How to Create Stunning Visualizations using Python From Scratch

How to Create Stunning Visualizations using Python From Scratch

Data science and data analytics can be beautiful things. Not only because of the insights and enhancements to decision-making they can provide, but because of the rich visualizations about the data that can be created. Following this step-by-step guide using the Matplotlib and Seaborn libraries will help you improve the…

Visualization is an important skill set for a data scientist. A good visualization can help in clearly communicating insights identified during the analysis, and it is a good technique to better understand the dataset. Our brain is wired in a way that makes it easy for us to extract patterns or trends from visual data as compared to extracting details based on reading or other means.

In this article, I will be covering the visualization concept from the basics using Python. Below are the steps to learn visualization from basics,

  • Step 1: Importing data
  • Step 2: Basic visualization using Matplotlib
  • Step 3: More advanced visualizations, still using Matplotlib
  • Step 4: Building quick visualizations for data analysis using Seaborn
  • Step 5: Building interactive charts

By the end of this journey, you would be equipped with everything that is required to build a visualization. Though we will be not covering every single visualization that can be built, you will be learning the concepts behind building a chart, and hence it would be easy for you to build any new charts that are not covered in this article.

The scripts and the data used in this article can also be found in the git repository here. All data used in this article can be found in the “Data” folder within the mentioned git repository, and the scripts are available in the folders ‘Day23, Day 24, and Day25’.

data visualization python

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