[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"$fsrk1lG1-weI7BQSM8xzZQs8r_9ppA9bUsQ_5ItRzZeU":3},{"answer":4,"createTime":5,"id":6,"options":7,"origin":12,"question":19,"related":20,"source":30,"type":31},[],"2023-05-13 19:40:07",9352710,[8,9,10,11],"Jupyter Notebook是一个交互式笔记本","Jupyter Notebook可以将说明文字、代码、图表、公式和结论都整合在一个文档中","Jupyter Notebook仅支持Python语言","Jupyter Notebook支持代码单元和Markdown单元",{"count":13,"courseId":14,"courseImg":15,"courseName":16,"workId":17,"workName":18},10,"dc60ca44c34ca2e245799247fe188b18","https:\u002F\u002Ftihai-oss-cloud.itihey.com\u002Fimg\u002F592ec71bbb66eb2b5a6bb4719b27c13f.png","案例驱动式Python基础与应用（省级一流课程）","3b805ea621ca49ea99ebe9266e6272d0","第10章 数据分析与可视化 章节测验","关于Jupyter Notebook描述不正确的是( )",[21,32,35,44,53,62,71,80,89,98],{"answer":22,"createTime":5,"id":23,"options":24,"question":29,"source":30,"type":31},[],9352709,[25,26,27,28],"包含了众多流行的科学、数学、工程和数据分析的Python库","仅支持Windows操作系统","开源和免费","Anaconda中包含编程的IDE—Jupyter Notebook","关于Anaconda的描述不正确的是( )","v1",0,{"answer":33,"createTime":5,"id":6,"options":34,"question":19,"source":30,"type":31},[],[8,9,10,11],{"answer":36,"createTime":5,"id":37,"options":38,"question":43,"source":30,"type":31},[],9352711,[39,40,41,42],"索引","列名","值","行名","DataFrame是pandas提供的二维表格,它不包含的部分是( )",{"answer":45,"createTime":5,"id":46,"options":47,"question":52,"source":30,"type":31},[],9352712,[48,49,50,51],"read_csv能够读取csv文件数据","to_csv能够将结构化数据写入.csv文件","csv是一种用分隔符分隔的文件格式,其分隔符不一定是逗号","read_csv能够读取各种文件数据,包括csv、excel、txt和数据库等","下列关于pandas数据读写说法错误的是( )",{"answer":54,"createTime":5,"id":55,"options":56,"question":61,"source":30,"type":31},[],9352713,[57,58,59,60],"df.loc['索引名', '列名'] df.iloc['索引位置', '列位置']","df.loc['索引位置', '列位置'] df.iloc['索引名', '列名']","df.loc['索引名', '列名'] df.iloc['索引名', '列名']","df.loc['索引位置', '列位置'] df.iloc['索引位置', '列位置']","下列loc、iloc属性的用法正确的是( )",{"answer":63,"createTime":5,"id":64,"options":65,"question":70,"source":30,"type":31},[],9352714,[66,67,68,69],"groupby方法支持对非数值列求和","groupby是pandas提供的一个用来分组的方法","groupby方法的结果能够直接查看","groupby方法通过参数axis来指定用来分组的列","下列关于groupby方法说法正确的是( )",{"answer":72,"createTime":5,"id":73,"options":74,"question":79,"source":30,"type":31},[],9352715,[75,76,77,78],"丢弃缺失值","用上一行数据填充缺失值","删除缺失值所在的列","用字符串填充缺失值","DataFrame中的缺失值的处理方法不包括( )",{"answer":81,"createTime":5,"id":82,"options":83,"question":88,"source":30,"type":31},[],9352716,[84,85,86,87],"\u003Cimg src=\"https:\u002F\u002Ftihai-oss-cloud.itihey.com\u002Fimg\u002Ff0a57ee818119f0a540f3963d69a826a.png\">","\u003Cimg src=\"https:\u002F\u002Ftihai-oss-cloud.itihey.com\u002Fimg\u002F60bdd8fa84f43471fa244428248d9239.png\">","\u003Cimg src=\"https:\u002F\u002Ftihai-oss-cloud.itihey.com\u002Fimg\u002Fe3eb1f93adcdc1d7ba1a0b99ed7f3814.png\">","\u003Cimg src=\"https:\u002F\u002Ftihai-oss-cloud.itihey.com\u002Fimg\u002F90bdb007f06978feee13cf90dc8fe8c6.png\">","请阅读下面一段程序: import matplotlib.pyplot as plt ax_one = plt.subplot(223) ax_one.plot([1,2,3,4,5]) plt.show() 运行程序,效果为( )",{"answer":90,"createTime":5,"id":91,"options":92,"question":97,"source":30,"type":31},[],9352717,[93,94,95,96],"xlim()","grid()","xticks","axhline()","下列函数中,可以设置坐标轴刻度标签的是( )",{"answer":99,"createTime":5,"id":100,"options":101,"question":106,"source":30,"type":31},[],9352718,[102,103,104,105],"twinx()","subplot2grid()","subplots()","subplot()","下列函数中,可以一次绘制多个子图的是( )"]