This browser is no longer supported.
Upgrade to Microsoft Edge to take advantage of the latest features, security updates, and technical support.
![](data:image/svg+xml, %3Csvg xmlns='http://www.w3.org/2000/svg' height='64' class='font-weight-bold' style='font: 600 30.11764705882353px "SegoeUI", Arial' width='64'%3E%3Ccircle fill='hsl(240, 89%, 33%)' cx='32' cy='32' r='32' /%3E%3Ctext x='50%25' y='55%25' dominant-baseline='middle' text-anchor='middle' fill='%23FFF' %3EDS%3C/text%3E%3C/svg%3E)
I using a notebook in Microsoft Fabric and I cannot get the columns to widen. When I watch videos of people doing it. They simply hover over the line between the columns and widen it. But I am not able to do that. How can I get the columns to widen?
The columns in the output tables, I mean
![](data:image/svg+xml, %3Csvg xmlns='http://www.w3.org/2000/svg' height='64' class='font-weight-bold' style='font: 600 30.11764705882353px "SegoeUI", Arial' width='64'%3E%3Ccircle fill='hsl(28.799999999999997, 3%, 12%)' cx='32' cy='32' r='32' /%3E%3Ctext x='50%25' y='55%25' dominant-baseline='middle' text-anchor='middle' fill='%23FFF' %3EA%3C/text%3E%3C/svg%3E)
Hi Daniel Swirsky,
Thank you for reaching out to us on Microsoft Q&A forum.
Can you please specify the exact Learn Path/Module name/Exercise link where you are encountering this error along with the screenshots for reference.
Thank you.
Hi Daniel Swirsky,
https://learn.microsoft.com/en-us/fabric/data-engineering/how-to-use-notebook
Please be aware that, Azure Synapse Notebook allows you to pass only a single value out using the mssparkutils.notebook.exit() function. If you want to pass an entire dataframe, there's no direct way to do this. However, you can work around it.
One common method is to save your dataframe to a file (like Parquet, CSV, or JSON) in a known location in your Azure Data Lake or Blob Storage, and then read that file in your Azure Data Factory (ADF) pipeline. Here is an example of how you can save a dataframe as a CSV file:
df.coalesce(1).write.format('com.databricks.spark.csv').option('header', 'true').save('abfss://your-data-lake@your-storage-account.dfs.core.windows.net/folder/file.csv')
In this example, df is your dataframe, 'com.databricks.spark.csv' is the format you want to write in (CSV in this case), and the last argument is the path where you want to save the file.
In your ADF pipeline, you can read the CSV file using a Copy Activity or another appropriate activity.
The key to this approach is that the notebook and the pipeline have a shared understanding of where the data is being written and read.
If you need to pass only a few fields or some aggregate information about your dataframe, you can create a dictionary or a JSON object, serialize it into a string, and pass that string using mssparkutils.notebook.exit().
# Let's assume df_summary contains some summary information about your dataframe.
df_summary = {"column1_avg": avg1, "column2_max": max2, "column3_min": min3}
summary_str = json.dumps(df_summary)
mssparkutils.notebook.exit(summary_str)
Then, in your ADF pipeline, you can use the @json() function to parse the JSON string back into an object.
Remember, the approach to use depends on your specific needs and the size and complexity of your data.
I hope this helps?
![](data:image/svg+xml, %3Csvg xmlns='http://www.w3.org/2000/svg' height='64' class='font-weight-bold' style='font: 600 30.11764705882353px "SegoeUI", Arial' width='64'%3E%3Ccircle fill='hsl(32, 3%, 13%)' cx='32' cy='32' r='32' /%3E%3Ctext x='50%25' y='55%25' dominant-baseline='middle' text-anchor='middle' fill='%23FFF' %3EMG%3C/text%3E%3C/svg%3E)
Thank you for reaching out to us on Microsoft Q&A forum.
Can you please specify the exact Learn Path/Module name/Exercise link where you are encountering this error along with the screenshots for reference.
Thank you.
Hi Daniel Swirsky,
Thank you for contacting us on Microsoft Q&A forum.
Please follow the below steps to widen columns in Microsoft Fabric.
Please find the below documents for your reference.
If the information is helpful, please accept the answer by clicking the "Upvote" and "Accept Answer" on the post. If you are still facing any issue, please let us know in the comments. We are glad to assist you.
We value your feedback, and it will help us to assist others who might have a similar query. Thank you for your contribution in enhancing Microsoft Q&A.
Thank you.