Explore and Engineer Features

EFS #3 EDA with Python, Pandas and Jupyter

Description

Profile the cleaned data, choose candidate target variable(s) Y, and construct a feature table plus first-pass relationship checks (crosstabs, correlations) between candidate features and Y.

Activities Flow (5)
cluster_explore_data_and_find_signal Explore Data and Find Signal activity_413 EFS1 Compute descriptive statistics per candidate variable activity_414 EFS2 Choose candidate target variable(s) Y activity_413->activity_414 activity_415 EFS3 Engineer and derive features activity_414->activity_415 activity_416 EFS4 Cross-tabulate categorical candidates against Y activity_415->activity_416 activity_417 EFS5 Compute correlation/covariance and significance between features and Y activity_416->activity_417