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yash_robin
New Contributor

Fabric Notebook - Load File

Hi,

 

I am trying to explore fabric notebook, when I try to work with CSV files I am looking for an option to load the CSV file to table programmatically? 

 

Thanks

2 ACCEPTED SOLUTIONS
MatrixMan112
New Contributor II

You can use pipelines to load the CSV file data into your tables.
You can also try notebooks:
https://learn.microsoft.com/en-us/fabric/data-engineering/lakehouse-notebook-load-data

View solution in original post

Anonymous
Not applicable

Hi @yash_robin ,

Thanks for using Fabric Community. 
As I understand you are very new to fabric and try to explore it. 

Here is a very simple code to load any csv data to table using pyspark.

vgchennamsft_0-1714647302542.png

 

df.write.format("delta").saveAsTable("gopi_lake_house.new_table")

 
Additional docs to refer -
Work with Delta Lake tables in Microsoft Fabric - Training | Microsoft Learn

Please refer above docs it will help you to get through few examples.

Hope this is helpful. Please let me know incase of further queries.

View solution in original post

3 REPLIES 3
MatrixMan112
New Contributor II

You can use pipelines to load the CSV file data into your tables.
You can also try notebooks:
https://learn.microsoft.com/en-us/fabric/data-engineering/lakehouse-notebook-load-data

Anonymous
Not applicable

Hi @yash_robin ,

Thanks for using Fabric Community. 
As I understand you are very new to fabric and try to explore it. 

Here is a very simple code to load any csv data to table using pyspark.

vgchennamsft_0-1714647302542.png

 

df.write.format("delta").saveAsTable("gopi_lake_house.new_table")

 
Additional docs to refer -
Work with Delta Lake tables in Microsoft Fabric - Training | Microsoft Learn

Please refer above docs it will help you to get through few examples.

Hope this is helpful. Please let me know incase of further queries.

Anonymous
Not applicable

Hi @yash_robin ,

Glad to know that your query got resolved. Please continue using Fabric Community on your further queries.

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