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uk-roberto92's avatar
uk-roberto92
Frequent Visitor
1 year ago
Solved

Python visual: Using parameters from slicer

Hi,

 

I included a Python visual in a PBI Dashboard I am building.

In this PBI I have a selection page with a slicer that propagates to other pages in the report.

 

Is it possible to have a sort of @parameter in the python visual aligned to the slicer?

Ex:

slicer = @parameter (Group A, Group B, ...)

 

Python Visual built on:

df = df[Group] == @parameter ("Group A", "Group B", ...) 

 

Thanks

Need Help
  • DataNinja777's avatar
    DataNinja777
    1 year ago

    Hi uk-roberto92 ,

     

    Yes, you can absolutely use a slicer to control the data in a Python visual in Power BI. The integration is quite seamless. When you add a data field to the "Values" section of your Python visual's configuration, any slicer in your report that is based on that same field will automatically filter the pandas DataFrame that gets passed to your Python script.

     

    You don't need to use a special @parameter or any placeholder syntax in your Python code. Power BI handles the filtering behind the scenes. If you have a slicer for a "Group" column, and the user selects "Group A", the DataFrame (which Power BI names dataset by default) available within your script will only contain rows where the "Group" column is "Group A". You can then write your Python code to work directly on this pre-filtered dataset.

     

    For instance, if you've dragged your "Group" and "Sales" columns into the Python visual's values field, your script can be as simple as plotting the data it receives. The dataset DataFrame will change dynamically as the user interacts with the slicer, and the visual will update accordingly.

    import matplotlib.pyplot as plt

# The 'dataset' DataFrame is already filtered by the slicer.
# There is no need to write additional filtering code.
# This example creates a simple bar plot of the data passed from Power BI.
dataset.plot(kind='bar', x='Group', y='Sales')

# Display the plot in the visual.
plt.show()

     

    Best regards,

2 Replies

  • DataNinja777's avatar
    DataNinja777
    Super User
    1 year ago

    Hi uk-roberto92 ,

     

    Yes, you can absolutely use a slicer to control the data in a Python visual in Power BI. The integration is quite seamless. When you add a data field to the "Values" section of your Python visual's configuration, any slicer in your report that is based on that same field will automatically filter the pandas DataFrame that gets passed to your Python script.

     

    You don't need to use a special @parameter or any placeholder syntax in your Python code. Power BI handles the filtering behind the scenes. If you have a slicer for a "Group" column, and the user selects "Group A", the DataFrame (which Power BI names dataset by default) available within your script will only contain rows where the "Group" column is "Group A". You can then write your Python code to work directly on this pre-filtered dataset.

     

    For instance, if you've dragged your "Group" and "Sales" columns into the Python visual's values field, your script can be as simple as plotting the data it receives. The dataset DataFrame will change dynamically as the user interacts with the slicer, and the visual will update accordingly.

    import matplotlib.pyplot as plt

# The 'dataset' DataFrame is already filtered by the slicer.
# There is no need to write additional filtering code.
# This example creates a simple bar plot of the data passed from Power BI.
dataset.plot(kind='bar', x='Group', y='Sales')

# Display the plot in the visual.
plt.show()

     

    Best regards,