Traceback (most recent call last):
File "C:\py\anaconda3\envs\tf2.10\lib\site-packages\pandas\core\groupby\groupby.py", line 1490, in array_func
result = self.grouper._cython_operation(
File "C:\py\anaconda3\envs\tf2.10\lib\site-packages\pandas\core\groupby\ops.py", line 959, in _cython_operation
return cy_op.cython_operation(
File "C:\py\anaconda3\envs\tf2.10\lib\site-packages\pandas\core\groupby\ops.py", line 657, in cython_operation
return self._cython_op_ndim_compat(
File "C:\py\anaconda3\envs\tf2.10\lib\site-packages\pandas\core\groupby\ops.py", line 497, in _cython_op_ndim_compat
return self._call_cython_op(
File "C:\py\anaconda3\envs\tf2.10\lib\site-packages\pandas\core\groupby\ops.py", line 541, in _call_cython_op
func = self._get_cython_function(self.kind, self.how, values.dtype, is_numeric)
File "C:\py\anaconda3\envs\tf2.10\lib\site-packages\pandas\core\groupby\ops.py", line 173, in _get_cython_function
raise NotImplementedError(
NotImplementedError: function is not implemented for this dtype: [how->mean,dtype->object]
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "C:\py\anaconda3\envs\tf2.10\lib\site-packages\pandas\core\nanops.py", line 1692, in _ensure_numeric
x = float(x)
ValueError: could not convert string to float: 'S001'
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "C:\py\anaconda3\envs\tf2.10\lib\site-packages\pandas\core\nanops.py", line 1696, in _ensure_numeric
x = complex(x)
ValueError: complex() arg is a malformed string
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "C:\Users\28081\PycharmProjects\pythonProject\大创\农产品溯源系统.py", line 331, in <module>
agri_system.visualize_sensor_data(days=7)
File "C:\Users\28081\PycharmProjects\pythonProject\大创\农产品溯源系统.py", line 267, in visualize_sensor_data
daily_avg = recent_data.groupby(pd.Grouper(key='timestamp', freq='D')).mean()
File "C:\py\anaconda3\envs\tf2.10\lib\site-packages\pandas\core\groupby\groupby.py", line 1855, in mean
result = self._cython_agg_general(
File "C:\py\anaconda3\envs\tf2.10\lib\site-packages\pandas\core\groupby\groupby.py", line 1507, in _cython_agg_general
new_mgr = data.grouped_reduce(array_func)
File "C:\py\anaconda3\envs\tf2.10\lib\site-packages\pandas\core\internals\managers.py", line 1503, in grouped_reduce
applied = sb.apply(func)
File "C:\py\anaconda3\envs\tf2.10\lib\site-packages\pandas\core\internals\blocks.py", line 329, in apply
result = func(self.values, **kwargs)
File "C:\py\anaconda3\envs\tf2.10\lib\site-packages\pandas\core\groupby\groupby.py", line 1503, in array_func
result = self._agg_py_fallback(values, ndim=data.ndim, alt=alt)
File "C:\py\anaconda3\envs\tf2.10\lib\site-packages\pandas\core\groupby\groupby.py", line 1457, in _agg_py_fallback
res_values = self.grouper.agg_series(ser, alt, preserve_dtype=True)
File "C:\py\anaconda3\envs\tf2.10\lib\site-packages\pandas\core\groupby\ops.py", line 994, in agg_series
result = self._aggregate_series_pure_python(obj, func)
File "C:\py\anaconda3\envs\tf2.10\lib\site-packages\pandas\core\groupby\ops.py", line 1015, in _aggregate_series_pure_python
res = func(group)
File "C:\py\anaconda3\envs\tf2.10\lib\site-packages\pandas\core\groupby\groupby.py", line 1857, in <lambda>
alt=lambda x: Series(x).mean(numeric_only=numeric_only),
File "C:\py\anaconda3\envs\tf2.10\lib\site-packages\pandas\core\generic.py", line 11556, in mean
return NDFrame.mean(self, axis, skipna, numeric_only, **kwargs)
File "C:\py\anaconda3\envs\tf2.10\lib\site-packages\pandas\core\generic.py", line 11201, in mean
return self._stat_function(
File "C:\py\anaconda3\envs\tf2.10\lib\site-packages\pandas\core\generic.py", line 11158, in _stat_function
return self._reduce(
File "C:\py\anaconda3\envs\tf2.10\lib\site-packages\pandas\core\series.py", line 4670, in _reduce
return op(delegate, skipna=skipna, **kwds)
File "C:\py\anaconda3\envs\tf2.10\lib\site-packages\pandas\core\nanops.py", line 96, in _f
return f(*args, **kwargs)
File "C:\py\anaconda3\envs\tf2.10\lib\site-packages\pandas\core\nanops.py", line 158, in f
result = alt(values, axis=axis, skipna=skipna, **kwds)
File "C:\py\anaconda3\envs\tf2.10\lib\site-packages\pandas\core\nanops.py", line 421, in new_func
result = func(values, axis=axis, skipna=skipna, mask=mask, **kwargs)
File "C:\py\anaconda3\envs\tf2.10\lib\site-packages\pandas\core\nanops.py", line 727, in nanmean
the_sum = _ensure_numeric(values.sum(axis, dtype=dtype_sum))
File "C:\py\anaconda3\envs\tf2.10\lib\site-packages\pandas\core\nanops.py", line 1699, in _ensure_numeric
raise TypeError(f"Could not convert {x} to numeric") from err
TypeError: Could not convert S001 to numeric
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "C:\Users\28081\PycharmProjects\pythonProject\大创\农产品溯源系统.py", line 336, in <module>
print("matplotlib版本：", plt.__version__)
AttributeError: module 'matplotlib.pyplot' has no attribute '__version__'
本文解决Python2环境下使用pandas时遇到的导入错误问题。通过修改site-packages下pandas/core/groupby/groupby.py文件中的导入语句，将import pandas.compat as compat改为from pandas import compat，成功解决了该问题。
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