10年内，哪一年高考题目最难？
裸睡的猪
共 4951字，需浏览 10分钟
·
2021-05-29 07:38
作者 ｜鸟哥
来源 ｜ python数据分析之禅
下面从3个角度进行分析
代码：
bar = (Bar().add_xaxis(list(range(2010,2021))).add_yaxis(series_name="历年一本线排名", yaxis_data=eve_scores_line, yaxis_index=0, color=colors[0]).set_series_opts(label_opts=opts.LabelOpts(is_show=True),markline_opts=opts.MarkLineOpts(data=[opts.MarkLineItem(type_="min", name="最小值"),opts.MarkLineItem(type_="max", name="最大值"),opts.MarkLineItem(type_="average", name="平均值"),]),colors=Faker.rand_color()).set_global_opts(xaxis_opts=opts.AxisOpts(name="年份",axisline_opts=opts.AxisLineOpts(linestyle_opts=opts.LineStyleOpts(color=colors[1]))),yaxis_opts=opts.AxisOpts(name="分数",type_="value",min_=400,max_=600,position="left",axisline_opts=opts.AxisLineOpts(linestyle_opts=opts.LineStyleOpts(color=colors[2])),axislabel_opts=opts.LabelOpts(formatter="{value}"),axistick_opts=opts.AxisTickOpts(is_show=True),splitline_opts=opts.SplitLineOpts(is_show=True),),tooltip_opts=opts.TooltipOpts(trigger="axis", axis_pointer_type="cross"),).render("每年一本线.html"))
for i in range(2010,2021): a=data[data['年份'].eq(i)] a=a[a['成绩'].ge(200)] a = a[a['成绩'].le(700)] sum_students = max(list(a['排名'])) dict={'200-300':0, '300-400':0, '400-500':0, '500-600':0, '600-700':0} for j in range(200,700,100): stmp = a[a['成绩'].ge(j)] stmp = stmp[stmp['成绩'].le(j+100)] renshu=int(list(stmp['排名'])[-1])-int(list(stmp['排名'])[0]) dict['{0}-{1}'.format(j,j+100)]=round(float(renshu/sum_students)*100,2) data_eve_years.append(dict)attr = Faker.choose()tl = Timeline()for i,j in zip(range(2010, 2021),data_eve_years): pie = ( Pie() .add( "", [list(z) for z in zip(list(j.keys()), [j[k] for k in list(j.keys())])], rosetype="radius", radius=["30%", "55%"], ) .set_global_opts(title_opts=opts.TitleOpts("{}年各分数段人数占比".format(i))) .set_series_opts(label_opts=opts.LabelOpts(formatter="{b}: {c}%")) ) tl.add(pie, "{}年".format(i))tl.render("timeline_pie.html")c = ( Line() .add_xaxis(xaxis_data=['{0}年'.format(i) for i in list(range(2010, 2021))]) .add_yaxis( series_name="历年600-700分人数占比情况", y_axis=[i['600-700'] for i in data_eve_years]) .set_global_opts( xaxis_opts=opts.AxisOpts(name="年份",axisline_opts=opts.AxisLineOpts( linestyle_opts=opts.LineStyleOpts(color='r'))), yaxis_opts=opts.AxisOpts( name="占比", type_="value", position="left", axislabel_opts=opts.LabelOpts(formatter="{value}%"), axistick_opts=opts.AxisTickOpts(is_show=True), splitline_opts=opts.SplitLineOpts(is_show=True), ), tooltip_opts=opts.TooltipOpts(trigger="axis", axis_pointer_type="cross"), ) .render("600-700占比折线图.html"))分析角度3：平均分排名
代码：
c = (Line()=['{0}年'.format(i) for i in list(range(2010,2021))]).add_yaxis(series_name="前1万名",y_axis=result[0],).add_yaxis(series_name="前2万名",y_axis=result[1],).add_yaxis(series_name="前3万名",y_axis=result[2],).add_yaxis(series_name="前4万名",y_axis=result[3],).set_global_opts(xaxis_opts=opts.AxisOpts(name="年份",axisline_opts=opts.AxisLineOpts(linestyle_opts=opts.LineStyleOpts(color='r'))),yaxis_opts=opts.AxisOpts(name="分数",type_="value",min_=500,max_=700,position="left",axislabel_opts=opts.LabelOpts(formatter="{value}"),axistick_opts=opts.AxisTickOpts(is_show=True),splitline_opts=opts.SplitLineOpts(is_show=True),),tooltip_opts=opts.TooltipOpts(trigger="axis", axis_pointer_type="cross"),).render("折线图.html"))
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