How can I convert price columns to an integer? - pandas

Question

How can I convert price columns to an integer?
code:
car_sales["Total Sales"] = car_sales["Price"].astype(int).cumsum()
car_sales
error:
ValueError Traceback (most recent call last)
<ipython-input-124-b84f0a711067> in <module>
----> 1 car_sales["Total Sales"] = car_sales["Price"].astype(int).cumsum()
2 car_sales
~\anaconda3\lib\site-packages\pandas\core\generic.py in astype(self, dtype, copy, errors)
5696 else:
5697 # else, only a single dtype is given
-> 5698 new_data = self._data.astype(dtype=dtype, copy=copy, errors=errors)
5699 return self._constructor(new_data).__finalize__(self)
5700
~\anaconda3\lib\site-packages\pandas\core\internals\managers.py in astype(self, dtype, copy, errors)
580
581 def astype(self, dtype, copy: bool = False, errors: str = "raise"):
--> 582 return self.apply("astype", dtype=dtype, copy=copy, errors=errors)
583
584 def convert(self, **kwargs):
~\anaconda3\lib\site-packages\pandas\core\internals\managers.py in apply(self, f, filter, **kwargs)
440 applied = b.apply(f, **kwargs)
441 else:
--> 442 applied = getattr(b, f)(**kwargs)
443 result_blocks = _extend_blocks(applied, result_blocks)
444
~\anaconda3\lib\site-packages\pandas\core\internals\blocks.py in astype(self, dtype, copy, errors)
623 vals1d = values.ravel()
624 try:
--> 625 values = astype_nansafe(vals1d, dtype, copy=True)
626 except (ValueError, TypeError):
627 # e.g. astype_nansafe can fail on object-dtype of strings
~\anaconda3\lib\site-packages\pandas\core\dtypes\cast.py in astype_nansafe(arr, dtype, copy, skipna)
872 # work around NumPy brokenness, #1987
873 if np.issubdtype(dtype.type, np.integer):
--> 874 return lib.astype_intsafe(arr.ravel(), dtype).reshape(arr.shape)
875
876 # if we have a datetime/timedelta array of objects
pandas\_libs\lib.pyx in pandas._libs.lib.astype_intsafe()
ValueError: invalid literal for int() with base 10: ' 4 00'

Answer 1

There exists a to_numeric function in pandas. See here.
car_sales["Total Sales"] = pd.to_numeric(car_sales["Price"], errors='coerce').cumsum()
This does return nan for 4 00 however so you must be careful. Follow what David Erickson said.
As an example if it is all spaces are supposed to be decimals, then
car_sales["Price"].str.replace(' ', '.')
should work if done before the conversion from an object.