Data Science Lab
  • What is Data Science Lab?
  • Accessing the Data Science Lab Module
  • Homepage
  • List Projects
  • List Feature Stores
  • Create
    • Create Project
      • Container Status Message
    • Create Feature Store
  • Registered Models and APIs
  • Settings
  • Trash
  • Tabs for a DSL Project
    • Workspace
      • Workspace Folders
        • Repo Folder Attributes
        • Repo Folder Attributes for a Repo Sync Project
        • Utils Folder Attributes
          • Utility Actions
        • Files Attributes
      • Working with the Workspace tab
        • Create
        • Import
          • Importing Notebook
          • Pull from Git
        • Adding File and Folders
      • Linter
      • Git Console
      • Adjustable Repository Panel
    • Data
      • Adding Data
      • Data List Page
    • Model
      • Import Model
      • Explainer Generator
      • Export to GIT/ Model Migration
      • Share a Model
      • Register a Model
      • Unregister a Model
      • Register a Model as an API Service
      • Delete a Model
    • AutoML
      • Creating AutoML Experiment
      • AutoML List Page
        • View Explanation
          • Model Summary
          • Model Interpretation
            • Classification Model Explainer
            • Regression Model Explainer
            • Forecasting Model Explainer
          • Dataset Explainer
  • Data Science Notebook
    • Preview File
    • Save as Notebook
    • .ipynb File Cells
      • Using a Code Cell
      • Using a Markdown Cell
        • Expanding and Collapsing Markdown Cell
      • Using an Assist Cell
    • Resource Utilization Graph
    • Taskbar
    • Actions Icons from Header
    • Notebook Actions
      • Register
        • Export
        • Register as a Job
      • Notebook Version Control
      • Share
      • Delete
      • Information
  • Model Creation using Data Science Notebook
  • Notebook Operations
    • Data
      • Reading Data
      • Copy Path Functionality
    • Secrets
    • Algorithms
    • Transforms
    • Artifacts
    • Variable Explorer
    • Writers
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On this page
  • Adding Data
  • ​Reading the Added Data
  • Project Level Data Tab
  • Reading Multiple Sheets inside an Excel Sheet
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  1. Notebook Operations

Data

The Data options enables a user to add data inside their project from the Data Science Notebook infrastructure.

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Last updated 5 months ago

Adding Data

  • 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.

​Reading the Added Data

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.

Project Level Data Tab

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.

Reading Multiple Sheets inside an Excel Sheet

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.

Please refer to these links: , , and

Adding Data Sets
Uploading and Adding Data Sandbox files
Adding Feature Stores