EDA default

This transform analyzes the data and returns various details such as total row count, null count in each column, not null count, null ratio, unique values, frequency history, histogram, most frequent values in the column, data type of each column, largely missing column, constant columns in a dataset, low cardinality column, and binary column (which has only two values such as yes or no, female or male and so on)

tags: [“EDA”]

Parameters

The table gives a brief description about each parameter in EDA default transform.

Name:

The name for the transform. By default, a name is populated. However, you can provide a custom name for the transform.

Input Dataset:

The file name of the input dataset. You can select the dataset that was uploaded from the drop-down list. (Required: True, Multiple: False)

Output Dataset:

The file name with which the output dataset is created with an overview of data. (Required: True, Multiple: False)

The sample input for this transform looks as below:

The output after running the EDA Default transform on the dataset appears as below.

How to use it in Notebook

The following is the code snippet you must use in the Jupyter Notebook editor to run the EDA default transform: