大数据可视化|Python疫情数据可视化分析+数据预测（pandas+pyecharts+statsmodels+matplotlib+sql） pandas|大数据|python|数据分析|数

1、MySQL数据库获取数据此处的原始数据表是全国各省的实时数据集，现在只获取江苏省份的数据

engine = create_engine(mysq_conn) # 具体内容以自己上就可以为准 select_data = "https://www.it610.com/article/select * from table_data where area='江苏'order by local_time desc" df = pd.read_sql(sql=select_data, con=engine) df.head()

大数据可视化|Python疫情数据可视化分析+数据预测（pandas+pyecharts+statsmodels+matplotlib+sql）

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2、转存数据集至本地csv，以免每次都要从数据库读取数据

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3、日期字符串字段，数据清洗

#转化获取年-月-日 new_df['日期'] = new_df['local_time'].dt.year.map(str)+'-'+new_df['local_time'].dt.month.map(str)+'-'+new_df['local_time'].dt.day.map(str)

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4、数据可视化

from pyecharts import options as opts from pyecharts.charts import Bar,Line,Pie,WordCloud,EffectScatter from pyecharts.charts import PictorialBar from pyecharts.globals import SymbolType from pyecharts.globals import ThemeType

c = ( Line(init_opts=opts.InitOpts(theme=ThemeType.MACARONS)) .add_xaxis(x_label) .add_yaxis( "新增确诊", is_smooth=True, symbol="emptyCircle", is_symbol_show=False, color="#6e9ef1", y_axis=y_data, label_opts=opts.LabelOpts(is_show=False), ) .set_series_opts( label_opts=opts.LabelOpts( is_show=False, position="inside", formatter="{c}", ) ) .set_global_opts( title_opts=opts.TitleOpts(title="江苏省日新增确诊趋势图"), tooltip_opts=opts.TooltipOpts(is_show=True,axis_pointer_type= "cross",trigger="axis"), xaxis_opts=opts.AxisOpts( name_rotate=60,axislabel_opts={"rotate":45}, axispointer_opts=opts.AxisPointerOpts( is_show=True, ), ), ) )c.render_notebook()

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line=( Line() .add_xaxis(xaxis_data=https://www.it610.com/article/x_label) .add_yaxis( series_name="最高新增城市", is_smooth=True, symbol="emptyCircle", is_symbol_show=False, color="#d14a61", y_axis=y_data, ) .add_yaxis( series_name="全省新增", is_smooth=True, symbol="emptyCircle", is_symbol_show=False, color="#6e9ef1", y_axis=y_data2, ) .set_global_opts( title_opts=opts.TitleOpts(title="江苏省日新增确诊突然增原因"), legend_opts=opts.LegendOpts(), xaxis_opts=opts.AxisOpts( type_="category", axistick_opts=opts.AxisTickOpts(is_align_with_label=True), axisline_opts=opts.AxisLineOpts( is_on_zero=False, linestyle_opts=opts.LineStyleOpts(color="#d14a61") ), axispointer_opts=opts.AxisPointerOpts( is_show=True, label=opts.LabelOpts(formatter=JsCode(js_formatter)) ), ), yaxis_opts=opts.AxisOpts( type_="value", splitline_opts=opts.SplitLineOpts( is_show=True, linestyle_opts=opts.LineStyleOpts(opacity=1) ), ), ) ) line.render_notebook()

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def line_charts()->Line: line1 = ( Line(init_opts=opts.InitOpts(width='1000px',height='500px'))# 示例对象 .add_xaxis(x_label)# x轴数据 .add_yaxis( "治愈率",# 图例名称 is_smooth=True, is_symbol_show=False, color="#6e9ef1", y_axis=y_label, # y轴数据 label_opts=opts.LabelOpts(is_show=False), linestyle_opts=opts.LineStyleOpts(width=2), yaxis_index=0, ) # 全局配置：标题/副标题 .set_global_opts( title_opts=opts.TitleOpts(title="全国治愈率/死亡率趋势图"),# 标题 xaxis_opts=opts.AxisOpts( name_rotate=60,axislabel_opts={"rotate":45}, ), yaxis_opts=opts.AxisOpts( name='治愈率(%)', min_=70, max_=100, interval=10, axislabel_opts=opts.LabelOpts(formatter='{value}%') ), toolbox_opts=opts.ToolboxOpts( # 工具栏 is_show = True, pos_top="top", pos_left="right", feature={ "saveAsImage": {} , "dataZoom":{"yAxisIndex": "none"}, "restore": {} , "magicType":{"show": True, "type":["line","bar"]}, "dataView": {} }, )) # bar 拓展 .extend_axis( yaxis=opts.AxisOpts( name='死亡率(%)', type_='value',# 类型 min_=3, max_=6, interval=1, ) ) ) return line1def line2_charts()->Line(): line1=( Line() .add_xaxis(x_label) .add_yaxis( '死亡率', y_axis=y_label1, is_smooth=True, # 设置线为平滑的 symbol="emptyCircle",# 悬浮数据样式 is_symbol_show=False,# 显示数据 color="#6e9ef1", ) ) return line1line1=line_charts() line2=line2_charts()line1.overlap(line2).render_notebook()

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bar = ( Line() .add_xaxis(xaxis_data=https://www.it610.com/article/x_data) .add_yaxis( series_name="累计确诊", y_axis=evaporation_capacity, yaxis_index=0, color=colors[1], label_opts=opts.LabelOpts(is_show=True), is_smooth=True, symbol="emptyCircle", is_symbol_show=False, linestyle_opts=opts.LineStyleOpts(width=2), ) .add_yaxis( series_name="累计死亡", y_axis=rainfall_capacity, yaxis_index=1, color=colors[0], label_opts=opts.LabelOpts(is_show=True), is_smooth=True, symbol="emptyCircle", is_symbol_show=False, linestyle_opts=opts.LineStyleOpts(width=2), ) .extend_axis( yaxis=opts.AxisOpts( name="死亡", type_="value", min_=50000, max_=4000000, position="right", axisline_opts=opts.AxisLineOpts( linestyle_opts=opts.LineStyleOpts(color=colors[1]) ), axislabel_opts=opts.LabelOpts(formatter="{value}"), ) ) .extend_axis( yaxis=opts.AxisOpts(type_="value", name="治愈", min_=50000, max_=150000000, position="left", axisline_opts=opts.AxisLineOpts( linestyle_opts=opts.LineStyleOpts(color=colors[2]) ), axislabel_opts=opts.LabelOpts(formatter="{value}"), splitline_opts=opts.SplitLineOpts( is_show=True, linestyle_opts=opts.LineStyleOpts(opacity=1) ), ) ) .set_global_opts( yaxis_opts=opts.AxisOpts( type_="value", name="确诊", min_=50000, max_=170000000, position="right", offset=20, axisline_opts=opts.AxisLineOpts( linestyle_opts=opts.LineStyleOpts(color=colors[0]) ), axislabel_opts=opts.LabelOpts(formatter="{value}"), ), ) )line = ( Line() .add_xaxis(xaxis_data=https://www.it610.com/article/x_data) .add_yaxis( series_name="累计治愈", y_axis=average_temperature, color=colors[2], label_opts=opts.LabelOpts(is_show=True), is_smooth=True, ) )bar.overlap(line).render_notebook()