{"kind":"task","effective_mode":"full","benchmark":{"kind":"benchmark","effective_mode":"full","slug":"bigcodebench","formal_name":"BigCodeBench","introduction":"BigCodeBench poses 1,140 function-level tasks drawn across 139 libraries. It tests whether a model can compose several real APIs correctly rather than write one self-contained function.","introduction_ja":"","introduction_en":"","category":"Category not supplied","task_count":null,"acquisition_status":"Acquisition status not supplied","official_url":"https://bigcode-bench.github.io/","indexing_mode":"index","profile":{"resources":[],"task_format":"","scoring":"","metric":"","size":"","answer_access":"","license":"","citation":"","maintainer":"","released":"","why_hard":"","related":[],"history":"","construction":"","limitations":"","saturation":"","scores":[]}},"task_id":"2b67184b-8076-5b0c-a655-fee9dbb7cadf","task_key":"default--v0~2e1~2e0~5fhf--2b67184b-8076-5b0c-a655-fee9dbb7cadf","task_revision_id":"1","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf 2b67184b-8076-5b0c-a655-fee9dbb7cadf","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"import matplotlib\\nimport matplotlib.pyplot as plt\\nfrom sklearn.preprocessing import StandardScaler\\ndef task_func(df):\\n\",\"complete_prompt\":\"import matplotlib\\nimport matplotlib.pyplot as plt\\nfrom sklearn.preprocessing import StandardScaler\\n\\ndef task_func(df):\\n    \\\"\\\"\\\"\\n    Standardize 'Age' and 'Score' columns in a pandas DataFrame, remove duplicate entries based on 'Name', and plot a scatter plot of these standardized values.\\n\\n    Parameters:\\n    df (pandas.DataFrame): DataFrame containing 'Name', 'Age', and 'Score' columns.\\n\\n    Returns:\\n    pandas.DataFrame: DataFrame with standardized 'Age' and 'Score', duplicates removed.\\n    matplotlib.axes.Axes: Axes object of the scatter plot.\\n\\n    Note:\\n    - The function use \\\"Scatter Plot of Standardized Age and Score\\\" for the plot title.\\n    - The function use \\\"Age (standardized)\\\" and \\\"Score (standardized)\\\" as the xlabel and ylabel respectively.\\n\\n    Requirements:\\n    - pandas\\n    - numpy\\n    - matplotlib.pyplot\\n    - sklearn.preprocessing\\n\\n    Example:\\n    >>> import pandas as pd\\n    >>> data = pd.DataFrame([{'Name': 'James', 'Age': 30, 'Score': 85},{'Name': 'James', 'Age': 35, 'Score': 90},{'Name': 'Lily', 'Age': 28, 'Score': 92},{'Name': 'Sam', 'Age': 40, 'Score': 88},{'Name': 'Nick', 'Age': 50, 'Score': 80}])\\n    >>> modified_df, plot_axes = task_func(data)\\n    >>> modified_df.head()\\n        Name       Age     Score\\n    0  James -0.797724 -0.285365\\n    2   Lily -1.025645  1.312679\\n    3    Sam  0.341882  0.399511\\n    4   Nick  1.481487 -1.426825\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Standardize 'Age' and 'Score' columns in a pandas DataFrame, remove duplicate entries based on 'Name', and plot a scatter plot of these standardized values.\\nNote that: The function use \\\"Scatter Plot of Standardized Age and Score\\\" for the plot title. The function use \\\"Age (standardized)\\\" and \\\"Score (standardized)\\\" as the xlabel and ylabel respectively.\\nThe function should output with:\\n    pandas.DataFrame: DataFrame with standardized 'Age' and 'Score', duplicates removed.\\n    matplotlib.axes.Axes: Axes object of the scatter plot.\\nYou should write self-contained code starting with:\\n```\\nimport matplotlib\\nimport matplotlib.pyplot as plt\\nfrom sklearn.preprocessing import StandardScaler\\ndef task_func(df):\\n```\",\"libs\":\"['matplotlib', 'sklearn']\"}","display_format":"code","language":"","answer_status":"published","assets":[],"source_url":"https://bigcode-bench.github.io/","history":"initial import","indexing_mode":"index","subproblems":[],"grids":[]}