Compare files excel
Peter Otten
__peter__ at web.de
Sun Jul 23 07:21:23 EDT 2017
Smith wrote:
> On 22/07/2017 22:21, Albert-Jan Roskam wrote:
>> df1['difference'] = (df1 == df2).all(axis=1)
>
> below here there is the mistake :
>
> In [17]: diff = df1['difference'] = (df1 == df2).all(axis=1)
>
---------------------------------------------------------------------------
> ValueError Traceback (most recent call
> last) <ipython-input-17-195a2c4caf00> in <module>()
> ----> 1 diff = df1['difference'] = (df1 == df2).all(axis=1)
>
> /usr/local/lib/python3.5/dist-packages/pandas/core/ops.py in f(self,
> other)
> 1295 def f(self, other):
> 1296 if isinstance(other, pd.DataFrame): # Another DataFrame
> -> 1297 return self._compare_frame(other, func, str_rep)
> 1298 elif isinstance(other, ABCSeries):
> 1299 return self._combine_series_infer(other, func)
>
> /usr/local/lib/python3.5/dist-packages/pandas/core/frame.py in
> _compare_frame(self, other, func, str_rep)
> 3570 def _compare_frame(self, other, func, str_rep):
> 3571 if not self._indexed_same(other):
> -> 3572 raise ValueError('Can only compare identically-labeled
> '
> 3573 'DataFrame objects')
> 3574 return self._compare_frame_evaluate(other, func, str_rep)
>
> ValueError: Can only compare identically-labeled DataFrame objects
The columns of both dataframes must be identical. Compare:
>>> import pandas as pd
>>> a = pd.DataFrame([[1,2],[3,4]], columns=["a", "b"])
>>> b = pd.DataFrame([[1,2],[3,5]], columns=["a", "c"])
With different column names:
>>> a != b
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/usr/lib/python3/dist-packages/pandas/core/ops.py", line 875, in f
return self._compare_frame(other, func, str_rep)
File "/usr/lib/python3/dist-packages/pandas/core/frame.py", line 2860, in
_compare_frame
raise ValueError('Can only compare identically-labeled '
ValueError: Can only compare identically-labeled DataFrame objects
Again, with identical column names:
>>> b = pd.DataFrame([[1,2],[3,5]], columns=["a", "b"])
>>> a != b
a b
0 False False
1 False True
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