Python datetime获取月份报错：TypeError: 'getset_descriptor'对象不可调用

我有一个包含datetime列的DataFrame，该列存储的是从epoch开始的毫秒数。我用lambda函数成功获取了星期几（周一为0），但获取月份时触发错误：TypeError: 'getset_descriptor' object is not callable。

相关代码 #

from datetime import date
from datetime import time
from datetime import datetime

# 获取星期几（周一为0）
df2['week_day'] = df2['datetime'].apply(lambda x: datetime.weekday(datetime.fromtimestamp(x / 1000))) # 正常运行
print ('converted datetime to weekday')
df2
df2['Month'] = df2['datetime'].apply(lambda x: datetime.month(datetime.fromtimestamp(x / 1000)))      # 运行出错
#pd.DatetimeIndex(df2['datetime']).month
df2

完整错误信息 #

TypeError                                 Traceback (most recent call last)
Input In [16], in <cell line: 9>()
      7 print ('converted datetime to weekday')
      8 df2
----> 9 df2['Month'] = df2['datetime'].apply(lambda x: datetime.month(datetime.fromtimestamp(x / 1000)))
     10 #pd.DatetimeIndex(df2['datetime']).month
     11 df2

File C:\ProgramData\Anaconda3\lib\site-packages\pandas\core\series.py:4433, in Series.apply(self, func, convert_dtype, args, **kwargs)
   4323 def apply(
   4324     self,
   4325     func: AggFuncType,
   (...)
   4328     **kwargs,
   4329 ) -> DataFrame | Series:
   4330     """
   4331     Invoke function on values of Series.
   4332 
   (...)
   4431     dtype: float64
   4432     """
-> 4433     return SeriesApply(self, func, convert_dtype, args, kwargs).apply()

File C:\ProgramData\Anaconda3\lib\site-packages\pandas\core\apply.py:1082, in SeriesApply.apply(self)
   1078 if isinstance(self.f, str):
   1079     # if we are a string, try to dispatch
   1080     return self.apply_str()
-> 1082 return self.apply_standard()

File C:\ProgramData\Anaconda3\lib\site-packages\pandas\core\apply.py:1137, in SeriesApply.apply_standard(self)
   1131         values = obj.astype(object)._values
   1132         # error: Argument 2 to "map_infer" has incompatible type
   1133         # "Union[Callable[..., Any], str, List[Union[Callable[..., Any], str]],
   1134         # Dict[Hashable, Union[Union[Callable[..., Any], str],
   1135         # List[Union[Callable[..., Any], str]]]]]"; expected
   1136         # "Callable[[Any], Any]"
-> 1137         mapped = lib.map_infer(
   1138             values,
   1139             f,  # type: ignore[arg-type]
   1140             convert=self.convert_dtype,
   1141         )
   1143 if len(mapped) and isinstance(mapped[0], ABCSeries):
   1144     # GH#43986 Need to do list(mapped) in order to get treated as nested
   1145     #  See also GH#25959 regarding EA support
   1146     return obj._constructor_expanddim(list(mapped), index=obj.index)

File C:\ProgramData\Anaconda3\lib\site-packages\pandas\_libs\lib.pyx:2870, in pandas._libs.lib.map_infer()

Input In [16], in <lambda>(x)
      7 print ('converted datetime to weekday')
      8 df2
----> 9 df2['Month'] = df2['datetime'].apply(lambda x: datetime.month(datetime.fromtimestamp(x / 1000)))
     10 #pd.DatetimeIndex(df2['datetime']).month
     11 df2

TypeError: 'getset_descriptor' object is not callable

datetime.weekday()是类方法，需要传入datetime对象作为参数；但month是datetime对象的属性，不是可调用的方法，你错误地给它加了括号当作方法使用，因此触发类型错误。

方案1：修正lambda函数 #

将datetime.month(...)改为调用datetime对象的.month属性：

df2['Month'] = df2['datetime'].apply(lambda x: datetime.fromtimestamp(x / 1000).month)

方案2：更高效的pandas原生处理 #

避免使用apply（循环处理效率低），直接用pandas的时间序列工具转换并提取字段：

import pandas as pd

# 将毫秒时间戳转为pandas datetime类型
df2['datetime'] = pd.to_datetime(df2['datetime'], unit='ms')
# 直接提取星期几（周一为0）和月份
df2['week_day'] = df2['datetime'].dt.weekday
df2['Month'] = df2['datetime'].dt.month

内容的提问来源于stack exchange，提问作者J.Billman