Pandas dataframe：删除名称中包含特定字符串的列

4 回答

• 68

  import pandas as pd
  
  import numpy as np
  
  array=np.random.random((2,4))
  
  df=pd.DataFrame(array, columns=('Test1', 'toto', 'test2', 'riri'))
  
  print df
  
        Test1      toto     test2      riri
  0  0.923249  0.572528  0.845464  0.144891
  1  0.020438  0.332540  0.144455  0.741412
  
  cols = [c for c in df.columns if c.lower()[:4] != 'test']
  
  df=df[cols]
  
  print df
         toto      riri
  0  0.572528  0.144891
  1  0.332540  0.741412
  

  回复于 2024-05-03T00:38:37+08:00
• 29

  这是一个很好的方法：

  df = df[df.columns.drop(list(df.filter(regex='Test')))]
  

  回复于 2024-05-03T00:38:37+08:00
• 6

  使用 DataFrame.select 方法：

  In [38]: df = DataFrame({'Test1': randn(10), 'Test2': randn(10), 'awesome': randn(10)})
  
  In [39]: df.select(lambda x: not re.search('Test\d+', x), axis=1)
  Out[39]:
     awesome
  0    1.215
  1    1.247
  2    0.142
  3    0.169
  4    0.137
  5   -0.971
  6    0.736
  7    0.214
  8    0.111
  9   -0.214
  

  回复于 2024-05-03T00:38:37+08:00
• 7

  您可以使用“过滤器”过滤掉您想要的列

  import pandas as pd
  import numpy as np
  
  data2 = [{'test2': 1, 'result1': 2}, {'test': 5, 'result34': 10, 'c': 20}]
  
  df = pd.DataFrame(data2)
  
  df
  
      c   result1     result34    test    test2
  0   NaN     2.0     NaN     NaN     1.0
  1   20.0    NaN     10.0    5.0     NaN
  

  现在过滤

  df.filter(like='result',axis=1)
  

  得到..

  result1  result34
  0   2.0     NaN
  1   NaN     10.0
  

  回复于 2024-05-03T00:38:37+08:00