CODEWITHSUNDEEP
pythonpandas
NKJ
NKJ

Reputation: 497

Error: pandas.core.indexing.IndexingError: Too many indexers

I am trying to Match multiple column in different sets and update an another column with the all the unmatched column name separated by ,

Update the result column with the unmatched column name

Input:

  A  B  C  D  E
0  f  e  b  a  d
1  c  b  a  c  b
2  f  f  a  b  c
3  d  c  c  d  c
4  f  b  b  b  e
5  b  a  f  c  d

Expected Output

   A  B  C  D  E           MATCHES
0  f  e  b  a  d  AD, BC Unmatched
1  c  b  a  c  b      BC Unmatched
2  f  f  a  b  c  AD, BC Unmatched
3  d  c  c  d  c       ALL MATCHED
4  f  b  b  b  e      AD Unmatched
5  b  a  f  c  d  AD, BC Unmatched

The below code gives Error when using it inside function Else its working fine if i am using separately without use of any function.

def test(x):
    try:
       for idx in df.index:
           unmatch_list = []
           if not df.loc[idx, 'A'] == df.loc[idx, 'D']:
              unmatch_list.append('AD')
           if not df.loc[idx, 'B'] == df.loc[idx, 'C']:
              unmatch_list.append('BC')
           # etcetera...
           if len(unmatch_list):
              unmatch_string = ', '.join(unmatch_list) + ' Unmatched'
           else:
              unmatch_string = 'ALL MATCHED'
           df.loc[idx, 'MATCHES'] = unmatch_string
 
     except ValueError:

It Gives Error when trying to process:

if not df.loc[idx, 'A'] == df.loc[idx, 'D']:
Error: pandas.core.indexing.IndexingError: Too many indexers

Need Suggestions:

Upvotes: 1

Views: 851

Answers (1)

jezrael
jezrael

Reputation: 862841

How is called function?

For me working if add return df and pass DataFrame to function:

def test(x):
    try:
       for idx in df.index:
           unmatch_list = []
           if not df.loc[idx, 'A'] == df.loc[idx, 'D']:
              unmatch_list.append('AD')
           if not df.loc[idx, 'B'] == df.loc[idx, 'C']:
              unmatch_list.append('BC')
           # etcetera...
           if len(unmatch_list):
              unmatch_string = ', '.join(unmatch_list) + ' Unmatched'
           else:
              unmatch_string = 'ALL MATCHED'
           df.loc[idx, 'MATCHES'] = unmatch_string
          
 
    except ValueError:
         print ('error')
    return df

df = test(df)
print (df)
   A  B  C  D  E           MATCHES
0  f  e  b  a  d  AD, BC Unmatched
1  c  b  a  c  b      BC Unmatched
2  f  f  a  b  c  AD, BC Unmatched
3  d  c  c  d  c       ALL MATCHED
4  f  b  b  b  e      AD Unmatched
5  b  a  f  c  d  AD, BC Unmatched

Solution with apply is possible, but is necessary change function like:

def test(x):
    try:
        unmatch_list = []
        if not x['A'] == x['D']:
           unmatch_list.append('AD')
        if not x['B'] == x['C']:
           unmatch_list.append('BC')
        # etcetera...
        if len(unmatch_list):
           unmatch_string = ', '.join(unmatch_list) + ' Unmatched'
        else:
           unmatch_string = 'ALL MATCHED'
 
    except ValueError:
         print ('error')
    return unmatch_string

df['MATCHES'] = df.apply(test, axis=1)
print (df)
   A  B  C  D  E           MATCHES
0  f  e  b  a  d  AD, BC Unmatched
1  c  b  a  c  b      BC Unmatched
2  f  f  a  b  c  AD, BC Unmatched
3  d  c  c  d  c       ALL MATCHED
4  f  b  b  b  e      AD Unmatched
5  b  a  f  c  d  AD, BC Unmatched

Upvotes: 1

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