I am trying to convert a column to int, so i don't have 0 in front of the number and .0 after the number. this is what i am using

data['ID'] = pd.to_numeric(data['ID'], errors='coerce')

but it is not converting the column type

here is image what it looks like.

Please if you can help

CodePudding user response：

This is due to the NaNs that are of float type.

You can use fillna to make the NaNs 0:

data['ID'] = pd.to_numeric(data['ID'], errors='coerce').fillna(0, downcast='infer')

Or to keep the NaN as the new integer NA, use convert_dtypes:

data['ID'] = pd.to_numeric(data['ID'], errors='coerce').convert_dtypes()

CodePudding user response：

You can use int(),

data['ID'] = list(map(lambda x: int(x), data['ID']))