Get a list of categories of categorical variable (Python Pandas)

Question

I have a pandas DataFrame with a column representing a categorical variable. How can I get a list of the categories? I tried .values on the column but that does not return the unique levels.

Thanks!

Answer 1

I believe need Series.cat.categories or unique:

np.random.seed(1245)  a = ['No', 'Yes', 'Maybe'] df = pd.DataFrame(np.random.choice(a, size=(10, 3)), columns=['Col1','Col2','Col3']) df['Col1'] = pd.Categorical(df['Col1'])  print (df.dtypes) Col1    category Col2      object Col3      object dtype: object  print (df['Col1'].cat.categories) Index(['Maybe', 'No', 'Yes'], dtype='object')  print (df['Col2'].unique()) ['Yes' 'Maybe' 'No']  print (df['Col1'].unique()) [Maybe, No, Yes] Categories (3, object): [Maybe, No, Yes] 

Answer 2

You can also use value_counts(), but it only works when you use it with a column name, with which you'll get the counts of each category as well. Example:

dataframe['Columnn name'].value_counts()

Alternatively, if you want the total count of categories in a variable, you can do this,

dataframe['Columnn name'].value_counts().count()