[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"$fwAG0K3LMpwZaYntlfbTCPybeRI04JTOSFbZjhvbIiqw":3},{"answer":4,"createTime":5,"id":6,"options":7,"origin":12,"question":16,"related":17,"source":27,"type":28},[],"2023-11-13 19:05:07",105563990,[8,9,10,11],"wordcloud","Numpy","jieba","matplotlib",{"courseId":13,"courseImg":14,"courseName":15},"0b611f573df91eebfe936fc3f3550502","https:\u002F\u002Ftihai-oss-cloud.itihey.com\u002Fimg\u002F25b30343053994e8940089572d36015b.jpg","大数据可视化技术","对Text文本文件进行分词处理常用的第三方包是( )",[18,29,32,41,50,59,68,77,85,94],{"answer":19,"createTime":5,"id":20,"options":21,"question":26,"source":27,"type":28},[],105563989,[22,23,24,25],"pip install pandas","pip show pandas","pip uninstall pandas","install pandas","在jupyter notebook中安装pandas程序包的命令是( )","v1",0,{"answer":30,"createTime":5,"id":6,"options":31,"question":16,"source":27,"type":28},[],[8,9,10,11],{"answer":33,"createTime":5,"id":34,"options":35,"question":40,"source":27,"type":28},[],105563991,[36,37,38,39],"import numpy as np import matplotlib.pyplot as plt data = np.array([20, 50, 10, 15, 30, 55]) pie_labels = np.array(['A', 'B', 'C', 'D', 'E', 'F']) plt.pie(data, labels=pie_labels) plt.show()","import numpy as np import matplotlib.pyplot as plt data = np.array([20, 50, 10, 15, 30, 55]) pie_labels = np.array(['A', 'B', 'C', 'D', 'E', 'F']) plt.pie(data, radius=1.5, labels=pie_labels) plt.show()","import numpy as np import matplotlib.pyplot as plt data = np.array([20, 50, 10, 15, 30, 55]) pie_labels = np.array(['A', 'B', 'C', 'D', 'E', 'F']) plt.pie(data, radius=1.5, explode=[0, 0.2, 0, 0, 0, 0],labels=pie_labels) plt.show()","import numpy as np import matplotlib.pyplot as plt data = np.array([20, 50, 10, 15, 30, 55]) pie_labels = np.array(['A', 'B', 'C', 'D', 'E', 'F']) plt.pie(data, radius=1.5, wedgeprops={'width': 0.6},labels=pie_labels) plt.show()","下列选项中,程序运行的效果为圆环图的是( )",{"answer":42,"createTime":5,"id":43,"options":44,"question":49,"source":27,"type":28},[],105563992,[45,46,47,48],"xlim()","grid ()","xticks()","axhline()","下列函数中,可以设置坐标轴刻度标签的是( )",{"answer":51,"createTime":5,"id":52,"options":53,"question":58,"source":27,"type":28},[],105563993,[54,55,56,57],"plt.axhline(y=1.5, ls='--', linewidth=1.5)","plt.axhline(y=1, ls='--', linewidth=1.5)","plt.axvline(x=1.5, ls='--', linewidth=1.5)","plt.axvline(x=1, ls='--', linewidth=1.5)","下列选项中,可以为图表添加一条值为1.5的水平参考线的是( )",{"answer":60,"createTime":5,"id":61,"options":62,"question":67,"source":27,"type":28},[],105563994,[63,64,65,66],"'k'","'#000000'","(0.0, 0.0, 0.0)","'b'","下列选项中,表示的颜色不是黑色的是( )",{"answer":69,"createTime":5,"id":70,"options":71,"question":76,"source":27,"type":28},[],105563995,[72,73,74,75],"\u003Cimg src=\"https:\u002F\u002Ftihai-oss-cloud.itihey.com\u002Fimg\u002F99f79eeace86123feb787f4d813e0998.png\">","\u003Cimg src=\"https:\u002F\u002Ftihai-oss-cloud.itihey.com\u002Fimg\u002F590c017e90286b391e09b9d69db4e92e.png\">","\u003Cimg src=\"https:\u002F\u002Ftihai-oss-cloud.itihey.com\u002Fimg\u002Fdd453dfc0e51dd3e334cb54fe5243636.png\">","\u003Cimg src=\"https:\u002F\u002Ftihai-oss-cloud.itihey.com\u002Fimg\u002F04c6972e18aa7adca2f5bc49be62eac7.png\">","请阅读下面一段程序: %matplotlib auto 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":78,"createTime":5,"id":79,"options":80,"question":84,"source":27,"type":28},[],105563996,[11,81,82,83],"seaborn","bokeh","pyecharts","下列哪个可视化库可以生成Echarts 图表?( )",{"answer":86,"createTime":5,"id":87,"options":88,"question":93,"source":27,"type":28},[],105563997,[89,90,91,92],"twinx()","constrained_layout()","tight_layout()","GridSpec()","下列选项中,可以实现紧密布局的是( )",{"answer":95,"createTime":96,"id":97,"options":98,"question":103,"source":27,"type":28},[],"2023-11-13 19:05:08",105563998,[99,100,101,102],"Scatter","Map","Funnel","Sankey","下列选项中,可以创建漏斗图的是( )"]