Add an R or Python visual
If you use the R or Python programming language, you can use them to visualize your data within Power BI Desktop. Power BI Desktop has an out-of-the-box visualization option for both R and Python that you can access on the Visualizations pane, and the process for creating these visuals is almost the same. You can also import a custom R or Python visual from Microsoft AppSource.
If you decide to use an R or Python visual, and you want to refresh the data in Power BI service, you'll need to use a personal gateway. For more information, see Use personal gateways in Power BI.
Create an R visual
Before you create the R visual, you must install R on your local computer so that Power BI Desktop can run R scripts. You can download and install R for free from many locations, including the Microsoft R Application Network and the CRAN Repository.
When you have downloaded and installed R, Power BI enables it automatically, but you should verify that it has been enabled in the correct location. In Power BI Desktop, select File > Options and settings > Options and then select R scripting in the Global options list. Verify that your local R installation is specified in the Detected R home directories drop-down menu and that it properly reflects the local R installation that you want Power BI Desktop to use. In the following image, the path to the local installation of R is C:\Program Files\R Open\R-3.5.3.
When you've verified your R installation, you can create the R visual.
Select the R visual icon in the Visualizations pane and then select Enable on the window that displays. You'll then see a placeholder R visual image on the report canvas, with the R script editor underneath.
Next, in the Field panel, select the fields that you want to use in your script. They will display in the Values section in the Visualizations pane. You'll use the data in these fields to create a plot.
As you select or remove fields, supporting code in the R script editor is automatically generated or removed. Based on your selections, the R script editor generates the following binding code:
The editor created a dataset dataframe with the fields that you added.
The default aggregation is: do not summarize.
Similar to table visuals, fields are grouped and duplicate rows appear only once.
When you have selected the fields, you're ready to write an R script that results in plotting to the R default device. When the script is complete, select Run from the R script editor title bar.
Power BI Desktop identifies the plot and presents it on the canvas.
Create a Python visual
No prerequisites exist for creating a Python visual, so you can start right away in Power BI Desktop by selecting the Python visual icon in the Visualizations pane. Select Enable on the window that displays, and then you'll then see a placeholder Python visual image on the report canvas, with the Python script editor underneath.
You can continue creating a Python visual in the same way as you did when creating the R visual. In summary, you would select the fields, write the Python script, and then select Run from the Python script editor title bar.
Import an R or Python visual
To import an R or Python visual from AppSource, in the Visualizations pane, select the Get more visuals icon and then select Get more visuals. On the window that displays, locate and select the R or Python visual that you want to import and then select Add.
The new visual icon will appear under the other visual icons in the Visualizations pane.