Missing Data
Explore techniques to merge retail sales feature data and identify missing values using pandas. Understand the importance of detecting missing data for accurate preprocessing and prepare for methods to handle these gaps in your machine learning projects.
We'll cover the following...
We'll cover the following...
Chapter Goals:
- Merge the two DataFrames containing the feature data
- Learn how to identify features with missing data
A. Merging the features
Both the features_df and stores_df DataFrames contain feature data, i.e. data related to the stores or weeks that correspond to the rows in train_df. Remember each feature is a column of the DataFrame, and ...