#10 Boost Your Power BI with Python Integration inside Power BI

Are you ready to supercharge your Power BI experience with Python scripting? Follow these steps to seamlessly integrate Python into Power BI and unlock powerful data analysis capabilities:

Step 1: Update Power BI Desktop

Always use the latest version for optimal performance. Avoid the AppStore and download directly from Microsoft’s official site:

https://www.microsoft.com/en-us/download/details.aspx?id=58494

Step 2: Install Python & Essential Packages

Download Python from the official site and add two key packages:

pip install pandas matplotlib        

Step 3: Set Up Your Development Environment

Opt for Visual Studio Code as your Python IDE, available here. Environment variables are optional but can be handy!

?You can download from https://code.visualstudio.com/download

Step 4: Enable Python Scripting in Power BI

Navigate to File > Options and settings > Options > Python scripting in Power BI Desktop. Adjust your Python path if needed. Based on your Python installation, you may need to edit your local Python installation path under Detected Python home directories.

Step 5: Develop & Test Your Python Scripts

Write your scripts in VSCode and ensure they run without hitches. Note that Power BI imports only pandas data frames. Scripts running over 30 minutes will time out. Interactive scripts (e.g., user input) will halt.

• Only pandas data frames import, so make sure the data you want to import to Power BI is represented in a data frame.
• Any Python script that runs longer than 30 minutes times out.
• Interactive calls in the Python script, such as waiting for user input, halt the script’s execution.

Step 6: Execute & Verify Your Script in Power BI

• To test if Python was installed and configure properly in your local machine,? select Get data under Home group of the Power BI Desktop ribbon > More > Search for Python.
• In the Get Data dialog box, select Other > Python script > then select Connect.

• On the Python script screen, paste the following Python script into the Script field, and select OK.

import pandas as pd
data = [['Alex',10],['Bob',12],['Clarke',13]]
df = pd.DataFrame(data,columns=['Name','Age'])
print (df)        

• If successfully, the expected output will be as follow > select Load if you want to load data to your model.

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