Convert categorical data in pandas dataframe

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I have a dataframe with this type of data (too many columns):

col1        int64
col2        int64
col3        category
col4        category
col5        category

Columns seems like this:

Name: col3, dtype: category
Categories (8, object): [B, C, E, G, H, N, S, W]

I want to convert all value in columns to integer like this:

[1, 2, 3, 4, 5, 6, 7, 8]

I solved this for one column by this:

dataframe["c"] = pandas.Categorical.from_array(dataframe.col3).codes

Now I have two columns in my dataframe - old col3 and new c and need to drop old columns.

That"s bad practice. It"s work but in my dataframe many columns and I don"t want do it manually.

How do this pythonic and just cleverly?

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