Embed Python Visuals in Power BI Desktop – Quick Review

Hi Folks,

This post is all about embedding Python visuals in Power BI, you will need to install the respective dependent libraries like Seaborn, Matplotlib when you were creating visuals as we are using the respective libraries.

Thank you @Dr.S.Gomathi for sharing insights at GPPB Tamil Nadu, 2024, while I don’t know that Power BI has this capability. I am writing this down.

The first thing you need to do is to install Python, you can install the latest version from internet. Click here to Download Python for Windows.

Once downloaded and installed in your local machine, you can find a folder created under your Windows Start menu like below.

You need to right click on Python 3.11(64-bit) icon which is the current latest version and then click on open file location.

Then you will be able to see the contents in the folder

You need again right click on Python 3.11 (64 bit) and open its actual contents where the library files reside.

Copy this path, we need this in a while.

Now open Power BI Desktop and navigate to File –> Options and Settings –> Options

Now in the options and settings, you need to select on the Python scripting and specify the path which you just copied above as below.

Now you were ready to use Python visuals in Power BI.

Next step is to click on Python visual as highlighted below

You will be then asked to enable Python scripts as below

You will need to click on Enable as shown above. Once it is done, you are ready to start using Python visuals in Power BI.

Then you need to load data from your DataSource. Here is the link to the excel I have used. Once data is loaded into your Power BI report, you need to select respective data fields which you want to visualize. Here I am using two fields for X and Y axis, then in Power BI Desktop, you should be able to see something like below.

and in order to effectively visualize the sales trends, I will be visualizing the data using Violin Chart, which is using Seaborn library, while the Seaborn is actually based on Matplotlib library. So, I need to make sure I have those two libraries installed in my machine. You can install by using Command Prompt in your PC, you need to enter below commands and press enter to install.

pip install matplot lib

pip install seaborn

Once installed, we can plot using the below command in the python script tab in Power BI Desktop

# The following code to create a dataframe and remove duplicated rows is always executed and acts as a preamble for your script:
# dataset = pandas.DataFrame(Sales, Country)
# dataset = dataset.drop_duplicates()
# Paste or type your script code here:
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
# Set the aesthetic style of the plots
sns.set_style("whitegrid")
# Create a violin plot for Sales Satisfaction across different Product Categories
plt.figure(figsize=(12, 8))
sns.violinplot(x='Year', y='COGS', data=dataset, palette='muted', split=True)
plt.title('Sales by Product Category')
plt.xlabel('Product Category')
plt.ylabel('Customer Satisfaction Rating')
plt.show()

Then you may need to click on run script as highlighted below

This gives your Violin chart showing the sales distribution for different product categories in your Power BI Desktop. If you were facing any problems viewing the report, check the error in the pop-up message displayed by Power BI, you can also follow the Microsoft article on this mentioned in the references.

Hope this helps someone trying to use Python visuals inside Power BI. Same way, you can use different visualizations available with Python which were not available in Power BI by default.

References:

https://learn.microsoft.com/en-us/power-bi/connect-data/desktop-python-scripts

Cheers,

PMDY

Community tools for Power BI Reports Development

Hi Folks,

This blog post is all about the tools developed by the community for Power BI Development over the years.

While I have only mentioned about DAX Studio in my earlier blog posts, this post lists down all the tools available till date.

  1. DAX Studio https://daxstudio.org/ – This is the single most important tool with lots of features.
  2. DAX formatter https://www.daxformatter.com/ – formats  DAX code
  3. DAX Guide https://dax.guide/
  4. Power BI Helper https://powerbihelper.org/ – tool to create documentation for the Power BI
  5. ALM Tool Kit (http://alm-toolkit.com/)- manages the application life cycle of models
  6. Bravo https://www.sqlbi.com/tools/bravo-for-power-bi/ – used for simple Power BI Tasks
  7. Tabular Editor https://tabulareditor.com/ – Used to create and manage Models
  8. Power BI Side Tools https://thebipower.fr/index.php/power-bi-sidetools/ – Increases the productivity during report development
  9. Power BI Embedded Analytics Playground https://playground.powerbi.com/en-us/home – Explore how you can use embedded analytics in your applications
  10. Business Ops – https://powerbi.tips/product/business-ops/ deployment tool for adding external tools extensions to Power BI Desktop   
  11. Power BI Embedder https://github.com/DynamicsNinja/PowerBiEmbedder XrmToolBox plugin that allows you to embed the Power BI report into the CDS form. 
  12. Power BI OptionSet Assistant – https://www.xrmtoolbox.com/plugins/GapConsulting.PowerBIOptionSetAssistant/ Creates a custom entity and populates it with records which represent option-set values
  13. Power Query M Builder https://www.xrmtoolbox.com/plugins/PowerQueryBuilder/ Create Power Query (M) scripts for Dynamics 365 and Power BI.

If I missed any, please let me know in comments.

References:

https://learn.microsoft.com/en-us/power-bi/transform-model/desktop-external-tools

Cheers,

PMDY