python - Check which columns in DataFrame are Categorical

Question

I am new to Pandas... I want to a simple and generic way to find which columns are categorical in my DataFrame, when I don't manually specify each column type, unlike in this SO question. The df is created with:

import pandas as pd
df = pd.read_csv("test.csv", header=None)

e.g.

           0         1         2         3        4
0   1.539240  0.423437 -0.687014   Chicago   Safari
1   0.815336  0.913623  1.800160    Boston   Safari
2   0.821214 -0.824839  0.483724  New York   Safari

.

UPDATE (2018/02/04) The question assumes numerical columns are NOT categorical, @Zero's accepted answer solves this.

BE CAREFUL - As @Sagarkar's comment points out that's not always true. The difficulty is that Data Types and Categorical/Ordinal/Nominal types are orthogonal concepts, thus mapping between them isn't straightforward. @Jeff's answer below specifies the precise manner to achieve the manual mapping.

Answer 1

You could use df._get_numeric_data() to get numeric columns and then find out categorical columns

In [66]: cols = df.columns

In [67]: num_cols = df._get_numeric_data().columns

In [68]: num_cols
Out[68]: Index([u'0', u'1', u'2'], dtype='object')

In [69]: list(set(cols) - set(num_cols))
Out[69]: ['3', '4']