Install Python in Power BI

How to Install Python and Connect It with Power BI: A Step-by-Step Guide

Power BI is a powerful business analytics tool that helps visualize data and share insights across an organization. By integrating Python with Power BI, you can enhance its capabilities by adding custom scripts, performing advanced analytics, and automating data imports, such as bringing in stock market data for analysis.

In this blog, we’ll walk you through the process of installing Python on your system and connecting it to Power BI. This integration will unlock new possibilities for your data analysis tasks, allowing you to leverage Python’s extensive libraries and functionalities directly within Power BI.

Table of Contents

1. Why Use Python with Power BI?
2. Prerequisites
3. Step 1: Installing Python
4. Step 2: Setting Up Python Environment
5. Step 3: Integrating Python with Power BI
6. Step 4: Importing Stock Data into Power BI Using Python
7. Step 5: Visualizing Data in Power BI
8. Conclusion
9. FAQs

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Why Use Python with Power BI?

Before diving into the setup, let’s explore why you might want to integrate Python with Power BI:

• Advanced Analytics: Python allows you to perform complex calculations and machine learning tasks that are not possible with Power BI alone.
• Automation: Automate the import and transformation of data, such as fetching stock market data, to keep your reports updated without manual intervention.
• Data Manipulation: Use Python libraries like Pandas and NumPy to manipulate data with greater flexibility.
• Custom Visualizations: Create unique visualizations that are not available in Power BI’s native toolset.
• Integration with External APIs: Connect to various data sources and APIs directly from Python, such as financial APIs for stock data.

Prerequisites

Before starting, make sure you have the following prerequisites:

1. Windows Operating System: This guide is tailored for Windows users, but similar steps apply to Mac and Linux.
2. Power BI Desktop: Ensure you have Power BI Desktop installed on your system. You can download it from the official Power BI website.
3. Internet Connection: Required for downloading Python and packages.

Step 1: Installing Python

Download Python

1. Visit the Official Python Website: Go to the Python.org downloads page.
2. Choose the Latest Version: Download the latest version of Python. As of this writing, Python 3.x is recommended.
3. Run the Installer: Execute the downloaded installer file.

Install Python

1. Check the Box “Add Python to PATH”: This is crucial for running Python from the command line.
2. Select “Install Now”: This option will install Python with default settings.
3. Wait for Installation: The installer will set up Python and all necessary components.
4. Verify Installation:
   • Open Command Prompt (cmd).
   • Type python --version to check if Python is installed correctly.
   • You should see the installed Python version displayed.

Bash:

python --version

 

Example output:

Python 3.10.6

 

Step 2: Setting Up Python Environment

Once Python is installed, we need to set up a Python environment for use with Power BI.

Install Python Packages

Power BI leverages Python for data manipulation, so we need to install essential packages such as Pandas and Matplotlib:

1. Open Command Prompt.
2. Install Pandas: Execute the following command to install the Pandas library:Install

   pip install pandas

3. Matplotlib: Execute the following command to install the Matplotlib library:
   

   pip install matplotlib

4. Install NumPy: Execute the following command to install the NumPy library:

   pip install numpy

These packages are crucial for handling data and creating visualizations.

Step 3: Integrating Python with Power BI

After setting up Python, we need to integrate it with Power BI to utilize Python scripts for data manipulation and visualization.

Configure Python in Power BI

1. Open Power BI Desktop.
2. Go to File > Options and Settings > Options:
3. Navigate to Python Scripting:
4. Select Python Home Directory:
   • Set the Python home directory to the path where Python is installed.
   • Default path: C:\Users\YourUsername\AppData\Local\Programs\Python\Python3x
5. Click OK to save settings.

Verify Python Integration

1. Open a New Power BI Report.
2. Go to the “Home” tab > “Get Data” > “More…”.
3. Select “Python Script”:
4. Enter a Sample Python Script to test the connection:python

   import pandas as pd
   import matplotlib.pyplot as plt
   data = {'Category': ['A', 'B', 'C'], 'Values': [10, 20, 30]} 
   df = pd.DataFrame(data) 
   
   # Plotting
   plt.bar(df['Category'], df['Values']) plt.xlabel('Category') 
   plt.ylabel('Values') plt.title('Sample Bar Chart') plt.show()

    

5. Run the Script: If everything is set up correctly, you should see the plot generated by Matplotlib.

Step 4: Importing Stock Data into Power BI Using Python

Now that we have Python integrated with Power BI, let’s import stock data from a financial API. For this example, we’ll use Yahoo Finance to fetch stock data.

Install Yahoo Finance Library

1. Open Command Prompt.
2. Install yfinance: Execute the following command:

   bash

   pip install yfinance

Write Python Script to Fetch Stock Data

1. Open Power BI Desktop.
2. Go to “Home” tab > “Get Data” > “More…”.
3. Select “Python Script” and enter the following script:

   python

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

    

4. Run the Script: This will fetch the stock data for Microsoft from Yahoo Finance and load it into Power BI.

Load Data into Power BI

1. After running the script, a navigator window will appear.
2. Select the DataFrame (e.g., table).
3. Click “Load” to import the data into Power BI.