How to Convert Pandas Categorical Columns to Numerical Indices Without `get_dummies` and `numpy`?

Convert Pandas Categories to Numbers

Consider a DataFrame with a categorical column, such as country codes:

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

To convert these categories to indices, avoiding the use of get_dummies and numpy, consider the following steps:

1. Categorize the Column: Convert the categorical column to a categorical type:

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

2. Retrieve Category Codes: Use the .codes attribute to retrieve the integer codes for each category:

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

The resulting DataFrame will include a new column called code with 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 obtain the category codes without modifying the DataFrame:

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

3. Use as Index: If desired, you can use the categorical column as an index for another DataFrame:

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

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