How to efficiently convert categorical data to numerical indices in Pandas?

Pandas: Conversion of Categories to Numerical Indices

To convert categories in a Pandas dataframe to numerical indices, we can follow the efficient method provided by a user:

Step 1: Categorize the Column
Firstly, convert the target column (in this case, cc) to a categorical type:

<code class="python">df.cc = pd.Categorical(df.cc)</code>

Step 2: Capture Category Codes
Create a new column named code to store the category codes:

<code class="python">df['code'] = df.cc.codes</code>

Result:

The dataframe now includes a code column with indices corresponding to the categories:

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

Additional Options:

• To retrieve the codes without modifying the DataFrame:

<code class="python">df.cc.astype('category').codes</code>

• To use the categorical column as an index:

<code class="python">df2 = pd.DataFrame(df.temp)
df2.index = pd.CategoricalIndex(df.cc)</code>

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