# ds1000 / 134

- taskset: [ds1000](https://harnessreport.com/tasks/ds1000.md)
- difficulty: 
- category: 
- language: 
- runnable from the site: no
- agent timeout: 1800s

## Results by harness

_none yet_

## Instruction

```
# 134: DS-1000 Task

## Prompt
Problem:
I am trying to find duplicates col rows in a pandas dataframe.
df=pd.DataFrame(data=[[1,1,2,5],[1,3,4,1],[4,1,2,5],[5,1,4,9],[1,1,2,5]],columns=['val', 'col1','col2','3col'])
df
Out[15]: 
   val  col1  col2  3col
0    1     1     2     5
1    1     3     4     1
2    4     1     2     5
3    5     1     4     9
4    1     1     2     5


duplicate_bool = df.duplicated(subset=['col1','col2'], keep='last')
duplicate = df.loc[duplicate_bool == True]
duplicate
Out[16]: 
   val  col1  col2  3col
0    1     1     2        5
2    4     1     2        5


Is there a way to add a column referring to the index of the last duplicate (the one kept)
duplicate
Out[16]: 
   val  col1  col2  3col  index_original
0    1     1     2     5               4
2    4     1     2     5               4


Note: df could be very very big in my case....


A:
<code>
import pandas as pd


df=pd.DataFrame(data=[[1,1,2,5],[1,3,4,1],[4,1,2,5],[5,1,4,9],[1,1,2,5]],columns=['val', 'col1','col2','3col'])
</code>
result = ... # put solution in this variable
BEGIN SOLUTION
<code>

## What to do
- Edit `solution/solution.py` so the code passes the DS-1000 tests.
- Do not access the internet or install new packages; required libraries are preinstalled in the Docker image.
- Run tests locally via `bash tests/test.sh`.

## Notes
- Keep the variable names/signatures implied by the prompt/code_context.
- The evaluator uses the original DS-1000 `code_context` (`test_execution` / `test_string`).
```
---
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