How can I normalize the data in a range of columns in my pandas dataframe

Question

Suppose I have a pandas data frame surveyData:

I want to normalize the data in each column by performing:

surveyData_norm = (surveyData - surveyData.mean         


        

Answer 1

Simple way and way more efficient:
Pre-calculate the mean:
dropna() avoid missing data.

mean_age = survey_data.Age.dropna().mean()
max_age = survey_data.Age.dropna().max()
min_age = survey_data.Age.dropna().min()

dataframe['Age'] = dataframe['Age'].apply(lambda x: (x - mean_age ) / (max_age -min_age ))

this way will work...