Pandas Library for Data Visualization in Python
In my previous article, I explained how the Seaborn Library can be used for advanced data visualization in Python. Seaborn is an excellent library and I always prefer to work with it, however, it is a bit of an advanced library and needs a bit of time and practice to get used to.
In this article, we will see how Pandas, which is another very useful Python library, can be used for data visualization in Python. Pandas is primarily used for importing and managing dataset in a variety of formats as explained in the article Beginner’s Tutorial on the Pandas Python Library. The data visualization capabilities of Pandas are lesser known. In this article, you will focus on the data visualization capabilities of Pandas.
It is pertinent to mention that like Seaborn, the Pandas data visualization capabilities are also based on the Matplotlib Library. But with Pandas, you can directly plot different types of visualizations directly from the Pandas dataframe which we will see in this article.
Basic Plots
In this section, we will see how Pandas dataframes can be used to plot simple plots such as histograms,