Reputation: 15
there is option available of merging duplicate row they affect in other column also. PFA in that merging duplicate column in one cell not affect other column please answer me how do i using python
thank you in advance
Upvotes: 0
Views: 884
Reputation: 1875
I think you should improve your question, but here is what I made out of it:
>>> my_data = {0: {'Date': 'Monday', 'Name': 'Lucy', 'Sale Price': 1371},
...: 1: {'Date': 'Monday', 'Name': 'Jone', 'Sale Price': 2269},
...: 2: {'Date': 'Monday', 'Name': 'Emily', 'Sale Price': 4337},
...: 3: {'Date': 'Tuesday', 'Name': 'Steven', 'Sale Price': 4755},
...: 4: {'Date': 'Tuesday', 'Name': 'Jone', 'Sale Price': 3493},
...: 5: {'Date': 'Tuesday', 'Name': 'Lucy', 'Sale Price': 4664},
...: 6: {'Date': 'Tuesday', 'Name': 'Emily', 'Sale Price': 2358},
...: 7: {'Date': 'Tuesday', 'Name': 'Ruby', 'Sale Price': 2337},
...: 8: {'Date': 'Wednesday', 'Name': 'Nicol', 'Sale Price': 1256},
...: 9: {'Date': 'Wednesday', 'Name': 'Steven', 'Sale Price': 4706},
...: 10: {'Date': 'Wednesday', 'Name': 'Jone', 'Sale Price': 3351}}
>>> df = pd.DataFrame.from_dict(my_data, orient='index')
>>> df
Date Name Sale Price
0 Monday Lucy 1371
1 Monday Jone 2269
2 Monday Emily 4337
3 Tuesday Steven 4755
4 Tuesday Jone 3493
5 Tuesday Lucy 4664
6 Tuesday Emily 2358
7 Tuesday Ruby 2337
8 Wednesday Nicol 1256
9 Wednesday Steven 4706
10 Wednesday Jone 3351
>>> df.groupby(['Date','Name']).sum()
Sale Price
Date Name
Monday Emily 4337
Jone 2269
Lucy 1371
Tuesday Emily 2358
Jone 3493
Lucy 4664
Ruby 2337
Steven 4755
Wednesday Jone 3351
Nicol 1256
Steven 4706
Upvotes: 1