TypeError Traceback (most recent call last)
Cell In[4], line 7
1 # 定义填充策略
2 fill_values = {
3 '驱动电机转速': 0,
4 '驱动电机转矩': 0,
5 '电机控制器直流母线电流': 0,
6 '电机控制器输入电压': 0,
----> 7 '驱动电机温度': df['驱动电机温度'].mean(),
8 '驱动电机控制器温度': df['驱动电机控制器温度'].mean()
9 }
11 # 对特定列进行填充
12 for column, value in fill_values.items():
File D:\anaconda\Lib\site-packages\pandas\core\series.py:6549, in Series.mean(self, axis, skipna, numeric_only, **kwargs)
6541 @doc(make_doc("mean", ndim=1))
6542 def mean(
6543 self,
(...)
6547 **kwargs,
6548 ):
-> 6549 return NDFrame.mean(self, axis, skipna, numeric_only, **kwargs)
File D:\anaconda\Lib\site-packages\pandas\core\generic.py:12420, in NDFrame.mean(self, axis, skipna, numeric_only, **kwargs)
12413 def mean(
12414 self,
12415 axis: Axis | None = 0,
(...)
12418 **kwargs,
12419 ) -> Series | float:
> 12420 return self._stat_function(
12421 "mean", nanops.nanmean, axis, skipna, numeric_only, **kwargs
12422 )
File D:\anaconda\Lib\site-packages\pandas\core\generic.py:12377, in NDFrame._stat_function(self, name, func, axis, skipna, numeric_only, **kwargs)
12373 nv.validate_func(name, (), kwargs)
12375 validate_bool_kwarg(skipna, "skipna", none_allowed=False)
> 12377 return self._reduce(
12378 func, name=name, axis=axis, skipna=skipna, numeric_only=numeric_only
12379 )
File D:\anaconda\Lib\site-packages\pandas\core\series.py:6457, in Series._reduce(self, op, name, axis, skipna, numeric_only, filter_type, **kwds)
6452 # GH#47500 - change to TypeError to match other methods
6453 raise TypeError(
6454 f"Series.{name} does not allow {kwd_name}={numeric_only} "
6455 "with non-numeric dtypes."
6456 )
-> 6457 return op(delegate, skipna=skipna, **kwds)
File D:\anaconda\Lib\site-packages\pandas\core\nanops.py:147, in bottleneck_switch.__call__.<locals>.f(values, axis, skipna, **kwds)
145 result = alt(values, axis=axis, skipna=skipna, **kwds)
146 else:
--> 147 result = alt(values, axis=axis, skipna=skipna, **kwds)
149 return result
File D:\anaconda\Lib\site-packages\pandas\core\nanops.py:404, in _datetimelike_compat.<locals>.new_func(values, axis, skipna, mask, **kwargs)
401 if datetimelike and mask is None:
402 mask = isna(values)
--> 404 result = func(values, axis=axis, skipna=skipna, mask=mask, **kwargs)
406 if datetimelike:
407 result = _wrap_results(result, orig_values.dtype, fill_value=iNaT)
File D:\anaconda\Lib\site-packages\pandas\core\nanops.py:719, in nanmean(values, axis, skipna, mask)
716 dtype_count = dtype
718 count = _get_counts(values.shape, mask, axis, dtype=dtype_count)
--> 719 the_sum = values.sum(axis, dtype=dtype_sum)
720 the_sum = _ensure_numeric(the_sum)
722 if axis is not None and getattr(the_sum, "ndim", False):
File D:\anaconda\Lib\site-packages\numpy\core\_methods.py:49, in _sum(a, axis, dtype, out, keepdims, initial, where)
47 def _sum(a, axis=None, dtype=None, out=None, keepdims=False,
48 initial=_NoValue, where=True):
---> 49 return umr_sum(a, axis, dtype, out, keepdims, initial, where)
TypeError: can only concatenate str (not "int") to str
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