check if multiple columns are object type-CodePudding

I'm importing an Excel file and when I check the datatype of the pandas series some are object and others are int64.

I want to find out if any of the columns passed are of object type.

When I run:

if df['dim_weight'].dtype == object or df['dim_length'].dtype == object or df['dim_height'].dtype == object:

and some of the columns are not an object this works as expected but when I do the inverse:

if not df['dim_weight'].dtype == object or not df['dim_length'].dtype == object or not df['dim_height'].dtype == object:

the check fails. Is there a more efficient way to check for this in Pandas? I ultimately want to check if any of the columns are not a string. Any guidance is greatly appreciated.

CodePudding user response：

Generally in the logic theory, the opposite of (A or B) is (not A) and (not B), not (not A) or (not B).

CodePudding user response：

You can use the attribute dtypes of dataframe to get a series containing the datatypes of all columns, then compare the series with inte64 and reduce with all to create a boolean condition:

if df.dtypes.eq('int64').all():
    # Execute the statements when condition is True