Calculating mean, std.dev and variance and creating a new data frame from these calculations in python

Question

My dataframe

date   Stk A     Stk B  Stk C   Stk D
01.01   0.03    0.0102  0.034   0.083232
02.02   0.05    0.017   0.0578  0.13872
03.03   0.04    0.0136          


        

Answer 1

Using pandas library in python

import pandas as pd
stats=pd.DataFrame()
stats["mean"]=data.mean()
stats["Std.Dev"]=data.std()
stats["Var"]=data.var()

And then transpose it like

stats.T

Answer 2

You can do something like this:

option 1

pd.DataFrame([df.mean(), df.std(), df.var()], index=['Mean', 'Std. dev', 'Variance'])

or something like this:

option 2

df2 = df.describe().loc[['mean', 'std']]
df2.loc['variance'] = df2.loc['std']**2

Answer 3

df.describe() will do the trick.

my_df.describe()

                Age
count  37471.000000  
mean      43.047317      
std       20.676562      
min        1.000000     
25%       28.000000     
50%       43.000000     
75%       59.000000 
max      117.000000