David Crook David Crook - 20 days ago 6
Python Question

Python Pandas Only Compare Identically Labeled DataFrame Objects

I tried all the solutions here:
Pandas "Can only compare identically-labeled DataFrame objects" error

Didn't work for me. Here's what I've got. I have two data frames. One is a set of financial data that already exists in the system and another set that has some that may or may not exist in the system. I need to find the difference and add the stuff that doesn't exist.

Here is the code:

import pandas as pd
import numpy as np
from azure.storage.blob import AppendBlobService, PublicAccess, ContentSettings
from io import StringIO

dataUrl = "http://ichart.finance.yahoo.com/table.csv?s=MSFT"
blobUrlBase = "https://pyjobs.blob.core.windows.net/"
data = pd.read_csv(dataUrl)

abs = AppendBlobService(account_name='pyjobs', account_key='***')
abs.create_container("stocks", public_access = PublicAccess.Container)
abs.append_blob_from_text('stocks', 'msft', data[:25].to_csv(index=False))
existing = pd.read_csv(StringIO(abs.get_blob_to_text('stocks', 'msft').content))

ne = (data != existing).any(1)


the failing code is the final line. I was going through an article on determining differences between data frames.

I checked the dtypes on all columns, they appear to be the same. I also did a side by side output, I sorted teh axis, the indices, dropped the indices etc. Still get that bloody error.

Here is the output of the first row of existing and data

>>> existing[:1]
Date Open High Low Close Volume Adj Close
0 2016-05-27 51.919998 52.32 51.77 52.32 17653700 52.32
>>> data[:1]
Date Open High Low Close Volume Adj Close
0 2016-05-27 51.919998 52.32 51.77 52.32 17653700 52.32


Here is the exact error I receive:

>>> ne = (data != existing).any(1)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "C:\Anaconda3\lib\site-packages\pandas\core\ops.py", line 1169, in f
return self._compare_frame(other, func, str_rep)
File "C:\Anaconda3\lib\site-packages\pandas\core\frame.py", line 3571, in _compare_frame
raise ValueError('Can only compare identically-labeled '
ValueError: Can only compare identically-labeled DataFrame objects

Answer

In order to get around this, you want to compare the underlying numpy arrays.

import pandas as pd

df1 = pd.DataFrame([[1, 2], [3, 4]], columns=['A', 'B'], index=['One', 'Two'])
df2 = pd.DataFrame([[1, 2], [3, 4]], columns=['a', 'b'], index=['one', 'two'])


df1.values == df2.values

array([[ True,  True],
       [ True,  True]], dtype=bool)
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