How to Convert Pandas Categories to Numerical Indices?

Converting Pandas Categories to Numerical Indices

Problem:

Given a dataframe containing categorical values, the task is to convert these categories into numerical indices. Suppose we have countries as categories like this:

cc | temp
US | 37.0
CA | 12.0
US | 35.0
AU | 20.0

Instead of one-hot encodings using get_dummies, the goal is to assign each country an index, such as cc_index = [1,2,1,3].

Solution:

To convert Pandas categories to numerical indices, follow these steps:

1. Change the data type of the categorical column:

   df.cc = pd.Categorical(df.cc)

2. Create a new column to store the category codes:

   df['code'] = df.cc.codes

This will result in a dataframe with the additional code column containing the numerical indices:

   cc  temp  code
0  US  37.0     2
1  CA  12.0     1
2  US  35.0     2
3  AU  20.0     0

Alternatively, you can utilize the astype method to convert the categorical column directly to a categorical column with codes:

df.cc.astype('category').codes

Another option is to use the categorical column as the index of a new dataframe:

df2 = pd.DataFrame(df.temp)
df2.index = pd.CategoricalIndex(df.cc)

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