Data Visualization using Functional/Object Oriented approach


Data Visualization is the graphical representation of data which helps us in storytelling. This can be seen mostly as an art and science. To communicate the results and findings in a better and comprehensive way we usually use plots, charts, statistical graphics and other tools.

Data Visualization is a very powerful tool. It will enable users to understand and make sense of large amounts of data in less time. There are usually many types of plots that we usually use. Some of the more common ones used in businesses are the line and bar plots. These are used to see the trends. We can carry out market analysis and compare metrics across different groups of businesses.

We can also use scatter plots in order to carry out different correlation analysis. Similarly there are many different charts and plots. It usually depends on one’s creativity on how he/she wants to tell the story using Data Visualization.

In this post we will discuss about visualizing data using python package — matplotlib. This post will mostly cover the functional and object oriented way of visualizing the data. However, if you want to learn visualizing data using predefined statements and passing different parameters associated with the plots then refer this post

Some of the visualizations that we will cover in this post are as follows:

  1. Barplot
  2. Scatter
  3. Histogram
  4. Box and whisker plot


  3. Data Science with Python: Combine Python with machine learning principles to discover hidden patterns in raw data by Rohan Chopra, Aaron England, Mohamed Noordeen Alaudeen