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我所做的只是将“年”和“年”的位置从第一行切换到第二行，反之亦然。

这是原始列

10+ years    653
< 1 year     249
2 years      243
3 years      235
5 years      202
4 years      191
1 year       177
6 years      163
7 years      127
8 years      108
9 years       72
.              2
Name: Employment.Length, dtype: int64

第一个例子（第一行的“年”，第二行的“年”）

raw_data['Employment.Length'] = raw_data['Employment.Length'].str.replace('years',' ')
raw_data['Employment.Length'] = raw_data['Employment.Length'].str.replace('year',' ')
raw_data['Employment.Length'] = np.where(raw_data['Employment.Length'].str[:2]=='10',10,raw_data['Employment.Length'])
raw_data['Employment.Length'] = np.where(raw_data['Employment.Length'].str[0]=='<',0,raw_data['Employment.Length'])
raw_data['Employment.Length'] = pd.to_numeric(raw_data['Employment.Length'], errors = 'coerce')

输出

10.0    653
0.0     249
2.0     243
3.0     235
5.0     202
4.0     191
1.0     177
6.0     163
7.0     127
8.0     108
9.0      72
Name: Employment.Length, dtype: int64

第二个例子（第一行的'year'，第二行的'years'）

raw_data_copy['Employment.Length'] = raw_data_copy['Employment.Length'].str.replace('year',' ')
raw_data_copy['Employment.Length'] = raw_data_copy['Employment.Length'].str.replace('years',' ')
raw_data_copy['Employment.Length'] = np.where(raw_data_copy['Employment.Length'].str[:2]=='10',10, raw_data_copy['Employment.Length'])
raw_data_copy['Employment.Length'] = np.where(raw_data_copy['Employment.Length'].str[0]=='<',0,raw_data_copy['Employment.Length'])
raw_data_copy['Employment.Length'] = pd.to_numeric(raw_data_copy['Employment.Length'], errors = 'coerce')

输出

10.0    653
0.0     249
1.0     177
Name: Employment.Length, dtype: int64

还有一件事是，当我用'year'注释掉我的第二行时，它给我的输出与第一个示例相同。当我用'years'注释掉我的第二行时，它给我的输出与第二个示例相同。

第三个例子

 raw_data_copy['Employment.Length'] = raw_data_copy['Employment.Length'].str.replace('years',' ')
    #raw_data_copy['Employment.Length'] = raw_data_copy['Employment.Length'].str.replace('years',' ')
    raw_data_copy['Employment.Length'] = np.where(raw_data_copy['Employment.Length'].str[:2]=='10',10, raw_data_copy['Employment.Length'])
    raw_data_copy['Employment.Length'] = np.where(raw_data_copy['Employment.Length'].str[0]=='<',0,raw_data_copy['Employment.Length'])
    raw_data_copy['Employment.Length'] = pd.to_numeric(raw_data_copy['Employment.Length'], errors = 'coerce')

输出

10.0    653
0.0     249
2.0     243
3.0     235
5.0     202
4.0     191
6.0     163
7.0     127
8.0     108
9.0      72
Name: Employment.Length, dtype: int64
4

1 回答 1

1

如果您首先替换'year'为' 'then ，则'years'不再替换为您的后续 .' s''s'str.replace('years', ' ')

而不是多个后续替换使用一个可选的s：'year[s]?'

import pandas as pd
s = pd.Series(['year', 'years', 'foo'])

s.str.replace('year[s]?', ' ')
#0       
#1       
#2    foo
#dtype: object
于 2021-05-26T15:18:06.690 回答