Question

我有一个Python数据框，其中包含一个名为＆＃34; SEGMENT＆＃34;的列。我想把这个专栏分成三列。请查看以黄色突出显示的所需输出。

以下是我尝试过的代码。不幸的是，我甚至无法获得第一个替换语句。：不会被 - 取代 - 。任何帮助是极大的赞赏！

df_stack_ranking['CURRENT_AUM_SEGMENT'] = df_stack_ranking['CURRENT_AUM_SEGMENT'].replace(':', '-')

s = df_stack_ranking['CURRENT_AUM_SEGMENT'].str.split(' ').apply(Series, 1).stack()

s.index = s.index.droplevel(-1)

s.name = 'SEGMENT'

df_stack_ranking.join(s.apply(lambda x: Series(x.split(':'))))

Answer 1

<强>设置

df = pd.DataFrame({'SEGMENT': {0: 'Hight:33-48', 1: 'Hight:33-48', 2: 'Very Hight:80-88'}})

df
Out[17]: 
            SEGMENT
0       Hight:33-48
1       Hight:33-48
2  Very Hight:80-88

<强>解决方案

使用split将列拆分为3个部分，然后展开以创建新的DF。

df.SEGMENT.str.split(':|-',expand=True)\
  .rename(columns=dict(zip(range(3),\
  ['SEGMENT','SEGMENT RANGE LOW','SEGMENT RANGE HIGH'])))
Out[13]: 
      SEGMENT SEGMENT RANGE LOW SEGMENT RANGE HIGH
0       Hight                33                 48
1       Hight                33                 48
2  Very Hight                80                 88

Answer 2

:或(|) \s*-\s*使用str.split（\s*表示零个或多个空格）：

df = pd.DataFrame({'SEGMENT': ['Hight: 33 - 48', 'Hight: 33 - 48', 'Very Hight: 80 - 88']})

cols = ['SEGMENT','SEGMENT RANGE LOW','SEGMENT RANGE HIGH']
df[cols] = df['SEGMENT'].str.split(':\s*|\s*-\s*',expand=True)
print (df)
      SEGMENT SEGMENT RANGE LOW SEGMENT RANGE HIGH
0       Hight                33                 48
1       Hight                33                 48
2  Very Hight                80                 88

str.extract的解决方案：

cols = ['SEGMENT','SEGMENT RANGE LOW','SEGMENT RANGE HIGH']
df[cols] = df['SEGMENT'].str.extract('([A-Za-z\s*]+):\s*(\d+)\s*-\s*(\d+)', expand = True)
print (df)
      SEGMENT SEGMENT RANGE LOW SEGMENT RANGE HIGH
0       Hight                33                 48
1       Hight                33                 48
2  Very Hight                80                 88

Answer 3

因为我喜欢命名str.extract正则表达式

中的列

regex = '\s*(?P<SEGMENT>\S+)\s*:\s*(?P<SEGMENT_RANGE_LOW>\S+)\s*-\s*(?P<SEGMENT_RANGE_HIGH>\S+)\s*'
df.SEGMENT.str.extract(regex, expand=True)

  SEGMENT SEGMENT_RANGE_LOW SEGMENT_RANGE_HIGH
0    High                33                 48
1    High                33                 48
2    High                80                 88

设置

df = pd.DataFrame({'SEGMENT': ['High: 33 - 48', 'High: 33 - 48', 'Very High: 80 - 88']})

Answer 4

columns = ['SEGMENT', 'SEGMENT RANGE LOW', 'SEGMENT RANGE HIGH']
df['temp'] = df['SEGMENT'].str.replace(': ','-').str.split('-')
for i, c in enumerate(columns):
    df[c] = df['temp'].apply(lambda x: x[i])
del df['temp']

用连字符替换冒号，然后在连字符上拆分以获取3列的值列表。然后为3列中的每列分配值并删除临时列。

Answer 5

我会使用正则表达式使用正则表达式

执行此操作

df.SEGMENT.str.extract('([A-Za-z ]+):(\d+)-(\d+)', expand = True).rename(columns = {0: 'SEGMENT', 1: 'SEGMENT RANGE LOW', 2: 'SEGMENT RANGE HIGH'})

    SEGMENT     SEGMENT RANGE LOW   SEGMENT RANGE HIGH
0   High        33                  48
1   High        33                  48
2   Very High   80                  88

Python：使用Lambda将字符串字段拆分为3个单独的字段

5 个答案: