UC Volumes: writing xlsx file to volume

[DylanStout]

How to write a DataFrame to a Volume in a catalog?

We tried the following code with our pandas Dataframe:

dbutils.fs.put('dbfs:/Volumes/xxxx/default/input_bestanden/x test.xlsx', pandasDf.to_excel('/Volumes/xxxx/default/input_bestanden/x test.xlsx'))

This results in the error:

([Errno 95] Operation not supported)

on

pandasDf.to_excel('/Volumes/xxxx/default/input_bestanden/x test.xlsx'))

[Kaniz_Fatma]

Hi @DylanStout, The error message “([Errno 95] Operation not supported)” suggests that the operation you’re trying to perform is not supported in the current context.

To write a DataFrame to a Databricks Volume, you’ll need to follow a different approach.

To write a DataFrame to a Volume in a catalog in Databricks, you can follow these steps:

1. Create a New Notebook:

   • In your Databricks workspace, click New in the sidebar, and then select Notebook.
   • Specify a unique name for your notebook and set the default language.
   • Click Connect and select a compute resource¹.

2. Define Variables:

   • In your notebook, define the following variables:

     catalog = "<catalog_name>"
     schema = "<schema_name>"
     volume = "<volume_name>"
     file_name = "new_baby_names.csv"
     table_name = "baby_names"
     path_volume = f"/Volumes/{catalog}/{schema}/{volume}"
     path_table = f"{catalog}.{schema}"
     

     Replace <catalog_name>, <schema_name>, and <volume_name> with your actual Unity Catalog volume names. You’ll save the baby name data into the specified table later¹.

3. Add Data to Your Unity Catalog Volume:

   • Upload your CSV file to the Unity Catalog volume. You can do this by clicking New > Add Data and selecting Upload Files to Volume. Choose the volume or a directory inside it, and then upload your file².

4. Load Data into DataFrame:

   • Create a DataFrame (let’s call it df) by reading the CSV file from your Unity Catalog volume:

     df = spark.read.csv(f"{path_volume}/{file_name}", header=True, inferSchema=True)
     

5. Insert Data into an Existing Table:

   • Insert the data from the DataFrame into an existing table in Unity Catalog:

     df.write.insertInto(path_table + "." + table_name)
     

This should allow you to write your DataFrame to the specified volume in your Unity Catalog. If you encounter any issues, please check your permissions and ensure that Unity Catalog is enabled ....

Let me know if you need further assistance! 😊