{"task": {"agent_timeout": 1800, "task": "134", "verifier_timeout": 1800, "instruction": "# 134: DS-1000 Task\n\n## Prompt\nProblem:\nI am trying to find duplicates col rows in a pandas dataframe.\ndf=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'])\ndf\nOut[15]: \n   val  col1  col2  3col\n0    1     1     2     5\n1    1     3     4     1\n2    4     1     2     5\n3    5     1     4     9\n4    1     1     2     5\n\n\nduplicate_bool = df.duplicated(subset=['col1','col2'], keep='last')\nduplicate = df.loc[duplicate_bool == True]\nduplicate\nOut[16]: \n   val  col1  col2  3col\n0    1     1     2        5\n2    4     1     2        5\n\n\nIs there a way to add a column referring to the index of the last duplicate (the one kept)\nduplicate\nOut[16]: \n   val  col1  col2  3col  index_original\n0    1     1     2     5               4\n2    4     1     2     5               4\n\n\nNote: df could be very very big in my case....\n\n\nA:\n<code>\nimport pandas as pd\n\n\ndf=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'])\n</code>\nresult = ... # put solution in this variable\nBEGIN SOLUTION\n<code>\n\n## What to do\n- Edit `solution/solution.py` so the code passes the DS-1000 tests.\n- Do not access the internet or install new packages; required libraries are preinstalled in the Docker image.\n- Run tests locally via `bash tests/test.sh`.\n\n## Notes\n- Keep the variable names/signatures implied by the prompt/code_context.\n- The evaluator uses the original DS-1000 `code_context` (`test_execution` / `test_string`).\n", "memory": "", "runnable": false, "difficulty": "", "language": "", "cpus": "", "instruction_truncated": false, "category": "", "compose": false, "has_solution": true, "oracle": null, "docker_image": "ds1000:latest", "taskset": "ds1000", "tags": []}, "runs": []}