Data Visualization is one of the most important skills that every data scientist should have. Data visualization helps in analyzing data by summarizing the data into graphs, which helps understand the story behind the numbers. There are so many tools that help in data visualization, but many beginners in data science find it difficult to choose a data visualization chart. So if you are one of them who struggle with choosing a data visualization graph, this article is for you. In this article, I will take you through how to choose a data visualization graph according to the data you want to analyze.
Why Do We Need to Choose the Right Data Visualization Graph?
There are so many types of data visualization graphs that you can use. But you cannot randomly choose any graph for visualizing data of any kind. So you must be clear about what you want to analyze and which Data Visualization graph will help you analyze perfectly.
As data science professionals, we use data visualization graphs for:
- visualizing change over time
- visualizing the part-to-whole composition
- visualizing data distribution
- comparing values between graphs
- understanding relationships between variables
- visualizing geographical data
So these are the tasks for which we use data visualization. You will find different types of graphs for each of these tasks. I hope you have understood why we need to choose a data visualization chart. Now, in the section below, I will walk you through how to choose a data visualization chart by introducing you to different types of charts to analyze different types of data.
Here’s How to Choose a Data Visualization Graph
Graphs to Show Change over Time
When we want to analyze the change in a numerical feature according to the time intervals, we can use any graph having time intervals on the x-axis and the values of the features on the y-axis. Below are some of the best data visualization graphs to visualize change over time:
Graphs to Show Part-to Whole Composition
When we want to analyze the part to the whole composition of a feature, we have to use graphs that are best for visualizing each component of a categorical group. Below are some of the best data visualization graphs to visualize part-to whole composition:
Graphs to Show Data Distribution
When we want to analyze the distribution of features of a dataset, we can use graphs that show how the values are distributed in a dataset. Below are some of the best data visualization graphs to visualize data distribution:
Graphs to Compare Values Between Groups
Comparing values between groups means analyzing the numerical values between different segments or categorical features. Below are some of the best graphs to compare data between groups:
Graphs to Understand Relationships Between Variables
Understanding the relationships between variables is one of the most valuable steps in data exploration. It helps in selecting the best features to train a machine learning model. Below are some of the best data visualization graphs to understand relationships between variables:
Graphs to Visualize Geographical Data
Sometimes we work with geographical data, which contains the data about latitudes and longitudes of geographical locations. Below are some of the best graphs to visualize geographical datasets:
So this is how you can choose the right data visualization graph for visualizing your data.
Summary
There are so many types of data visualization graphs that you can use. But you cannot randomly choose any graph for visualizing data of any kind. So you must be clear about what you want to analyze and which Data Visualization graph will help you analyze perfectly. I hope this article has given you a better understanding of choosing a data visualization graph for analyzing the kind of data you are working with. Feel free to ask valuable questions in the comments section below.
