Trying to get the average, cardinality and the standard deviation (Pandas)-CodePudding

I'm trying to get the average, cardinality and the standard deviation of a column for each row of a dataframe. I am also trying to do this in a single line. I've been stuck on this question for ages. Thanks

CodePudding user response：

example df:

import numpy as np
import pandas as pd
df = pd.DataFrame(
    {
        'a': [1, 2, np.NaN],
        'b': [5, 2, 2],
        'c': [3, 2, np.NaN],
        'd': [1, 1, 1]
    }
)

     a  b    c  d
0  1.0  5  3.0  1
1  2.0  2  2.0  1
2  NaN  2  NaN  1

You can calculate the values like this using the axis=1 parameter:

df.mean(axis=1)  # average
df.nunique(axis=1)  # cardinality
df.std(axis=1)  # standard deviation

example: df.mean() gives you:

a    1.5
b    3.0
c    2.5
d    1.0

which is for column a: 1 2/2=1.5

and df.mean(axis=1) gives you:

0    2.50
1    1.75
2    1.50

which is for the first row: 1 5 3 1/4 = 2.5

CodePudding user response：

You could transpose and aggregate like this (using @bitflip data as example, thanks):

import numpy as np
import pandas as pd
df = pd.DataFrame(
    {'a': [1, 2, np.NaN],
     'b': [5, 2, 2],
     'c': [3, 2, np.NaN],
     'd': [1, 1, 1]})

                0     1         2
mean     2.500000  1.75  1.500000
nunique  3.000000  2.00  2.000000
std      1.914854  0.50  0.707107