You will learn how to build smart visualizations like correlation plots in Power BI.
A correlation Plot is an important visualization for any data analysis or data science project. Power BI has some small visualization capability and custom visual features are enabling to implement this.
In this blog, we are going to explore the one smart and AI visualizations, named correlation plot.
For this case study, I consider the US Superstore dataset from Kaggle.
- Let’s start with the Get Data option under the Home tab. As this is a CSV file, select the Text/CSV option from the drop-down list
- Select the file named US Superstore data.csv
- After selecting the file, data will be displayed in the below format
- Click on Load and save data.
What is Correlation Plot?
A correlation plot can display the correlation among different measures, and optionally you can create some clusters by correlation coefficient.
If you want to know more about the correlation coefficient, you can go through my blog related statistics.
How to Create a Correlation Plot?
You can find this Correlation Plot under Custom Visual. In Power BI, many custom visuals are based on R packages. This visual uses corrplot R packages.
Now you will create a Correlation Plot step by step.
- Goto Visualization section → Click on Get more visuals.
- Open the “Power BI Visuals” dialog box. Search with “correlation plot”.
- Click on Add button beside on Correlation Plot
4. Select Correlation Plot visual and add it to your current page after clicking on Enable button.
5. Now add some relevant measures to this plot under the Values section.
6. Now you can add some formatting.
7. First enable Labels, increase the font size and change the color.
8. Next enable Correlation plot parameters. You can change the Element shape to shade and keep the default selection for other options.
9. Now you can enable Correlation coefficients to display data labels with modified color, font and number of digits after the decimal point.
10. Lastly enable the Additional Settings and enable Show warnings.
11. Now Correlation Plot is ready to serve.
The plot reveals that there is some negative correlation for the discount with all the other measures. You see a positive correlation between the profit and all other measures, except for the discount. In this way, you can explain this visual to your customers.