{"task": {"agent_timeout": 1800, "task": "63", "verifier_timeout": 1800, "instruction": "# 63: DS-1000 Task\n\n## Prompt\nProblem:\nI am using Pandas to get a dataframe like this:\n    name  a  b   c\n0  Aaron  3  5   7\n1  Aaron  3  6   9\n2  Aaron  3  6  10\n3  Brave  4  6   0\n4  Brave  3  6   1\n\n\nI want to replace each name with a unique ID so output looks like:\n  name  a  b   c\n0    1  3  5   7\n1    1  3  6   9\n2    1  3  6  10\n3    2  4  6   0\n4    2  3  6   1\n\n\nHow can I do that?\nThanks!\n\n\nA:\n<code>\nimport pandas as pd\n\nexample_df = pd.DataFrame({'name': ['Aaron', 'Aaron', 'Aaron', 'Brave', 'Brave', 'David'],\n                   'a': [3, 3, 3, 4, 3, 5],\n                   'b': [5, 6, 6, 6, 6, 1],\n                   'c': [7, 9, 10, 0, 1, 4]})\ndef f(df=example_df):\n    # return the solution in this function\n    # result = f(df)\n    ### BEGIN SOLUTION\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": []}