有没有办法在条件中使用多种数据类型过滤 Python 中的列？

Question

I am trying to filter columns based on numeric and categorical data types and then create separate list for each for Regression Problems.

Problem is i am not able to do this using .isin(['object','O'])

List of Columns:

Manufacturer 157 non-null object

Model 157 non-null object

Sales_in_thousands 157 non-null float64

four_year_resale_value 121 non-null float64

Vehicle_type 157 non-null object

Price_in_thousands 155 non-null float64

Engine_size 156 non-null float64

Horsepower 156 non-null float64

Wheelbase 156 non-null float64

Width 156 non-null float64

Latest_Launch 157 non-null object

Power_perf_factor 155 non-null float64

I want to do it using .isin([]) as multiple options can be passed in the list but its not working

Below code doesn't work and I am looking for solutions for this code

df.dtypes.loc[df.dtypes.isin(['object','O'])]

Below code works but I dont like this way of writing code as if there are too many options then this code can get unnecessarily long & messy

df.dtypes.loc[(df.dtypes == ('object')) | (df.dtypes == ('O'))] 

Output:

Manufacturer object

Model object

Vehicle_type object

Latest_Launch object

Answer 1

There's a handy helper function for exactly what you're trying to do, select_dtypes

df.select_dtypes(include=['O'])

df.select_dtypes(exclude=['O'])