{"task": {"agent_timeout": 1800, "task": "249", "verifier_timeout": 1800, "instruction": "# 249: DS-1000 Task\n\n## Prompt\nProblem:\nI have a dataframe with column names, and I want to find the one that contains a certain string, but does not exactly match it. I'm searching for 'spike' in column names like 'spike-2', 'hey spike', 'spiked-in' (the 'spike' part is always continuous). \nI want the column name to be returned as a string or a variable, so I access the column later with df['name'] or df[name] as normal. I want to get a dataframe like:\n   spike-2  spiked-in\n0      xxx        xxx\n1      xxx        xxx\n2      xxx        xxx\n(xxx means number)\n\nI've tried to find ways to do this, to no avail. Any tips?\n\n\nA:\n<code>\nimport pandas as pd\n\n\ndata = {'spike-2': [1,2,3], 'hey spke': [4,5,6], 'spiked-in': [7,8,9], 'no': [10,11,12]}\ndf = pd.DataFrame(data)\ns = 'spike'\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": []}