Question

我在名为test.csv的文件中有以下数据集：

ID,ENROLLMENT_DATE,TRAINER_MANAGING,TRAINER_OPERATOR,FIRST_VISIT_DATE
1536D,12-Feb-12,"06DA1B3-Lebanon NH",,15-Feb-12
F15D,18-May-12,"06405B2-Lebanon NH",,25-Jul-12
8096,8-Aug-12,"0643D38-Hanover NH","0643D38-Hanover NH",25-Jun-12
A036,1-Apr-12,"06CB8CF-Hanover NH","06CB8CF-Hanover NH",9-Aug-12
8944,19-Feb-12,"06D26AD-Hanover NH",,4-Feb-12
1004E,8-Jun-12,"06388B2-Lebanon NH",,24-Dec-11
16D87,3-Jul-12,"0649597-White River VT","0649597-White River VT",30-Mar-12
30D7,11-Nov-12,"06D95A3-Hanover NH","06D95A3-Hanover NH",30-Nov-11
3AE2,21-Feb-12,"06405B2-Lebanon NH",,26-Oct-12
B0FE,17-Feb-12,"06D1B9D-Hartland VT",,16-Feb-12
127A1,11-Dec-11,"064456E-Hanover NH","064456E-Hanover NH",11-Nov-12
161FF,20-Feb-12,"0643D38-Hanover NH","0643D38-Hanover NH",3-Jul-12
F4F9,30-Nov-11,"063B208-Randolph VT","063B208-Randolph VT",
475B,25-Sep-12,"06D26AD-Hanover NH",,5-Nov-12
151A3,7-Mar-12,"06388B2-Lebanon NH",,16-Nov-12
CA62,3-Jan-12,,,
D31B,18-Dec-11,"06405B2-Lebanon NH",,9-Jan-12
20F5,8-Jul-12,"0669C50-Randolph VT",,3-Feb-12
C6DC,19-Dec-11,"0649597-White River VT","0649597-White River VT",9-Apr-12
14E48,1-Aug-12,"06D3206-Hanover NH",,
177F8,20-Aug-12,"063B208-Randolph VT","063B208-Randolph VT",5-May-12
553E,11-Oct-12,"06D95A3-Hanover NH","06D95A3-Hanover NH",8-Mar-12
12D5F,18-Jul-12,"0649597-White River VT","0649597-White River VT",2-Nov-12
C6DC,13-Apr-12,"06388B2-Lebanon NH",,
11795,27-Feb-12,"0643D38-Hanover NH","0643D38-Hanover NH",19-Jun-12
17B43,11-Aug-12,,,22-Oct-12
16C99,11-Aug-12,"06D3206-Hanover NH",,19-Jun-12

我可以使用以下代码获取访问过综合体的人员列表：

import numpy as np
a = np.recfromcsv('test.csv')
print a[a['first_visit_date'] != '']

这是我遇到的问题。我似乎找不到打印名为trainer的条件列的方法。我想弄清楚如果它不为空，如何输出'trainer_operator'，否则我想输出'trainer_managing'。我想我需要使用numpy.lib.recfunctions.rec_append_fields来创建列。我只是不确定如何填充它。

我还应该说我刚刚开始发现numpy的力量，所以我试图将它用于很多事情。这可能不是使用它的正确情况。如果有更好的方法来操纵数据，请告诉我。

提前致谢！

Answer 1

一种直截了当的方法是使用numpy.where：

>>> fvd_exists = a['first_visit_date'] != ''
>>> np.where(fvd_exists, a['trainer_managing'], a['trainer_operator'])
array(['"06DA1B3-Lebanon NH"', '"06405B2-Lebanon NH"',
       '"0643D38-Hanover NH"', '"06CB8CF-Hanover NH"',
       '"06D26AD-Hanover NH"', '"06388B2-Lebanon NH"',
       ...

如果您有一组更复杂的需求，只需在a上使用布尔运算表达它们，并将结果传递给fvd_exists。

然后，您可以使用fromarrays创建新的记录数组。这是一个完整的例子：

>>> a = np.recfromcsv('test.csv')
>>> b = a[a['first_visit_date'] != '']
>>> has_op = b['trainer_operator'] != ''
>>> trainer_col = np.where(name, b.trainer_operator, b.trainer_managing)
>>> np.rec.fromarrays([b.id, b.enrollment_date, trainer_col],
...                   names=['id', 'enrollment_date', 'trainer'])
rec.array([('1536D', '12-Feb-12', '"06DA1B3-Lebanon NH"'),
       ('F15D', '18-May-12', '"06405B2-Lebanon NH"'),
       ('8096', '8-Aug-12', '"0643D38-Hanover NH"'),
       ('A036', '1-Apr-12', '"06CB8CF-Hanover NH"'),
       ('8944', '19-Feb-12', '"06D26AD-Hanover NH"'),
       ('1004E', '8-Jun-12', '"06388B2-Lebanon NH"'),
       ('16D87', '3-Jul-12', '"0649597-White River VT"'),
       ('30D7', '11-Nov-12', '"06D95A3-Hanover NH"'),
       ('3AE2', '21-Feb-12', '"06405B2-Lebanon NH"'),
       ('B0FE', '17-Feb-12', '"06D1B9D-Hartland VT"'),
       ('127A1', '11-Dec-11', '"064456E-Hanover NH"'),
       ('161FF', '20-Feb-12', '"0643D38-Hanover NH"'),
       ('475B', '25-Sep-12', '"06D26AD-Hanover NH"'),
       ('151A3', '7-Mar-12', '"06388B2-Lebanon NH"'),
       ('D31B', '18-Dec-11', '"06405B2-Lebanon NH"'),
       ('20F5', '8-Jul-12', '"0669C50-Randolph VT"'),
       ('C6DC', '19-Dec-11', '"0649597-White River VT"'),
       ('177F8', '20-Aug-12', '"063B208-Randolph VT"'),
       ('553E', '11-Oct-12', '"06D95A3-Hanover NH"'),
       ('12D5F', '18-Jul-12', '"0649597-White River VT"'),
       ('11795', '27-Feb-12', '"0643D38-Hanover NH"'),
       ('17B43', '11-Aug-12', ''),
       ('16C99', '11-Aug-12', '"06D3206-Hanover NH"')], 
      dtype=[('id', '|S5'), ('enrollment_date', '|S9'), ('trainer', '|S24')])

使用numpy在python中有条件地返回列

1 个答案: