Answers for "normalise min max all columns pandas"

normalise min max all columns pandas

# mean and standard deviation normalisation
normalized_df=(df-df.mean())/df.std()

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

minimum and max value in all columns pandas

#for multiple columns 
min_vals = df[["A","B","C"]].min() #can add how much ever columns
max_vals = df[["D","E","F"]].max() #can add how much ever columns

#for single column
min_val = df["Column"].min() 
max_val = df["Column"].max() 

#to refer to all columns
min_val = df[:].min() 
max_val = df[:].max()