Python 基于多个列值创建列_Python_Python 3.x_Pandas_Data Science

Python 基于多个列值创建列

python python-3.x pandas

Python 基于多个列值创建列,python,python-3.x,pandas,data-science,Python,Python 3.x,Pandas,Data Science,如果我的df如下所示： ID | Car | Plane | Tank | Scooter | Misc | Day 4 Yes No Yes No 32 Mon 2 No No No No 22 Tues 1 Yes No No No 11 Wed 如果在汽车、飞机、坦克或滑板车的任何列中有值为是或否，我如何创建一个表示真或假的新列？谢

如果我的df如下所示：

ID | Car | Plane | Tank | Scooter | Misc  | Day
4    Yes    No      Yes    No        32     Mon
2    No     No      No     No        22     Tues
1    Yes    No      No     No        11     Wed

如果在汽车、飞机、坦克或滑板车的任何列中有值为是或否，我如何创建一个表示真或假的新列？谢谢

您可以使用

.iloc

确定要用于检查的列。你可以。使用

.any（1）

查看是否有任何值是

'Yes'

或

'No'

代码如下。我添加了第4行，其中的值为'Maybe'，以显示记录不符合'Yes'，'No'条件

#created the DataFrame with a few sample values
import pandas as pd
df = pd.DataFrame({'ID':[4,2,1,3],
                   'Car':['Yes','No','Yes','Maybe'],
                   'Plane':['No','No','No','Maybe'],
                   'Tank':['Yes','No','No','Maybe'],
                   'Scooter':['No','No','No','Maybe'],
                   'Misc':[32,22,11,44],
                   'Day':['Mon','Tues','Wed','Thu']})

#printing the full DataFrame to make sure the values are as expected
print(df)

#the iloc option can be used to filter the columns you want to checked
#printing it out for you to see which ones are being used for selection 
print(df.iloc[:,1:-2])

#if you want to check for 'Yes' or 'No', then use |. If either then it will set to 'True'
#if you want to check for only for 'Yes', then you dont need the second part
df['Check'] = ((df.iloc[:,1:-2] == 'Yes') | (df.iloc[:,1:-2] == 'No')).any(1)

#the DataFrame will have the new column with True or False
print (df)

结果如下：

df['Check'] = (df.iloc[:,1:-2] == 'Yes').any(1)

初始数据帧：

   ID    Car  Plane   Tank Scooter  Misc   Day
0   4    Yes     No    Yes      No    32   Mon
1   2     No     No     No      No    22  Tues
2   1    Yes     No     No      No    11   Wed
3   3  Maybe  Maybe  Maybe   Maybe    44   Thu

     Car  Plane   Tank Scooter
0    Yes     No    Yes      No
1     No     No     No      No
2    Yes     No     No      No
3  Maybe  Maybe  Maybe   Maybe

   ID    Car  Plane   Tank Scooter  Misc   Day  Check
0   4    Yes     No    Yes      No    32   Mon   True
1   2     No     No     No      No    22  Tues   True
2   1    Yes     No     No      No    11   Wed   True
3   3  Maybe  Maybe  Maybe   Maybe    44   Thu  False

   ID    Car  Plane   Tank Scooter  Misc   Day  Check
0   4    Yes     No    Yes      No    32   Mon   True
1   2     No     No     No      No    22  Tues  False
2   1    Yes     No     No      No    11   Wed   True
3   3  Maybe  Maybe  Maybe   Maybe    44   Thu  False

   ID    Car  Plane  Misc   Tank   Day Scooter  Check
0   4    Yes     No    32    Yes   Mon      No   True
1   2     No     No    22     No  Tues      No  False
2   1    Yes     No    11     No   Wed      No   True
3   3  Maybe  Maybe    44  Maybe   Thu   Maybe  False

从数据帧筛选的列为：

   ID    Car  Plane   Tank Scooter  Misc   Day
0   4    Yes     No    Yes      No    32   Mon
1   2     No     No     No      No    22  Tues
2   1    Yes     No     No      No    11   Wed
3   3  Maybe  Maybe  Maybe   Maybe    44   Thu

     Car  Plane   Tank Scooter
0    Yes     No    Yes      No
1     No     No     No      No
2    Yes     No     No      No
3  Maybe  Maybe  Maybe   Maybe

   ID    Car  Plane   Tank Scooter  Misc   Day  Check
0   4    Yes     No    Yes      No    32   Mon   True
1   2     No     No     No      No    22  Tues   True
2   1    Yes     No     No      No    11   Wed   True
3   3  Maybe  Maybe  Maybe   Maybe    44   Thu  False

   ID    Car  Plane   Tank Scooter  Misc   Day  Check
0   4    Yes     No    Yes      No    32   Mon   True
1   2     No     No     No      No    22  Tues  False
2   1    Yes     No     No      No    11   Wed   True
3   3  Maybe  Maybe  Maybe   Maybe    44   Thu  False

   ID    Car  Plane  Misc   Tank   Day Scooter  Check
0   4    Yes     No    32    Yes   Mon      No   True
1   2     No     No    22     No  Tues      No  False
2   1    Yes     No    11     No   Wed      No   True
3   3  Maybe  Maybe    44  Maybe   Thu   Maybe  False

供您使用的最终结果：

   ID    Car  Plane   Tank Scooter  Misc   Day
0   4    Yes     No    Yes      No    32   Mon
1   2     No     No     No      No    22  Tues
2   1    Yes     No     No      No    11   Wed
3   3  Maybe  Maybe  Maybe   Maybe    44   Thu

