This page explains the Copy Path functionality for the added data.
The Copy Path operation can access Sandbox files uploaded with various file types inside the Data Science Notebook.
A file and the Data Sandbox environment variable (@SYS.DATASANDBOX_PATH) can be generated with the Copy Path functionality and accessed inside the Data Science Notebooks.
Please Note: The Copy Path functionality can be used to read Sandbox files. The supported File types for the Copy Path functionality are txt, png, jpg, jpeg, xls, xlsm, and mp4.
Check out the walk-through on using the Copy Path functionality inside a Data Science Notebook.
Navigate to a Data Science Notebook page.
Select a Code cell.
Open the Data tab.
Select a Sandbox file with the supported file types (txt, png, jpg, jpeg, xls, xlsm, and mp4).
Click the Ellipsis icon.
Choose the Copy Path option.
It will provide the file path in the new code cell with the Data Sandbox Environment Variable.
Run the cell.
It will display the same path below, after the successful run.
Provide the code to read the file data from the file path.
Run the cell.
The file data will be accessed and displayed below.
The Data options enables a user to add data inside their project from the Data Science Notebook infrastructure.
Navigate to a Data Science Notebook page (.ipynb file).
Click the Data icon given in the right side panel.
The Data option opens displaying the related icons.
Click on the Add icon.
The Add Data page appears.
The steps to add data may vary based on the selected Data source.
Please Note: Refer to the Adding Data page for more details on how to add data.
Please refer to these links: Adding Data Sets, Uploading and Adding Data Sandbox files, and Adding Feature Stores
Please Note: Using the get_data function datasets and data sandbox files (csv & xlsx files) can be read.
Add a new Code cell to Notebook or access an empty Code cell.
Select a dataset from the Data tab.
The get_data function appears in the code cell.
Provide the df (DataFrame) to print the data from the selected Dataset. A Dataset can be an added dataset, data sandbox file, or feature store.
Run the cell.
The Data preview appears below after the cell run is completed.
The Data Sets/ Sandbox files/ Feature Stores added to a Data Science Notebook will also be listed under the Data tab provided under the same project. Hence, the added datasets will be available for all the Data Science Notebooks created or imported under the same project.
Check out the illustration to read multiple sheets in a Notebook cell.
Add an Excel file with multiple sheets to a DS Project.
Insert a Markdown cell with the names of the Excel sheets.
Insert a new code cell.
Use a checkbox next to read data.
The get_data function in the code cell.
Run the code cell.
The data preview will appear below.
Select another datasheet name and copy it from the markdown cell.
Paste the copied datasheet name in the code cell that contains the get_data function.
Run the code cell.
The data preview will be displayed below.
This section explains the steps to read the added Data inside a Data Science Notebook.
Please Note: Using the get_data function datasets and data sandbox files (csv & xlsx files) can be read.
Add a new Code cell to Notebook or access an empty Code cell.
Select a dataset from the Data tab.
The get_data function appears in the code cell.
Provide the df (DataFrame) to print the data from the selected Dataset. A Dataset can be an added dataset, data sandbox file, or feature store.
Run the cell.
The Data preview appears below after the cell run is completed.
The Data Sets/ Sandbox files/ Feature Stores added to a Data Science Notebook will also be listed under the Data tab provided under the same project. Hence, the added datasets will be available for all the Data Science Notebooks created or imported under the same project.
Check out the illustration to read multiple sheets in a Notebook cell.
Add an Excel file with multiple sheets to a DS Project.
Insert a Markdown cell with the names of the Excel sheets.
Insert a new code cell.
Use a checkbox next to read data.
The get_data function in the code cell.
Run the code cell.
The data preview will appear below.
Select another datasheet name and copy it from the markdown cell.
Paste the copied datasheet name in the code cell that contains the get_data function.
Run the code cell.
The data preview will be displayed below.
