遍历 Python 中 dataframe 的列并显示分类变量的值计数

Question

I'm new to Python and programming, so this is no doubt a newbie question. I want to show the value counts for each unique value of each categorical variable in a data frame, but what I've written isn't working. I'm trying to avoid writing separate lines for each individual column if I can help it.

#	Column	Non-Null Count	Dtype
0	checking_balance	1000 non-null	category
1	months_loan_duration	1000 non-null	int64
2	credit_history	1000 non-null	category
3	purpose	1000 non-null	category
4	amount	1000 non-null	int64
5	savings_balance	1000 non-null	category
6	employment_duration	1000 non-null	category
7	percent_of_income	1000 non-null	int64
8	years_at_residence	1000 non-null	int64
9	age	1000 non-null	int64
10	other_credit	1000 non-null	category
11	housing	1000 non-null	category
12	existing_loans_count	1000 non-null	int64
13	job	1000 non-null	category
14	dependents	1000 non-null	int64
15	phone	1000 non-null	category
16	default	1000 non-null	category

Code I've written:

for col in creditData.columns:
    if creditData[col].dtype == 'category':
        print(creditData[col].value_counts())

The results:

unknown       394
< 0 DM        274
1 - 200 DM    269
> 200 DM       63
Name: checking_balance, dtype: int64

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-14-6a53236835fc> in <module>
      1 for col in creditData.columns: # Loop through all columns in the dataframe
----> 2         if creditData[col].dtype == 'category':
      3                 print(creditData[col].value_counts())

TypeError: data type 'category' not understood

Answer 1

this works for me

for i in creditData.columns:
    if creditData[i].dtype != 'int64':
        print(creditData[i].value_counts())