Seeking Advice: Importing Data from Elasticube to Pandas DataFrame in Sisense Jupyter Notebook

[leo82]

I'm looking for help with using Sisense and Jupyter Notebook. Here's what I need to do:

1. Load CSV data into a Sisense Elasticube table (Table A). (this I know how to do)
2. Transfer data from Table A into a pandas dataframe for processing. How?

I found a resource (link below) with good information but it doesn't explain these steps. Has anyone managed to import data from a Sisense Elasticube table into a Jupyter Notebook dataframe? Or are there other ways to load data into Sisense Jupyter Notebook?

Any advice would be much appreciated!

https://docs.sisense.com/main/SisenseLinux/transforming-data-with-custom-code.htm

[rapidbisupport · Accepted solution]

Hello @leo82 ,

To transfer data from Table A to a pandas DataFrame for processing in Sisense ElastiCube, you can easily achieve this if you've enabled the "Custom Code" feature in your Sisense setup. Assuming you have this setup and can add custom code to the ElastiCube:

In your Jupyter Notebook on Sisense, you can use the default Sisense package to import data directly from the ElastiCube into a pandas DataFrame. Here's a sample code snippet for this:

from init_sisense import sisense_conn
data_frame = sisense_conn.get_data_from_cube(table_name="your_table_name", cube_name="your_cube_name")

Replace `"your_table_name"` and `"your_cube_name"` with the actual names of your table and cube. This will allow you to work with the data in pandas for further analysis or processing.

Please note that your import should be in the first / test cell to avoid any issues in building.

Let me know if you need more help with this!

Derek N

RAPID BI
[email protected]

RAPID BI - Sisense Professional Services | Implementations | Custom Add-ons