使用 Pandas query() 过滤时间戳列上的数据帧

Posted 2023-02-24

【中文标题】使用 Pandas query() 过滤时间戳列上的数据帧

【英文标题】：Using Pandas query() to filter dataframe on a timestamp column

【发布时间】：2020-06-02 06:12:17

【问题描述】：

我正在尝试在时间戳列上使用字符串和函数 query() 过滤 Pandas 数据框：

df.query('Timestamp < "2020-02-01"')

但是，我收到以下错误：

Traceback (most recent call last):   
File "C:\ENERCON\Python 3.7.2\lib\site-packages\IPython\core\interactiveshell.py", line 3326, in run_code
     exec(code_obj, self.user_global_ns, self.user_ns)   
File "<ipython-input-3-7bb40e9c631a>", line 1, in <module>
     df.query('Timestamp < "2020-02-01"')   
File "C:\ENERCON\Python 3.7.2\lib\site-packages\pandas\core\frame.py", line 3199, in query
     res = self.eval(expr, **kwargs)   
File "C:\ENERCON\Python 3.7.2\lib\site-packages\pandas\core\frame.py", line 3315, in eval
     return _eval(expr, inplace=inplace, **kwargs)   
File "C:\ENERCON\Python 3.7.2\lib\site-packages\pandas\core\computation\eval.py", line 327, in eval
     ret = eng_inst.evaluate()   
File "C:\ENERCON\Python 3.7.2\lib\site-packages\pandas\core\computation\engines.py", line 142, in evaluate
     return self.expr()   
File "C:\ENERCON\Python 3.7.2\lib\site-packages\pandas\core\computation\expr.py", line 837, in __call__
     return self.terms(self.env)   
File "C:\ENERCON\Python 3.7.2\lib\site-packages\pandas\core\computation\ops.py", line 380, in __call__
     return self.func(left, right) 
TypeError: '<' not supported between instances of 'type' and 'str'

也尝试将字符串转换为日期时间，但错误类似。

df.query('Timestamp < @pd.to_datetime("2020-02-01")')
Traceback (most recent call last):
  File "C:\ENERCON\Python 3.7.2\lib\site-packages\IPython\core\interactiveshell.py", line 3326, in run_code
    exec(code_obj, self.user_global_ns, self.user_ns)
  File "<ipython-input-5-23540526aad9>", line 1, in <module>
    df.query('Timestamp < @pd.to_datetime("2020-02-01")')
  File "C:\ENERCON\Python 3.7.2\lib\site-packages\pandas\core\frame.py", line 3199, in query
    res = self.eval(expr, **kwargs)
  File "C:\ENERCON\Python 3.7.2\lib\site-packages\pandas\core\frame.py", line 3315, in eval
    return _eval(expr, inplace=inplace, **kwargs)
  File "C:\ENERCON\Python 3.7.2\lib\site-packages\pandas\core\computation\eval.py", line 322, in eval
    parsed_expr = Expr(expr, engine=engine, parser=parser, env=env, truediv=truediv)
  File "C:\ENERCON\Python 3.7.2\lib\site-packages\pandas\core\computation\expr.py", line 830, in __init__
    self.terms = self.parse()
  File "C:\ENERCON\Python 3.7.2\lib\site-packages\pandas\core\computation\expr.py", line 847, in parse
    return self._visitor.visit(self.expr)
  File "C:\ENERCON\Python 3.7.2\lib\site-packages\pandas\core\computation\expr.py", line 441, in visit
    return visitor(node, **kwargs)
  File "C:\ENERCON\Python 3.7.2\lib\site-packages\pandas\core\computation\expr.py", line 447, in visit_Module
    return self.visit(expr, **kwargs)
  File "C:\ENERCON\Python 3.7.2\lib\site-packages\pandas\core\computation\expr.py", line 441, in visit
    return visitor(node, **kwargs)
  File "C:\ENERCON\Python 3.7.2\lib\site-packages\pandas\core\computation\expr.py", line 450, in visit_Expr
    return self.visit(node.value, **kwargs)
  File "C:\ENERCON\Python 3.7.2\lib\site-packages\pandas\core\computation\expr.py", line 441, in visit
    return visitor(node, **kwargs)
  File "C:\ENERCON\Python 3.7.2\lib\site-packages\pandas\core\computation\expr.py", line 747, in visit_Compare
    return self.visit(binop)
  File "C:\ENERCON\Python 3.7.2\lib\site-packages\pandas\core\computation\expr.py", line 441, in visit
    return visitor(node, **kwargs)
  File "C:\ENERCON\Python 3.7.2\lib\site-packages\pandas\core\computation\expr.py", line 565, in visit_BinOp
    return self._maybe_evaluate_binop(op, op_class, left, right)
  File "C:\ENERCON\Python 3.7.2\lib\site-packages\pandas\core\computation\expr.py", line 547, in _maybe_evaluate_binop
    return self._maybe_eval(res, self.binary_ops)
  File "C:\ENERCON\Python 3.7.2\lib\site-packages\pandas\core\computation\expr.py", line 519, in _maybe_eval
    self.env, self.engine, self.parser, self.term_type, eval_in_python
  File "C:\ENERCON\Python 3.7.2\lib\site-packages\pandas\core\computation\ops.py", line 399, in evaluate
    res = self(env)
  File "C:\ENERCON\Python 3.7.2\lib\site-packages\pandas\core\computation\ops.py", line 380, in __call__
    return self.func(left, right)
TypeError: '<' not supported between instances of 'type' and 'Timestamp'

如果我使用 .loc 运行等效函数，我会得到想要的结果（但我不能使用用户输入字符串）。

df.loc[df['Timestamp'] < "2020-02-01"]
Out[4]:                 
     Timestamp  Error  ...  ToD  Day_Night
0    2020-01-17 00:00:00      0  ...    0      Night  
1    2020-01-17 00:10:00      0  ...    0      Night
2    2020-01-17 00:20:00      0  ...    0      Night
3    2020-01-17 00:30:00      0  ...    0      Night 
4    2020-01-17 00:40:00      0  ...    0      Night 
2154 2020-01-31 23:10:00      0  ...   23      Night  
2155 2020-01-31 23:20:00      0  ...   23      Night 
2156 2020-01-31 23:30:00      0  ...   23      Night
2157 2020-01-31 23:40:00      0  ...   23      Night 
2158 2020-01-31 23:50:00      0  ...   23      Night
[2159 rows x 37 columns]

有人知道如何将query() 与日期时间列一起使用吗？

【问题讨论】：

我认为错误消息提供了一个线索 - 时间戳是一种类型，不能与 str 或 datetime 进行比较。运行测试并将时间戳名称更改为其他名称，然后查看代码是否有效。 df['Timestamp'] 是熊猫允许的，这就是它起作用的原因，因为它不是一种类型，而是一种列。阅读警告框了解更多信息：pandas.pydata.org/pandas-docs/stable/user_guide/…

谢谢，这就是问题所在。重命名该列后，它可以工作。

【参考方案1】：

Timestamp 列名隐藏了内置类型 timestamp。作为第一步，您可以使用 rename() 将列重命名为其他名称：

df.rename(columns="Timestamp": "MyTimestamp")

那么以下应该可以解决日期时间的问题：

df.query('MyTimestamp < 20200201')

---

或者，如果您想使用时间戳查询数据帧：

df.query('MyTimestamp < @ts("20200201T071320")'