How to count the number of categorical features with Pandas?

Question

I have a pd.DataFrame which contains different dtypes columns. I would like to have the count of columns of each type. I use Pandas 0.24.2.

I tried:

    dataframe.dtypes.value_counts()

It worked fine for other dtypes (float64, object, int64) but for a weird reason, it doesn't aggregate the 'category' features, and I get a different count for each category (as if they would be counted as different values of dtypes).

I also tried:

    dataframe.dtypes.groupby(by=dataframe.dtypes).agg(['count'])

But that raises a

TypeError: data type not understood.

Reproductible example:

import pandas as pd

df = pd.DataFrame([['A','a',1,10], ['B','b',2,20], ['C','c',3,30]], columns = ['col_1','col_2','col_3','col_4'])

df['col_1'] = df['col_1'].astype('category')
df['col_2'] = df['col_2'].astype('category')

print(df.dtypes.value_counts())

Expected result:

    int64       2
    category    2
    dtype: int64

Actual result:

    int64       2
    category    1
    category    1
    dtype: int64

Answer 1

As @jezrael mentioned that it is deprecated in 0.25.0, dtypes.value_counts(0) would give two categoryies, so to fix it do:

print(df.dtypes.astype(str).value_counts())

Output:

int64       2
category    2
dtype: int64

Answer 2

Use DataFrame.get_dtype_counts:

print (df.get_dtype_counts())
category    2
int64       2
dtype: int64

But if use last version of pandas your solution is recommended:

Deprecated since version 0.25.0.

Use .dtypes.value_counts() instead.