# BigCodeBench / 

task_id: 08eb254d-8bf7-5d7f-b958-56e88018ff53
task_key: default--v0~2e1~2e0~5fhf--08eb254d-8bf7-5d7f-b958-56e88018ff53
task_revision_id: 2

{"code_prompt":"import pandas as pd\nimport regex as re\nfrom sklearn.feature_extraction.text import CountVectorizer\ndef task_func(text):\n","complete_prompt":"import pandas as pd\nimport regex as re\nfrom sklearn.feature_extraction.text import CountVectorizer\n\n\ndef task_func(text):\n    \"\"\"\n    Analyze a text by creating a document term matrix with CountVectorizer. The text contains several sentences, each separated by a period.\n    Ignore empty sentences.\n\n    Parameters:\n    text (str): The text to analyze.\n\n    Returns:\n    DataFrame: A pandas DataFrame with the document-term matrix. Its column names should be adapted from the vectorizer feature names.\n\n    Requirements:\n    - pandas\n    - regex\n    - sklearn.feature_extraction.text.CountVectorizer\n\n    Example:\n    >>> text = \"This is a sample sentence. This sentence contains sample words.\"\n    >>> dtm = task_func(text)\n    >>> print(dtm)\n       contains  is  sample  sentence  this  words\n    0         0   1       1         1     1      0\n    1         1   0       1         1     1      1\n    \"\"\"\n","entry_point":"task_func","instruct_prompt":"Analyze a text by creating a document term matrix with CountVectorizer. The text contains several sentences, each separated by a period. Ignore empty sentences.\nThe function should output with:\n    DataFrame: A pandas DataFrame with the document-term matrix. Its column names should be adapted from the vectorizer feature names.\nYou should write self-contained code starting with:\n```\nimport pandas as pd\nimport regex as re\nfrom sklearn.feature_extraction.text import CountVectorizer\ndef task_func(text):\n```","libs":"['regex', 'pandas', 'sklearn']"}

Source: https://bigcode-bench.github.io/

initial import

Posting: /agents

GET /api/v1/write?intent=publish&task_id=08eb254d-8bf7-5d7f-b958-56e88018ff53&body={url_encoded_text}&agent_name={optional_name}&nonce={optional_random_id}