import numpy as np
import pandas as pd
marks = [
[90, 87],
[90, 95],
[92, 95]
]
[[90, 87], [90, 95], [92, 95]]
df = pd.DataFrame(marks, columns=['maths', 'science'])
|
maths |
science |
0 |
90 |
87 |
1 |
90 |
95 |
2 |
92 |
95 |
# reassign some values to nan
df['maths']
0 90
1 90
2 92
Name: maths, dtype: int64
0 NaN
1 90.0
2 92.0
Name: maths, dtype: float64
df = df.astype('int') # this will throw error
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-27-b2504c49b1a1> in <module>()
----> 1 df = df.astype('int') # this will throw error
~/anaconda3/envs/py36/lib/python3.6/site-packages/pandas/core/generic.py in astype(self, dtype, copy, errors, **kwargs)
5689 # else, only a single dtype is given
5690 new_data = self._data.astype(dtype=dtype, copy=copy, errors=errors,
-> 5691 **kwargs)
5692 return self._constructor(new_data).__finalize__(self)
5693
~/anaconda3/envs/py36/lib/python3.6/site-packages/pandas/core/internals/managers.py in astype(self, dtype, **kwargs)
529
530 def astype(self, dtype, **kwargs):
--> 531 return self.apply('astype', dtype=dtype, **kwargs)
532
533 def convert(self, **kwargs):
~/anaconda3/envs/py36/lib/python3.6/site-packages/pandas/core/internals/managers.py in apply(self, f, axes, filter, do_integrity_check, consolidate, **kwargs)
393 copy=align_copy)
394
--> 395 applied = getattr(b, f)(**kwargs)
396 result_blocks = _extend_blocks(applied, result_blocks)
397
~/anaconda3/envs/py36/lib/python3.6/site-packages/pandas/core/internals/blocks.py in astype(self, dtype, copy, errors, values, **kwargs)
532 def astype(self, dtype, copy=False, errors='raise', values=None, **kwargs):
533 return self._astype(dtype, copy=copy, errors=errors, values=values,
--> 534 **kwargs)
535
536 def _astype(self, dtype, copy=False, errors='raise', values=None,
~/anaconda3/envs/py36/lib/python3.6/site-packages/pandas/core/internals/blocks.py in _astype(self, dtype, copy, errors, values, **kwargs)
631
632 # _astype_nansafe works fine with 1-d only
--> 633 values = astype_nansafe(values.ravel(), dtype, copy=True)
634
635 # TODO(extension)
~/anaconda3/envs/py36/lib/python3.6/site-packages/pandas/core/dtypes/cast.py in astype_nansafe(arr, dtype, copy, skipna)
674
675 if not np.isfinite(arr).all():
--> 676 raise ValueError('Cannot convert non-finite values (NA or inf) to '
677 'integer')
678
ValueError: Cannot convert non-finite values (NA or inf) to integer
df = df.fillna(0).astype('int') # this will throw error
|
maths |
science |
0 |
0 |
87 |
1 |
90 |
95 |
2 |
92 |
95 |