     Car  Plane   Tank Scooter
0    Yes     No    Yes      No
1     No     No     No      No
2    Yes     No     No      No
3  Maybe  Maybe  Maybe   Maybe

   ID    Car  Plane   Tank Scooter  Misc   Day  Check
0   4    Yes     No    Yes      No    32   Mon   True
1   2     No     No     No      No    22  Tues   True
2   1    Yes     No     No      No    11   Wed   True
3   3  Maybe  Maybe  Maybe   Maybe    44   Thu  False

   ID    Car  Plane   Tank Scooter  Misc   Day  Check
0   4    Yes     No    Yes      No    32   Mon   True
1   2     No     No     No      No    22  Tues  False
2   1    Yes     No     No      No    11   Wed   True
3   3  Maybe  Maybe  Maybe   Maybe    44   Thu  False

   ID    Car  Plane  Misc   Tank   Day Scooter  Check
0   4    Yes     No    32    Yes   Mon      No   True
1   2     No     No    22     No  Tues      No  False
2   1    Yes     No    11     No   Wed      No   True
3   3  Maybe  Maybe    44  Maybe   Thu   Maybe  False

如果您的状况发生以下变化：

如果'Car'、'Plane'、'Tank'、'Scooter'中的任何值='Yes'，则将'Check'设置为True。对于所有其他情况，请将“检查”设置为False

然后，前面的代码可以简化如下：

df['Check'] = (df.iloc[:,1:-2] == 'Yes').any(1)

此操作的输出如下：

   ID    Car  Plane   Tank Scooter  Misc   Day
0   4    Yes     No    Yes      No    32   Mon
1   2     No     No     No      No    22  Tues
2   1    Yes     No     No      No    11   Wed
3   3  Maybe  Maybe  Maybe   Maybe    44   Thu

     Car  Plane   Tank Scooter
0    Yes     No    Yes      No
1     No     No     No      No
2    Yes     No     No      No
3  Maybe  Maybe  Maybe   Maybe

   ID    Car  Plane   Tank Scooter  Misc   Day  Check
0   4    Yes     No    Yes      No    32   Mon   True
1   2     No     No     No      No    22  Tues   True
2   1    Yes     No     No      No    11   Wed   True
3   3  Maybe  Maybe  Maybe   Maybe    44   Thu  False

   ID    Car  Plane   Tank Scooter  Misc   Day  Check
0   4    Yes     No    Yes      No    32   Mon   True
1   2     No     No     No      No    22  Tues  False
2   1    Yes     No     No      No    11   Wed   True
3   3  Maybe  Maybe  Maybe   Maybe    44   Thu  False

   ID    Car  Plane  Misc   Tank   Day Scooter  Check
0   4    Yes     No    32    Yes   Mon      No   True
1   2     No     No    22     No  Tues      No  False
2   1    Yes     No    11     No   Wed      No   True
3   3  Maybe  Maybe    44  Maybe   Thu   Maybe  False

如果您的数据帧不是由汽车、飞机、坦克和滑板车相邻构成的，您可以将它们放入一个列表中，并使用该列表进行过滤和检查

例如，如果您的数据帧如下所示：

df = pd.DataFrame({'ID':[4,2,1,3],
                   'Car':['Yes','No','Yes','Maybe'],
                   'Plane':['No','No','No','Maybe'],
                   'Misc':[32,22,11,44],
                   'Tank':['Yes','No','No','Maybe'],
                   'Day':['Mon','Tues','Wed','Thu'],
                   'Scooter':['No','No','No','Maybe']})

然后它会像这样

   ID    Car  Plane  Misc   Tank   Day Scooter
0   4    Yes     No    32    Yes   Mon      No
1   2     No     No    22     No  Tues      No
2   1    Yes     No    11     No   Wed      No
3   3  Maybe  Maybe    44  Maybe   Thu   Maybe

您将无法使用

.iloc[：，1:-2]

。相反，您可以将所有列放入一个列表中，并按如下方式使用该列表

cols = ['Car','Plane','Tank','Scooter']

print(df[cols])

df['Check'] = (df[cols] == 'Yes').any(1)

这将为您提供与我们前面讨论的iloc选项相同的结果

输出将为：

   ID    Car  Plane   Tank Scooter  Misc   Day
0   4    Yes     No    Yes      No    32   Mon
1   2     No     No     No      No    22  Tues
2   1    Yes     No     No      No    11   Wed
3   3  Maybe  Maybe  Maybe   Maybe    44   Thu

     Car  Plane   Tank Scooter
0    Yes     No    Yes      No
1     No     No     No      No
2    Yes     No     No      No
3  Maybe  Maybe  Maybe   Maybe

   ID    Car  Plane   Tank Scooter  Misc   Day  Check
0   4    Yes     No    Yes      No    32   Mon   True
1   2     No     No     No      No    22  Tues   True
2   1    Yes     No     No      No    11   Wed   True
3   3  Maybe  Maybe  Maybe   Maybe    44   Thu  False

   ID    Car  Plane   Tank Scooter  Misc   Day  Check
0   4    Yes     No    Yes      No    32   Mon   True
1   2     No     No     No      No    22  Tues  False
2   1    Yes     No     No      No    11   Wed   True
3   3  Maybe  Maybe  Maybe   Maybe    44   Thu  False

   ID    Car  Plane  Misc   Tank   Day Scooter  Check
0   4    Yes     No    32    Yes   Mon      No   True
1   2     No     No    22     No  Tues      No  False
2   1    Yes     No    11     No   Wed      No   True
3   3  Maybe  Maybe    44  Maybe   Thu   Maybe  False