLIB
This library is designed for creating geospatial visualizations in Python. It is built on top of the Matplotlib library and is particularly useful for creating visualizations of spatial data such as maps and choropleth plots.
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