如何在 Pandas 中编写两个变量（列）的条件

Question

我正在尝试计算没有登录但有卡片视图的实例，并创建一个包含计数（或 True）的新列。我使用下面的条件语句并得到一个关键错误。谁能帮我弄清楚这是怎么回事？

import pandas as pd
import numpy as np

sample = pd.DataFrame({ 'Month' : pd.Categorical(["Jan", "Jan", "Feb",  "Feb", "March","Apr", "May"]),
'Name' : pd.Categorical(["Peter", "Meg", "Peter", "Meg", "Meg","Lois", "Lois"]),
'Logins': [1, 1, 1, 1, 1, 1, 0],
'Card': [1, 1, 2, 2, 1, 2, 1]})

sample['LoginNoCard'] = sample['Logins'].where((sample['Logins'] == 0) & (sample['Card'] > 0), sample[1])

我这里的解决方案是创建一个新的数据框。我想使用条件创建一个新列。 If Logins == 0 & Card > 0, then 0. If Logins > 0 and Card == 0, then 1. Else NaN.

Answer 1

你可以考虑使用嵌套的np.where()条件 for if Logins == 0 & Card > 0, then 0, if Logins > 0 and Card == 0, then 1, else NaN.

In [81]: np.where(((sample['Logins']==0) & (sample['Card']>0)), 0,
                    np.where(((sample['Logins']>0) & (sample['Card']==0)), 1,
                    pd.np.nan))
Out[81]: array([ nan,  nan,  nan,  nan,  nan,  nan,   0.])

要将其分配给列，您可以

In [82]: sample['LoginNoCard'] = np.where(((sample['Logins']==0) & (sample['Card']>0)), 0,
                                            np.where(((sample['Logins']>0) & (sample['Card']==0)), 1,
                                            pd.np.nan))
In [83]: sample
Out[83]:
   Card  Logins  Month   Name  LoginNoCard
0     1       1    Jan  Peter          NaN
1     1       1    Jan    Meg          NaN
2     2       1    Feb  Peter          NaN
3     2       1    Feb    Meg          NaN
4     1       1  March    Meg          NaN
5     2       1    Apr   Lois          NaN
6     1       0    May   Lois            0

如何在 Pandas 中编写两个变量（列）的条件

How to write a conditional on two variables (columns) in Pandas

python

conditional

pandas