in one column in my df I have values and unite of measurements, so I extracted the values to another column however the dtype is still object

My table:

I wanted to convert them to float to use them in my calculations however I am getting the below error, even when doing a simple calculation such as df['uom_value'].astype(float).sum() any help is appreciated

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
Input In [22], in <cell line: 1>()
----> 1 df['uom_value'].astype(float).sum()

File ~\Anaconda3\envs\general\lib\site-packages\pandas\core\generic.py:5912, in NDFrame.astype(self, dtype, copy, errors)
   5905     results = [
   5906         self.iloc[:, i].astype(dtype, copy=copy)
   5907         for i in range(len(self.columns))
   5908     ]
   5910 else:
   5911     # else, only a single dtype is given
-> 5912     new_data = self._mgr.astype(dtype=dtype, copy=copy, errors=errors)
   5913     return self._constructor(new_data).__finalize__(self, method="astype")
   5915 # GH 33113: handle empty frame or series

File ~\Anaconda3\envs\general\lib\site-packages\pandas\core\internals\managers.py:419, in BaseBlockManager.astype(self, dtype, copy, errors)
    418 def astype(self: T, dtype, copy: bool = False, errors: str = "raise") -> T:
--> 419     return self.apply("astype", dtype=dtype, copy=copy, errors=errors)

File ~\Anaconda3\envs\general\lib\site-packages\pandas\core\internals\managers.py:304, in BaseBlockManager.apply(self, f, align_keys, ignore_failures, **kwargs)
    302         applied = b.apply(f, **kwargs)
    303     else:
--> 304         applied = getattr(b, f)(**kwargs)
    305 except (TypeError, NotImplementedError):
    306     if not ignore_failures:

File ~\Anaconda3\envs\general\lib\site-packages\pandas\core\internals\blocks.py:580, in Block.astype(self, dtype, copy, errors)
    562 """
    563 Coerce to the new dtype.
    564 
   (...)
    576 Block
    577 """
    578 values = self.values
--> 580 new_values = astype_array_safe(values, dtype, copy=copy, errors=errors)
    582 new_values = maybe_coerce_values(new_values)
    583 newb = self.make_block(new_values)

File ~\Anaconda3\envs\general\lib\site-packages\pandas\core\dtypes\cast.py:1292, in astype_array_safe(values, dtype, copy, errors)
   1289     dtype = dtype.numpy_dtype
   1291 try:
-> 1292     new_values = astype_array(values, dtype, copy=copy)
   1293 except (ValueError, TypeError):
   1294     # e.g. astype_nansafe can fail on object-dtype of strings
   1295     #  trying to convert to float
   1296     if errors == "ignore":

File ~\Anaconda3\envs\general\lib\site-packages\pandas\core\dtypes\cast.py:1237, in astype_array(values, dtype, copy)
   1234     values = values.astype(dtype, copy=copy)
   1236 else:
-> 1237     values = astype_nansafe(values, dtype, copy=copy)
   1239 # in pandas we don't store numpy str dtypes, so convert to object
   1240 if isinstance(dtype, np.dtype) and issubclass(values.dtype.type, str):

File ~\Anaconda3\envs\general\lib\site-packages\pandas\core\dtypes\cast.py:1181, in astype_nansafe(arr, dtype, copy, skipna)
   1177     raise ValueError(msg)
   1179 if copy or is_object_dtype(arr.dtype) or is_object_dtype(dtype):
   1180     # Explicit copy, or required since NumPy can't view from / to object.
-> 1181     return arr.astype(dtype, copy=True)
   1183 return arr.astype(dtype, copy=copy)

ValueError: could not convert string to float: 'you can see diemension in the order, it was 3'

CodePudding user response：

Use from pandas.to_numeric method. Note that it is better to set the coerce argument for your method based on your usage. For more detail, read about it in docs