Data Correlation Visualization in Power BI: A Comprehensive Guide to Charts and Graphs
Exploring different chart types to plot correlated variables.
In any data analysis-related project, data visualization plays an important role.
There is no doubt that data visualization helps to communicate complex information in a way so that you can make better decisions, identify potential problems and provide insights to others more effectively.
There are many ways to find out the correlation among different variables.
In this blog, you will learn how many chart types are available to explore the relationships between two or more variables.
I am using Microsoft Power BI as a visualization tool.
And you will explore and learn the below chart formats.
- Scatter Plot
- Bubble Plot
- Heatmap
- Combo chart
Let’s start.
Scatter Plot
If you must display the relationship between two numeric variables, then you can consider a scatter plot. It defines the correlation between variables.
There are many advantages. Out of that two main advantages are following
- It helps to easily find if there is a correlation or trend between the variables.
- Helps to identify outliers or unusual data points
How to Create Scatter Plot in Power BI
https://www.youtube.com/embed/iLo1lgDivJU?t=119&start=119&end=388
Bubble Plot
A bubble chart is a variation of a scatter plot. It displays the relationship among three numerical variables where 3rd additional variable represents the size of the bubbles.
Some key advantages are following
- This plot allows adding of a third variable to the visualization by using bubble size to represent the value of a third variable. It helps to provide more insights into the relationship between the two main variables.
- It highlights specific data points that may be of interest.
How to Create Bubble Plot in Power BI
https://www.youtube.com/embed/iLo1lgDivJU?t=389&start=389&end=602
Download
Please find the code in the below location
Data Analysis in Power BI — Chapter 16
Heatmap
A heatmap is a graphical representation of data visualizing values using colours.
- It is a two-dimensional representation where the data is organized in a matrix or grid format, and each cell in the matrix is assigned a colour based on its value
Usage:
a)Helps to display the correlation matrix
b)Can be used to display changes over time in data variation. etc.
How to Create Heatmap in Power BI
Download
Data Analysis in Power BI — Chapter 22
Combo Chart
A combo chart is mainly a combination of bar and line charts and has one or two Y axes.
It’s a good option to show the correlation between two numeric variables where the bar represents one variable and the line for the other one.
In Power BI, there are two types of combo charts. They are known as “Line and stacked column chart” and “Line and clustered column chart”.
How to Create Combo Chart in Power BI
In the below video, you will find the steps to create a combo chart. In addition, you will get an idea about Ribbon Chart
https://www.youtube.com/embed/E7y2DO8Jg6Q?t=65&start=65&end=255
Download
Please find the code in the below location
Data Analysis in Power BI — Chapter 12
Line Chart
Line charts help to visualize the correlation between variables over the change of time.
It helps to observe the progression, differences, and patterns in data. Line charts are mainly effective for displaying continuous data, such as stock prices or temperature changes.
How to Create Line Chart in Power BI
https://www.youtube.com/embed/ueenXepkdVY?t=84&start=84&end=255
Download:
Please find the code in the below location
Data Analysis in Power BI — Chapter 11
Conclusion:
In this blog, you learnt about the below items
- Power BI empowers users to visualize and analyze data correlation through its wide range of chart options.
2. Different charts are available for visualizing the relationship and correlation between variables.
3. Users can use charts and interactive features to gain valuable insights, visualize data correlation, and unlock the true potential of their data-driven ambitions.
If you have any questions related to this project, please feel free to post your comments.
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