如何在pandas数据帧中的列之间进行条件计算？

李佑根

这是一个简单的数据框

import pandas as pd
import numpy as np
dates = pd. date_range(' 20130101' , periods=14)
data = pd.DataFrame({'a':[1,0,0,1,0,0,0,1,1,0,0,1,0,0],'b':[0,0,1,0,0,1,0,0,0,0,1,0,1,0]},index=dates)

现在我想添加列“c”，同时满足以下条件。

if a = 1, c = 1
if b = 1, c = 0
if a = 0 and b = 0, c = c.shift(1)约束：不存在a = 1和b = 1同时存在的情况。

这是一个简单的问题，但很难解决......

有什么好主意吗？

耶斯列

IIUC你需要：

data['c'] = np.where(data.a == 1, 1,
            np.where(data.b == 1, 0, np.nan))
print (data)
            a  b    c
2013-01-01  1  0  1.0
2013-01-02  0  0  NaN
2013-01-03  0  1  0.0
2013-01-04  1  0  1.0
2013-01-05  0  0  NaN
2013-01-06  0  1  0.0
2013-01-07  0  0  NaN
2013-01-08  1  0  1.0
2013-01-09  1  0  1.0
2013-01-10  0  0  NaN
2013-01-11  0  1  0.0
2013-01-12  1  0  1.0
2013-01-13  0  1  0.0
2013-01-14  0  0  NaN

然后我不确定是否需要bfill或ffill：

data['c'] = data['c'].bfill()
print (data)
            a  b    c
2013-01-01  1  0  1.0
2013-01-02  0  0  0.0
2013-01-03  0  1  0.0
2013-01-04  1  0  1.0
2013-01-05  0  0  0.0
2013-01-06  0  1  0.0
2013-01-07  0  0  1.0
2013-01-08  1  0  1.0
2013-01-09  1  0  1.0
2013-01-10  0  0  0.0
2013-01-11  0  1  0.0
2013-01-12  1  0  1.0
2013-01-13  0  1  0.0
2013-01-14  0  0  NaN

data['c'] = data['c'].ffill()
print (data)
            a  b    c
2013-01-01  1  0  1.0
2013-01-02  0  0  1.0
2013-01-03  0  1  0.0
2013-01-04  1  0  1.0
2013-01-05  0  0  1.0
2013-01-06  0  1  0.0
2013-01-07  0  0  0.0
2013-01-08  1  0  1.0
2013-01-09  1  0  1.0
2013-01-10  0  0  1.0
2013-01-11  0  1  0.0
2013-01-12  1  0  1.0
2013-01-13  0  1  0.0
2013-01-14  0  0  0.0

本文收集自互联网，转载请注明来源。

如有侵权，请联系 [email protected] 删除。