getdummies
get_dummies is a function in the pandas library that converts categorical variables into dummy or indicator variables. It takes a DataFrame or Series and returns a new DataFrame where each category value in the selected columns is represented by a separate binary column. The value is 1 if the observation belongs to that category and 0 otherwise. The function can be configured with parameters such as columns to encode, prefix and prefix_sep to control new column names, and dummy_na to create an extra column detecting missing values. In addition, drop_first can be set to True to drop the first category in each encoded column, which helps avoid multicollinearity in some models. The sparse parameter can request a sparse representation to save memory on large datasets.
get_dummies can be applied to multiple columns by passing a list to columns, or to the whole
Limitations include high dimensionality when many categories exist, potential sparsity, and the loss of information about