Data Science Simplified

The Perfect Plotting Guide For Data Science Practitioners

Can’t Decide Which Plot To Choose? Not Anymore

Photo by charlesdeluvio on Unsplash

Data visualization is an essential skill for any data scientist. Choosing the right plot can make or break your analysis, helping stakeholders grasp insights effortlessly. This guide will walk you through the most commonly used plots when to use them, and Python code snippets to get started.

1. Understanding the Data Types

Before choosing a visualization, identify the type of data you are working with:

• Categorical Data: Labels or groups (e.g., gender, product category)
• Numerical Data: Continuous or discrete numbers (e.g., age, revenue)
• Time Series Data: Data indexed by time (e.g., stock prices, temperature readings)
• Relational Data: Data that shows relationships between variables (e.g., correlations)

2. Choosing the Right Plot for the Right Purpose

A. Comparison

1. Bar Chart

• Use When: Comparing categorical data.
• Common Mistake: Using too many bars makes it…