Merging rows data such that the column which has different string values combines multiple cells into one separated by Comma

@g_mansii wrote:

I have below Dataframe ‘nbr’

||Postal_Code|Borough|Neighborhood|
|0|M3A|North York|Parkwoods|
|1|M4A|North York|Victoria Village|
|2|M5A|Downtown Toronto|Harbourfront|
|3|M5A|Downtown Toronto|Regent Park|
|4|M6A|North York|Lawrence Heights|
|5|M6A|North York|Lawrence Manor|
|6|M7A|Queen’s Park|Queen’s Park|

I want to run Python code Such that the rows 4 and 5 should merge into 1 row and give back result like below: (I have tried groupby and agg methods but they do not work here)

||Postal_Code|Borough|Neighborhood|
|0|M3A|North York|Parkwoods|
|1|M4A|North York|Victoria Village|
|2|M5A|Downtown Toronto|Harbourfront|
|3|M5A|Downtown Toronto|Regent Park|
|4|M6A|North York|Lawrence Heights , Lawrence Manor|
|5|M7A|Queen’s Park|Queen’s Park|

Code below :
nbr1.index = pd.RangeIndex(len(nbr1.index))

More than one neighborhood can exist in one postal code area.

for row_index,row in nbr1.iterrows():
if(nbr1.loc[row_index,[‘Postal_Code’]].values.astype(‘str’) == nbr1.loc[row_index + 1,[‘Postal_Code’]].values.astype(‘str’)):
print(‘inside same Postal code’)
print(nbr1.loc[row_index,[‘Postal_Code’]].values.astype(‘str’))
print(nbr1.loc[row_index + 1,[‘Postal_Code’]].values.astype(‘str’))

    if(nbr1.loc[row_index,['Borough']].values.astype('str') == nbr1.loc[row_index + 1,['Borough']].values.astype('str')):
        print('inside same Borough')
        print(nbr1.loc[row_index,['Borough']].values.astype('str'))
        print(nbr1.loc[row_index + 1,['Borough']].values.astype('str'))
        print(nbr1.loc[row_index,['Neighborhood']].values.astype('str'))
        print(nbr1.loc[row_index + 1,['Neighborhood']].values.astype('str'))
        print('Adding')
        nbr1[row_index,['Neighborhood']] = nbr1.loc[row_index,['Neighbourhood']].values.astype('str').apply(lambda x: '-'.join(x +1), axis=1)

nbr1.index = pd.RangeIndex(len(nbr1.index))

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