如何在Python Pandas中选择两个值之间的DataFrame中的行？

5 回答

• 56

  您应该使用 () 对布尔向量进行分组以消除歧义 .

  df = df[(df['closing_price'] >= 99) & (df['closing_price'] <= 101)]
  

  回复于 2024-05-02T11:34:54+08:00
• 44

  还要考虑series between：

  df = df[df['closing_price'].between(99, 101, inclusive=True)]
  

  回复于 2024-05-02T11:34:54+08:00
• 3

  有一个更好的选择 - 使用query()方法：

  In [58]: df = pd.DataFrame({'closing_price': np.random.randint(95, 105, 10)})
  
  In [59]: df
  Out[59]:
     closing_price
  0            104
  1             99
  2             98
  3             95
  4            103
  5            101
  6            101
  7             99
  8             95
  9             96
  
  In [60]: df.query('99 <= closing_price <= 101')
  Out[60]:
     closing_price
  1             99
  5            101
  6            101
  7             99
  

  UPDATE: 回答评论：

  我喜欢这里的语法，但在尝试与expresison结合时倒下了; df.query（'（mean 2 * sd）<= closing_price <=（mean 2 * sd）'）

  In [161]: qry = "(closing_price.mean() - 2*closing_price.std())" +\
       ...:       " <= closing_price <= " + \
       ...:       "(closing_price.mean() + 2*closing_price.std())"
       ...:
  
  In [162]: df.query(qry)
  Out[162]:
     closing_price
  0             97
  1            101
  2             97
  3             95
  4            100
  5             99
  6            100
  7            101
  8             99
  9             95
  

  回复于 2024-05-02T11:34:54+08:00
• 15

  newdf = df.query('closing_price.mean() <= closing_price <= closing_price.std()')
  

  要么

  mean = closing_price.mean()
  std = closing_price.std()
  
  newdf = df.query('@mean <= closing_price <= @std')
  

  回复于 2024-05-02T11:34:54+08:00
• 0

  而不是这个

  df = df[(99 <= df['closing_price'] <= 101)]
  

  你应该用它

  df = df[(df['closing_price']>=99 ) & (df['closing_price']<=101)]
  

  我们必须使用NumPy的按位逻辑运算符|，＆，〜，^来进行复合查询 . 此外，括号对于运算符优先级很重要 .

  欲了解更多信息，请访问以下链接：Comparisons, Masks, and Boolean Logic

  回复于 2024-05-02T11:34:54+08:00