Normalize columns of pandas data frame

Question

I have a dataframe in pandas where each column has different value range. For example:

df:

A     B   C 1000  10  0.5 765   5   0.35 800   7   0.09 

Any idea how I can normalize the columns of this dataframe where each value is between 0 and 1?

My desired output is:

A     B    C 1     1    1 0.765 0.5  0.7 0.8   0.7  0.18(which is 0.09/0.5) 

Answer 1

one easy way by using Pandas: (here I want to use mean normalization)

normalized_df=(df-df.mean())/df.std() 

to use min-max normalization:

normalized_df=(df-df.min())/(df.max()-df.min()) 

Edit: To address some concerns, need to say that Pandas automatically applies colomn-wise function in the code above.