Python程序用True和False替换'qualify'列值'yes'和'no'

Posted 2021-05-05

import numpy as np
import pandas as pd

exam_data =pd.DataFrame( {'name': ['Anastasia', 'Dima', 'Katherine', 
'James', 'Emily', 'Michael', 'Matthew', 'Laura', 'Kevin', 'Jonas'],
'score': [12.5, 9, 16.5, np.nan, 9, 20, 14.5, np.nan, 8, 19],
'attempts': [1, 3, 2, 3, 2, 3, 1, 1, 2, 1],
'qualify': ['yes', 'no', 'yes', 'no', 'no', 'yes', 'yes', 'no', 'no', 
'yes']})

 exam_data.set_index([['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j'], 
 'name'])



 r1 = exam_data.replace('yes', 'true')
 r2 = exam_data.replace('no', 'false')
 r1

我希望结果如此

attempts    name        qualify score
       a    1           Anastasia   true    12.5
       b    3           Dima        false   9.0
       c    2           Katherine   true    16.5
       d    3           James       false   NaN
       e    2           Emily       false   9.0
       f    3           Michael     true    20.0
       g    1           Matthew     true    14.5
       h    1           Laura       false   NaN
       i    2           Kevin       false   8.0
       j    1           Jonas       true    19.0

答案

最简单的是通过qazxsw poi比较值：

yes

如果想使用exam_data['qualify'] = exam_data['qualify'] == 'yes' print (exam_data) attempts name qualify score 0 1 Anastasia True 12.5 1 3 Dima False 9.0 2 2 Katherine True 16.5 3 3 James False NaN 4 2 Emily False 9.0 5 3 Michael True 20.0 6 1 Matthew True 14.5 7 1 Laura False NaN 8 2 Kevin False 8.0 9 1 Jonas True 19.0 - 如果dict中定义的另一个值没有改变：

replace

或者exam_data['qualify'] = exam_data['qualify'].replace({'yes':True, 'no':False}) - 如果在dict中定义的另一个值然后替换为maps：

NaN