厦门seo建站,类似淘宝商城网站建设方案,医疗器械公司,江苏网站建设网络推广1.显现用到的包Pyecharts 是一个用于生成 Echarts 图表的类库。常规的Echarts 是由百度开源的一个数据可视化 JS 库#xff0c;主要用于数据可视化。简单来说#xff0c;Pyecharts是一款将python与echarts结合的强大的数据可视化工具。使用 Pyecharts 可以生成独立的网页主要用于数据可视化。简单来说Pyecharts是一款将python与echarts结合的强大的数据可视化工具。使用 Pyecharts 可以生成独立的网页也可以在 flask , Django 中集成使用。2.Pyecharts安装# 安装 v1 以上版本$ pip install pyecharts -U# 如果需要安装 0.5.11 版本的开发者可以使用# pip install pyecharts0.5.11PS: 这里要专门说明一下自从 0.3.2 开始为了缩减项目本身的体积以及维持 pyecharts 项目的轻量化运行pyecharts 将不再自带地图 js 文件。如用户需要用到地图图表(Geo、Map)可自行安装对应的地图文件包。# 通过pip命令进行安装pip install echarts-countries-pypkgpip install echarts-china-provinces-pypkgpip install echarts-china-cities-pypkg3.实践1.柱状图from pyecharts.charts import Barfrom pyecharts import options as opts# V1 版本开始支持链式调用bar (Bar().add_xaxis([衬衫, 毛衣, 领带, 裤子, 风衣, 高跟鞋, 袜子]).add_yaxis(商家A, [114, 55, 27, 101, 125, 27, 105]).add_yaxis(商家B, [57, 134, 137, 129, 145, 60, 49]).set_global_opts(title_optsopts.TitleOpts(title某商场销售情况)))bar.render()image.png2.Pie饼状图from pyecharts import options as optsfrom pyecharts.charts import Piefrom pyecharts.faker import Fakerpie (Pie().add(, [list(z) for z in zip(Faker.choose(), Faker.values())]).set_colors([blue, green, yellow, red, pink, orange, purple]).set_global_opts(title_optsopts.TitleOpts(titlePie-设置颜色)).set_series_opts(label_optsopts.LabelOpts(formatter{b}: {c})))pie.render()image.png4. 仪表盘from pyecharts import options as optsfrom pyecharts.charts import Gaugeg (Gauge().add(, [(完成率, 99.6)]).set_global_opts(title_optsopts.TitleOpts(titleGauge-基本示例)))g.render()image.png5.折线图import pyecharts.options as optsfrom pyecharts.charts import Linefrom pyecharts.faker import Fakerc (Line().add_xaxis(Faker.choose()).add_yaxis(商家A, Faker.values(), is_smoothTrue).add_yaxis(商家B, Faker.values(), is_smoothTrue).set_global_opts(title_optsopts.TitleOpts(titleLine-smooth)))c.render()image.png6.K线图from pyecharts import options as optsfrom pyecharts.charts import Klinedata [[2320.26, 2320.26, 2287.3, 2362.94],[2300, 2291.3, 2288.26, 2308.38],[2295.35, 2346.5, 2295.35, 2345.92],[2347.22, 2358.98, 2337.35, 2363.8],[2360.75, 2382.48, 2347.89, 2383.76],[2383.43, 2385.42, 2371.23, 2391.82],[2377.41, 2419.02, 2369.57, 2421.15],[2425.92, 2428.15, 2417.58, 2440.38],[2411, 2433.13, 2403.3, 2437.42],[2432.68, 2334.48, 2427.7, 2441.73],[2430.69, 2418.53, 2394.22, 2433.89],[2416.62, 2432.4, 2414.4, 2443.03],[2441.91, 2421.56, 2418.43, 2444.8],[2420.26, 2382.91, 2373.53, 2427.07],[2383.49, 2397.18, 2370.61, 2397.94],[2378.82, 2325.95, 2309.17, 2378.82],[2322.94, 2314.16, 2308.76, 2330.88],[2320.62, 2325.82, 2315.01, 2338.78],[2313.74, 2293.34, 2289.89, 2340.71],[2297.77, 2313.22, 2292.03, 2324.63],[2322.32, 2365.59, 2308.92, 2366.16],[2364.54, 2359.51, 2330.86, 2369.65],[2332.08, 2273.4, 2259.25, 2333.54],[2274.81, 2326.31, 2270.1, 2328.14],[2333.61, 2347.18, 2321.6, 2351.44],[2340.44, 2324.29, 2304.27, 2352.02],[2326.42, 2318.61, 2314.59, 2333.67],[2314.68, 2310.59, 2296.58, 2320.96],[2309.16, 2286.6, 2264.83, 2333.29],[2282.17, 2263.97, 2253.25, 2286.33],[2255.77, 2270.28, 2253.31, 2276.22],]k (Kline().add_xaxis([2017/7/{}.format(i 1) for i in range(31)]).add_yaxis(k线图, data).set_global_opts(yaxis_optsopts.AxisOpts(is_scaleTrue),xaxis_optsopts.AxisOpts(is_scaleTrue),title_optsopts.TitleOpts(titleK线图-基本示例),))k.render()image.png7.地图from pyecharts import options as optsfrom pyecharts.charts import Mapfrom pyecharts.faker import Fakermap (Map().add(中国地图, [list(z) for z in zip(Faker.provinces, Faker.values())], china).set_global_opts(title_optsopts.TitleOpts(titleMap-基本示例)))map.render()image.png
