📦 Wrap your dataset#

To scan, test and debug your model, you need to provide a dataset that can be executed by your model. This dataset can be your training, testing, golden, or production dataset.

The pandas.DataFrame you provide should contain the raw data before pre-processing (categorical encoding, scaling, etc.). The prediction function that you wrap with the Giskard Model should be able to execute the pandas dataframe.

from giskard import demo, Dataset

wrapped_dataset = Dataset(
    df=demo.titanic_df(),
    target="Survived",  # Ground truth variable
    cat_columns=['Pclass', 'Sex', "SibSp", "Parch", "Embarked"]  # List of categorical columns. Optional, but is a MUST if available. Inferred automatically if not.
    # name="titanic_dataset", # Optional
    # column_types=None # # Optional: if not provided, it is inferred automatically
)

  • Mandatory parameters

    • df: A pandas.DataFrame that contains the raw data (before all the pre-processing steps) and the actual ground truth variable (target). df can contain more columns than the features of the model, such as the sample_id, metadata, etc.

  • Optional parameters

    • target: The column name in dataset corresponding to the actual target variable (ground truth).

    • name: Name of the wrapped dataset.

    • One of:

      • cat_columns: A list of strings representing the names of categorical columns. These are columns that are processed by the model with common categorical pre-processing, such as one-hot encoding. It can be binary, numerical, or textual with a few unique values. If not provided, the column types will automatically be inferred.

      • column_types: A dictionary of column names and their types (numeric, category or text) for all columns of dataset. If not provided, the column types will automatically be inferred.

Note

You can easily revert your Giskard dataset back to a pandas DataFrame. To do so, use the .df method. For more information about Dataset methods, see the API Reference.

Upload your Dataset to the Giskard server#

Uploading your dataset to the Giskard server enables you to:

  • Inspect and debug your dataset

  • Use your dataset as the input for your tests (unit datasets)

To upload your dataset to the Giskard server, go to the page Upload an object to the Giskard server.