Create R or Python visuals in Power BI

Power BI is a powerful analytics tool that allows users to visualize and analyze data in a user-friendly manner. While Power BI provides various out-of-the-box visualizations, users also have the option to create their own visuals using R or Python scripts. In this article, we will explore how to create R or Python visuals in Power BI.

Enabling R or Python scripting in Power BI

Before we dive into the process of creating R or Python visuals, it is important to note that this feature requires enabling the “R script visuals” and “Python scripting” options in the Power BI Desktop settings. Once these options are enabled, users can start leveraging R or Python scripts to create custom visuals.

Creating an R visual in Power BI

To create an R visual in Power BI, follow these steps:

1. Open Power BI Desktop and go to the “Home” tab.
2. Click on the “R script” button in the “Visualizations” section. This will add an empty R visual to the canvas.
3. Drag and drop the desired fields from the dataset onto the R visual.
4. Write the R script inside the script editor that appears on the right side. You can utilize R’s extensive library ecosystem to perform data manipulations and create visualizations.
5. Once the script is written, click on the “Run” button to execute the R script and generate the visual.

Creating a Python visual in Power BI

Similarly, to create a Python visual in Power BI, follow these steps:

1. Open Power BI Desktop and go to the “Home” tab.
2. Click on the “Python visual” button in the “Visualizations” section. This will add an empty Python visual to the canvas.
3. Drag and drop the desired fields from the dataset onto the Python visual.
4. Write the Python script inside the script editor that appears on the right side. You can leverage popular Python libraries like Pandas, Matplotlib, or Seaborn to manipulate data and create visualizations.
5. Once the script is written, click on the “Run” button to execute the Python script and generate the visual.

Passing data to R or Python scripts

Power BI provides a convenient way to pass data between the dataset and R or Python scripts. Users can access the data from within the script using the dataset object.

Example: Creating visuals using R and Python

Here’s an example of how to create a scatter plot using R script in Power BI:

library(ggplot2)
ggplot(data = dataset, aes(x = column1, y = column2)) +
geom_point()

And here’s an example of creating a bar plot using Python script in Power BI:

import pandas as pd
import matplotlib.pyplot as plt

df = dataset[['column1', 'column2']]
df.plot(kind='bar', x='column1', y='column2')
plt.show()

Conclusion

By utilizing R or Python scripts in Power BI, users can create highly customized and interactive visuals that go beyond the capabilities of the built-in visualizations. This empowers users to tailor their analytics solutions to their specific needs.

In conclusion, creating R or Python visuals in Power BI is a powerful way to enhance data visualization and analysis. By leveraging the extensive capabilities of R and Python, users can create custom visuals that suit their specific requirements. So, start exploring the possibilities and unleash the full potential of your data-driven insights using R or Python visuals in Power BI.