Calculating and adding average and standard deviation columns to a data frame

问题

I have:

df = pd.DataFrame({'A1': [0.1,0.5,3.0, 9.0], 'A2':[2.0,4.5,1.2,9.0]})

I would like to add 2 columns to the data frame that calculate the average and standard deviation like:

    A1  A2   Mean Stddev
0   0.1 2.0    0    0
1   0.5 4.5    0    0
2   3.0 1.2    0    0
3   9.0 9.0    0    0

回答1:

Let's try with assign using mean and std with parameter axis=1:

df.assign(Mean=df.mean(1), Stddev=df.std(1))

Output:

    A1   A2  Mean    Stddev
0  0.1  2.0  1.05  1.343503
1  0.5  4.5  2.50  2.828427
2  3.0  1.2  2.10  1.272792
3  9.0  9.0  9.00  0.000000

Edit for comment / add CpK:

df.assign(mean=df.mean(1),stddev=df.std(1)).eval('Cpk = (mean +  stddev) / A2')

Output:

    A1   A2  mean    stddev       Cpk
0  0.1  2.0  1.05  1.343503  1.196751
1  0.5  4.5  2.50  2.828427  1.184095
2  3.0  1.2  2.10  1.272792  2.810660
3  9.0  9.0  9.00  0.000000  1.000000

来源：https://stackoverflow.com/questions/47146358/calculating-and-adding-average-and-standard-deviation-columns-to-a-data-frame