Starting December 3, join live sessions with database experts and the Microsoft product team to learn just how easy it is to get started
Learn moreGet certified in Microsoft Fabric—for free! For a limited time, get a free DP-600 exam voucher to use by the end of 2024. Register now
Hi,
Cornelia here. I am really excited to participate in this Hackathon!😁
I am trying to use Data Wrangler in order to generate a summary of a dataset.
I can save the csv or the generated Python code by clicking on specific buttons but I would need to automate this code or csv generation inside a data pipeline. Is there such a posibility or a workaround to use Data Wrangler in this way?
Thanks!
Solved! Go to Solution.
Hi Cornelia,
If I understand you correctly, you'd like to describe a dataset automatically/programatically, the way data wrangler does in python notebooks. I don't know that there is an api to use the data wrangler programatically.
what I can suggest is either using the dataframe description capabilites in spark:
https://spark.apache.org/docs/3.1.1/api/python/reference/api/pyspark.sql.DataFrame.describe.html
or generate the description directly in the dataset (assuming we're talking about pbi datasets = semantic models) using MCode
https://learn.microsoft.com/en-us/powerquery-m/table-schema
https://learn.microsoft.com/en-us/powerquery-m/table-profile
hope this helps!
Thank you for your help! 😁
Even if Data Wrangler seems pretty good at generating python code for describing data, I ended up creating some custom pyspark functions - easier to modify and automate.
Hi Cornelia,
If I understand you correctly, you'd like to describe a dataset automatically/programatically, the way data wrangler does in python notebooks. I don't know that there is an api to use the data wrangler programatically.
what I can suggest is either using the dataframe description capabilites in spark:
https://spark.apache.org/docs/3.1.1/api/python/reference/api/pyspark.sql.DataFrame.describe.html
or generate the description directly in the dataset (assuming we're talking about pbi datasets = semantic models) using MCode
https://learn.microsoft.com/en-us/powerquery-m/table-schema
https://learn.microsoft.com/en-us/powerquery-m/table-profile
hope this helps!
Once you have the Python code generated with data wrangler you can put it in a cell of a notebook and from the notebook schedule a data pipeline run of the notebook.
Starting December 3, join live sessions with database experts and the Fabric product team to learn just how easy it is to get started.
Check out the November 2024 Fabric update to learn about new features.