Create a Power BI Report With Python Jupyter Notebook For Beginners

Introduction

In this tutorial, you will learn how to create a Power BI report using Python in a Jupyter Notebook. This step-by-step guide will walk you through setting up your environment, installing necessary packages, and authenticating your Power BI account, all the way to generating a report.

Step 1: Set Up Your Python Environment

1. Install Python: Ensure you have Python installed on your machine.
2. Launch Terminal: Open your terminal or command prompt.
3. Create a Virtual Environment:
   • Run the following command to create a virtual environment named power_bi_jupyter_demo:

     python -m venv power_bi_jupyter_demo
     

4. Activate the Virtual Environment:
   • For macOS/Linux:

     source power_bi_jupyter_demo/bin/activate
     

   • For Windows (Command Prompt):

     power_bi_jupyter_demo\Scripts\activate
     

   • For Windows (PowerShell):

     .\power_bi_jupyter_demo\Scripts\Activate.ps1
     

Step 2: Install Required Packages

1. Install Jupyter Notebook: Run the following command to install Jupyter Notebook:

   pip install notebook
   

2. Install Additional Libraries:
   • Install the following libraries:

     pip install ipympl
     pip install powerbi-client
     pip install pandas
     

Step 3: Launch Jupyter Notebook

1. Start Jupyter Notebook: Run the following command to launch Jupyter Notebook:

   jupyter notebook
   

2. Create a New Notebook: Click on "New" and select "Python 3" to create a new notebook.

Step 4: Import Libraries and Load Data

1. Import Necessary Libraries:

   from powerbi.client import QuickVisualize, GetDataSetConfig, Report
   import pandas as pd
   

2. Load Your Dataset:
   • Download the Financial Sample dataset from this link.
   • Use the following code to read the dataset:

     df = pd.read_csv('path_to_your_file/Financial Sample.csv')
     

   • Replace 'path_to_your_file/Financial Sample.csv' with the actual path to your downloaded file.

Step 5: Authenticate Your Power BI Account

1. Choose an Authentication Method:

   • Device Code Login: This method is useful if you do not have the right device.

     auth = DeviceCodeLoginAuthentication()
     

   • Interactive Login: If you have saved your credentials, you can use:

     auth = InteractiveLoginAuthentication()
     

2. Connect to Power BI:

   • Use the following code to authenticate and connect:

     pbi_visualize = QuickVisualize(df, auth)
     

Step 6: Create Your Power BI Report

1. Initialize the Report:

   report = Report(auth, df)
   

2. Open the Generated Report:
   • To visualize your report, you can print it or open it in an HTML report viewer:

     print(report)
     

Conclusion

You have successfully created a Power BI report using Python in a Jupyter Notebook. Key points to remember include setting up a virtual environment, installing necessary packages, authenticating your Power BI account, and loading your dataset.

Next steps could include customizing your report further or exploring additional datasets to analyze. Happy reporting!