Apply function row wise on pandas data frame on columns with numerical values

Question

I have the following data frame:

import pandas as pd
df = pd.DataFrame({'AAA' : ['w','x','y','z'], 'BBB' : [10,20,30,40],'CCC' : [100,50,-30,-50]})

Which looks like this:

In [32]: df
Out[32]:
  AAA  BBB  CCC
0   w   10  100
1   x   20   50
2   y   30  -30
3   z   40  -50

What I want to do is to perform function operation on every row for every column except those with non-numerical value (in this case AAA). In the real case the non-numerical case is always on first column, and the rest (could be greater than 2 columns) are always numerical.

The final desired output is:

  AAA  BBB  CCC  Score
0   w   10  100  110
1   x   20   50   70
2   y   30  -30    0
3   z   40  -50  -10

I tried this but failed:

import numpy as np
df["Score"] = df.apply(np.sum, axis=1)

What's the right way to do it?

Update2:

This is the code that give SettingWithCopyWarning. Please fresh start the ipython for testing.

import pandas as pd
import numpy as np 
def cvscore(fclist):
    sd = np.std(fclist)
    mean = np.mean(fclist)
    cv = sd/mean
    return cv

def calc_cvscore_on_df(df):
    df["CV"] = df.iloc[:,1:].apply(cvscore, axis=1)
    return df

df3 = pd.DataFrame(np.random.randn(1000, 3), columns=['a', 'b', 'c'])
calc_cvscore_on_df(df3[["a","b"]])

Answer 1

To select everything but the first column, you could use df.iloc[:, 1:]:

In [371]: df['Score'] = df.iloc[:, 1:].sum(axis=1)

In [372]: df
Out[372]: 
  AAA  BBB  CCC  Score
0   w   10  100    110
1   x   20   50     70
2   y   30  -30      0
3   z   40  -50    -10

To apply an arbitrary function, func, to each row:

df.iloc[:, 1:].apply(func, axis=1)

---

For example,

import numpy as np
import pandas as pd

def cvscore(fclist):
    sd = np.std(fclist)
    mean = np.mean(fclist)
    cv = sd/mean
    return cv

df = pd.DataFrame({'AAA' : ['w','x','y','z'], 'BBB' : [10,20,30,40],
                   'CCC' : [100,50,-30,-50]})

df['Score'] = df.iloc[:, 1:].apply(cvscore, axis=1)
print(df)

yields

  AAA  BBB  CCC     Score
0   w   10  100  1.211386
1   x   20   50  0.868377
2   y   30  -30       NaN
3   z   40  -50 -5.809058