df.dtypes
name object
rating object
genre object
year int64
released object
score float64
votes float64
director object
writer object
star object
country object
budget float64
gross float64
company object
runtime float64
dtype: object
Then when i try to convert using :
df['budget'] = df['budget'].astype("int64")
it says:
ValueError Traceback (most recent call last)
<ipython-input-23-6ced5964af60> in <module>
1 # Change Datatype for Columns
----> 2 df['budget'] = df['budget'].astype("int64")
3
4 #df['column_name'].astype(np.float).astype("Int32")
5 #df['gross'] = df['gross'].astype('int64')
~\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)
866
867 if not np.isfinite(arr).all():
--> 868 raise ValueError("Cannot convert non-finite values (NA or inf) to integer")
869
870 elif is_object_dtype(arr):
ValueError: Cannot convert non-finite values (NA or inf) to integer
Assuming that the budget does not contain infinite values, the problem may be because you have nan values. These values are usually allowed in floats but not in ints.
You can:
df['budget'] = df['budget'].astype("Int64")
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