在具有数值的列上的pandas数据框上逐行应用函数

Question

我有以下数据框:

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

看起来像这样:

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

我想要做的是对除了具有非数值的那些列(在这种情况下AAA)之外的每一列执行函数操作.在实际情况下,非数字情况总是在第一列,其余(可能大于2列)总是数字.

最终的期望输出是:

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

我尝试过但失败了:

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

什么是正确的方法呢？

UPDATE2:

这是给出的代码SettingWithCopyWarning.请重新开始ipython测试.

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

要选择除第一列之外的所有内容,您可以使用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

要func对每行应用任意函数:

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

例如,

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)

产量

  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