Python笔记：中国疫情随时间变化趋势

        涉及到时间序列的观察值，我们可以绘制折线图来做相关数据分析。例如：

from pyecharts.charts import *
from pyecharts import options as opts

x_data = ['2-06', '2-13', '2-20', '2-27', '3-05', '3-12', '3-19', '3-26', '4-02', '4-09', '4-17']
# 现有确诊
y1_data = [20677, 46537, 49156, 36829, 22695, 13171, 6287, 2896, 987, 351, 122]
# 累计治愈
y2_data = [817, 4131, 11788, 26403, 41966, 51533, 58381, 61731, 63612, 64236, 63494]
line = (Line()
        .add_xaxis(x_data)
        .add_yaxis('现有确诊', y1_data, color='#10aeb5')
        .add_yaxis('累计治愈', y2_data, color='#e83132')
        .set_series_opts(label_opts=opts.LabelOpts(is_show=True))
        .set_global_opts(
            title_opts=opts.TitleOpts(title='中国疫情随时间变化趋势')
       ))

# line.render(path='中国疫情折线图.html')
line.render_notebook()

输出结果：

        文末小trips：十六进制颜色码可参考： https://blog.csdn.net/bjbz_cxy/article/details/79514030

来源：oschina

链接：https://my.oschina.net/u/3750423/blog/4317172