Python: Data Visualization Libraries

Today Python is one of the most used programming languages in the world. No wonder Python is leading in data visualization as well. Due to the rich set of libraries such as Matplotlib, Seaborn, ggplot, Bokeh, Plotly, Pygal, Altair, Geoplotlib the list goes on, the Python stands out.

Matplotlib

This is the first visualization library in Python. Matplotlib is known as the grandfather of all the data visualization libraries in Python. Many other libraries are developed based on Matplotlib. It’s simple and powerful to develop visualizations. Wide range of graphs from histogram to heat plot to line plot can be plotted with Matplotlib.

Seaborn

Seaborn is well-known library for data visualization. Built on top of Matplotlib. Seaborn’s default styles and color palettes are more advanced than Matplotlib. Seaborn higher-level library, meaning it’s easier to generate certain kinds of plots, including time series, violin plots.

ggplot

ggplot is a Python visualization library identical to R’s ggplot2 and graphics grammar. If you are keenly interested in graphics grammar without having a second thought, go ahead with ggplot. It operates differently as compared to Matplotlib, it works with layer components one by one to develop a full plot. For example, we can start with axes, and then, add points, then a line, a trend line etc.

Bokeh

Bokeh is like ggplot, is also based on the grammar of graphics. It supports streaming and real-time data. It’s ability to develop web-ready, interactive we can easily integrate with JSON, HTML or interactive applications.

Plotly

The Plotly is well known as an online platform for data visualization. Like Bokeh, Plotly’s strength lies in making interactive plots. It offers some unique charts such as ‘contour’ plots, which are not available in other libraries.

Pygal

Like Bokeh and Plotly the Pygal also offers interactive plots to integrate with web applications. Pygal holds a unique ability to develop charts as SVG, it differentiates from others. It’s amazing to use Pygal for smaller data set but if the data set is large then it becomes slothful.

Geoplotlib

Geoplotlib is a toolbox used for plotting geographical data with the map. It offers a variety of charts like a heat map, dot-density maps. Since most of the Python libraries do not offer maps. It’s amazing to have a dedicated library for map.