Python Pandas - error: Can only compare identically-labeled Series objects

Question

set df1["name"] = df2["name] if df1["id"] == df2["id].

Both dataframes are of different sizes. I am trying to implement this behavior by writing the code as below:

   dtl['name'] = dtlLookUp[["name"]].loc[ dtlLookUp["id"] == (dtl["id"]) ]

However, I am getting error:

ValueError: Can only compare identically-labeled Series objects

EDIT :

dtl['name'] = dtlLookUp[["name"]].loc[ dtlLookUp["id"].isin(dtl["id"])) ] ? Can you come up with a minimal reproducible example ? — harpan
– harpan, Commented Oct 31, 2018 at 17:32
Could you post the output of dtl.info() and dtlLookup.info() — Vishnudev Krishnadas
– Vishnudev Krishnadas, Commented Oct 31, 2018 at 17:34
@harvpan , I want to get the name for that particular id. So, I think I need comparison: == rather then .isin() . seems right? — Akhan
– Akhan, Commented Oct 31, 2018 at 17:54
@frozenshine can you come up with a minimal reproducible example ? — harpan
– harpan, Commented Oct 31, 2018 at 17:55

miken32 · Accepted Answer · 2022-10-11 18:06:28Z

13

My problem is solved. Posting it for anyone else who might encounter the same error ( as I search this error but none of the already posted solutions worked for me, So I simply changed the orientation of my problem solving). I treated this problem as a Left Join.

    psb = pd.merge(dtl, dtlLookUp, how='left', on=['id'])

edited Oct 11, 2022 at 18:06

miken32

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answered Oct 31, 2018 at 19:06

Akhan

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Vishnudev Krishnadas · Accepted Answer · 2018-10-31 18:02:10Z

2

Convert id columns on both dataframe to same dtype before condition check. I am assuming the columns named id should have dtype int.

df1['id'] = df1.id.astype(int)
df2['id'] = df2.id.astype(int)

Put values from the other dataframe based on selection

selection = (df1.id == df2.id)
df1.loc[selection, 'name'] = df2.loc[selection, 'name']

answered Oct 31, 2018 at 18:02

Vishnudev Krishnadas

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4 Comments

Akhan Over a year ago

If i use astype(int), I get error: ValueError: cannot convert float NaN to integer

Vishnudev Krishnadas Over a year ago

You need to fill nan before comparing. Use df.id.fillna(0) to fill zeros where the value is empty i.e. np.nan

Akhan Over a year ago

ok thanks for that. After filling nan's, selection = (df1.id == df2.id) gives the same error as mentioned in the question :(

Vishnudev Krishnadas Over a year ago

@frozenshine How about you use df.reset_index(drop=True) for both dataframe and then select? Pandas uses index for matching

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