Data Science & Machine Learning - 6.1 Matplotlib & Its Installation

Hi friends,

Welcome to this post on Data Visualization under Data Science & Machine Learning. In the previous post, we performed some practical data analysis using Pandas on the Kaggle SF Salaries Dataset. In this post, we'll learn about Matplotlib, one of the most popular Python libraries for visualizing our results using various plots. 

About Matplotlib [1]

1. Matplotlib is a Python 2D plotting library which produces high quality figures in a variety of hardcopy formats and interactive environments across platforms
2. It allows us to generate plots directly from NumPy Arrays and Pandas DataFrames which makes it even more popular
3. It can be used in Python scripts, the Python and IPython shell, the jupyter notebook, web application servers, etc.
4. It is widely said that Matplotlib tries to make easy things easy and hard things possible

Here are some of the plots supported by the Matplotlib library:

Image source: Matlplotlib

Matplotlib Installation

Just like the installation of other Python libraries such as NumPy/Pandas, it is recommended to use the Anaconda distribution of Python in order to install Matlplotlib as well. You can see the installation of Anaconda distribution of Python here. Once you have that installed, you can install Matplotlib by running the following command in the command prompt:

conda install matplotlib

You can still install Matplotlib even if you don't have the recommended Anaconda distribution of Python (not recommended) using the following command:

pip install matplotlib

You can see the list of various plots supported by Matplotlib from this link. Now that we have installed Matplotlib successfully on our systems, we will start using the Matplotlib library starting with basic plots from the next post.