gpt4 book ai didi

python - 使用 Pandas query() 过滤时间戳列上的数据帧

转载 作者:行者123 更新时间:2023-12-02 09:08:32 25 4
gpt4 key购买 nike

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

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,我会得到所需的结果(但我无法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?

最佳答案

Timestamp 列名称隐藏了内置类型 timestamp。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问题:

df.query('MyTimestamp < 20200201')
<小时/>

或者,如果您想使用时间戳查询数据帧:

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

关于python - 使用 Pandas query() 过滤时间戳列上的数据帧,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/60277241/

25 4 0
Copyright 2021 - 2024 cfsdn All Rights Reserved 蜀ICP备2022000587号
广告合作:1813099741@qq.com 6ren.com