如果其他条件在多个列上，则为 pandas [英] pandas if else conditions on multiple columns

问题描述

假设我的df以下:

import pandas as pd

data_dic = {
    "a": [0,0,1,2],
    "b": [0,3,4,5],
    "c": [6,7,8,9]
}
df = pd.DataFrame(data_dic)

结果:

   a  b  c
0  0  0  6
1  0  3  7
2  1  4  8
3  2  5  9

我需要根据条件将值从上述各列粘贴到新列中:

I need to past value to new column from above columns based on conditions:

if df.a > 0 then value df.a
else if df.b > 0 then value df.b 
else value df.c

我现在尝试:

df['value'] = [x if x > 0 else 'ww' for x in df['a']]

但是不知道如何在其中输入更多条件.

but don't know how to input more conditions in this.

预期结果:

   a  b  c value
0  0  0  6  6
1  0  3  7  3
2  1  4  8  1
3  2  5  9  2

感谢您的辛勤工作.

推荐答案

使用在40万行中向量化和循环解之间的区别:

Difference between vectorized and loop solutions in 400k rows:

df = pd.concat([df] * 100000, ignore_index=True)

In [158]: %timeit df['value2'] = np.select([df.a > 0 , df.b > 0], [df.a, df.b], default=df.c)
9.86 ms ± 611 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)

In [159]: %timeit df['value1'] = [x if x > 0 else y if y>0 else z for x,y,z in zip(df['a'],df['b'],df['c'])]
399 ms ± 52.3 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)

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