Reverse z Score pandas dataframe

I am using this to compute the z score of my dataframe:

df_z=df.apply(zscore)

Is there a reverse operation that can give me the orginal values?

There is no built-in way to go from df_z (z scores) back to df (original values). However, you can do it fairly easily as follows:

Step 1: Keep track of the mean and standard deviations of all of the original variables. Perhaps like this:

mean_std={}
for var in df.columns:
    mean_std[var]=(df[var].mean(), df[var].std())

Step 2: Convert back to z scores

def reverse_zscore(pandas_series, mean, std):
    '''Mean and standard deviation should be of original variable before standardization'''
    yis=pandas_series*std+mean
    return yis

original_mean, original_std = mean_std[var]
original_var_series = reverse_zscore(df_z[var], original_mean, original_std)

Alternatively, just store your original dataframe somewhere