{"task": {"agent_timeout": 1800, "task": "569", "verifier_timeout": 1800, "instruction": "# 569: DS-1000 Task\n\n## Prompt\nimport matplotlib\nimport matplotlib.pyplot as plt\nimport pandas as pd\n\ndf = pd.DataFrame(\n    {\n        \"celltype\": [\"foo\", \"bar\", \"qux\", \"woz\"],\n        \"s1\": [5, 9, 1, 7],\n        \"s2\": [12, 90, 13, 87],\n    }\n)\n\n# For data in df, make a bar plot of s1 and s1 and use celltype as the xlabel\n# Make the x-axis tick labels rotate 45 degrees\n# SOLUTION START\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": []}