xxx
6 months ago
parent
d0e4d0b7c9
commit
b85c2c8609
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<!DOCTYPE html>
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<html>
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<head>
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<meta charset="UTF-8">
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<title>Awesome-pyecharts</title>
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<script type="text/javascript" src="https://assets.pyecharts.org/assets/echarts.min.js"></script>
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<script type="text/javascript" src="https://assets.pyecharts.org/assets/themes/infographic.js"></script>
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</head>
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<body>
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<div id="cf9171b428624c54bc4aff53cf3f918d" class="chart-container" style="width:900px; height:500px;"></div>
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<script>
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var chart_cf9171b428624c54bc4aff53cf3f918d = echarts.init(
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document.getElementById('cf9171b428624c54bc4aff53cf3f918d'), 'infographic', {renderer: 'canvas'});
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var option_cf9171b428624c54bc4aff53cf3f918d = {
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"animation": true,
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"animationThreshold": 2000,
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"animationDuration": 1000,
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"animationEasing": "cubicOut",
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"animationDelay": 0,
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"animationDurationUpdate": 300,
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"animationEasingUpdate": "cubicOut",
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"animationDelayUpdate": 0,
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"series": [
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{
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"type": "pie",
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"name": "\u516c\u53f8\u7c7b\u578b\u73af\u5f62\u56fe",
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"clockwise": true,
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"data": [
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{
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"name": "\u4e0a\u5e02\u516c\u53f8",
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"value": 192
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},
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{
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"name": "\u4e8b\u4e1a\u5355\u4f4d",
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"value": 2
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},
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{
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"name": "\u5176\u5b83",
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"value": 71
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},
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{
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"name": "\u5408\u8d44",
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"value": 39
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},
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{
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"name": "\u56fd\u4f01",
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"value": 80
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},
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{
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"name": "\u5916\u5546\u72ec\u8d44",
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"value": 289
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},
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{
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"name": "\u6c11\u8425",
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"value": 714
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},
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{
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"name": "\u6e2f\u6fb3\u53f0\u516c\u53f8",
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"value": 4
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},
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{
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"name": "\u80a1\u4efd\u5236\u4f01\u4e1a",
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"value": 132
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}
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],
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"radius": [
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"20%",
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"40%"
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],
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"center": [
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"50%",
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"40%"
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],
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"label": {
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"show": true,
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"position": "top",
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"margin": 8,
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"formatter": "{b}:{d}%"
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}
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}
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],
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"legend": [
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{
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"data": [
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"\u4e0a\u5e02\u516c\u53f8",
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"\u4e8b\u4e1a\u5355\u4f4d",
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"\u5176\u5b83",
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"\u5408\u8d44",
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"\u56fd\u4f01",
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"\u5916\u5546\u72ec\u8d44",
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"\u6c11\u8425",
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"\u6e2f\u6fb3\u53f0\u516c\u53f8",
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"\u80a1\u4efd\u5236\u4f01\u4e1a"
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],
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"selected": {},
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"show": true,
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"left": "15%",
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"top": "15%",
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"orient": "vertical",
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"padding": 5,
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"itemGap": 10,
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"itemWidth": 25,
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"itemHeight": 14
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}
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],
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"tooltip": {
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"show": true,
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"trigger": "item",
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"triggerOn": "mousemove|click",
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"axisPointer": {
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"type": "line"
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},
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"showContent": true,
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"alwaysShowContent": false,
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"showDelay": 0,
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"hideDelay": 100,
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"textStyle": {
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"fontSize": 14
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},
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"borderWidth": 0,
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"padding": 5
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},
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"title": [
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{
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"text": "\u516c\u53f8\u7c7b\u578b",
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"left": "35%",
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"top": "3%",
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"padding": 5,
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"itemGap": 10,
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"textStyle": {
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"fontSize": 25
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}
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}
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]
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};
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chart_cf9171b428624c54bc4aff53cf3f918d.setOption(option_cf9171b428624c54bc4aff53cf3f918d);
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</script>
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</body>
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</html>
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@ -0,0 +1,31 @@
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import pandas as pd
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from pyecharts.charts import Pie
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from pyecharts import options as opts
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from pyecharts.globals import ThemeType
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data = [
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["上市公司", 192],
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["事业单位", 2],
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[ "其它", 71],
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[ "合资", 39],
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[ "国企", 80],
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[ "外商独资", 289],
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[ "民营", 714],
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[ "港澳台公司", 4],
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[ "股份制企业", 132]
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]
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pie=Pie(init_opts=opts.InitOpts(theme=ThemeType.INFOGRAPHIC))\
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.add("公司类型环形图",
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data,
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radius=["20%","40%"],
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center=['50%','40%'],
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label_opts=opts.LabelOpts(formatter='{b}:{d}%')
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)\
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.set_global_opts(
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title_opts=opts.TitleOpts('公司类型',pos_left="35%",pos_top="3%",
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title_textstyle_opts=opts.TextStyleOpts(font_size=25)),
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legend_opts=opts.LegendOpts(orient="vertical",pos_left='15%',pos_top='15%')
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)
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pie.render("公司类型环形图.html")
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@ -0,0 +1,42 @@
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import matplotlib.pyplot as plt
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import pandas as pd
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# 解决中文乱码
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plt.rcParams['font.sans-serif'] = ['SimHei']
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# 创建画布
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plt.figure()
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data=pd.read_csv("最新数据.csv")
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# 将城市这一列数据提取出来
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city = data[["城市",'职位名称']]
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# 将城市列去重后转化为列表变成x轴数据
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x_data = data['城市'].drop_duplicates().tolist()
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x_data=x_data[:10]
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# print(x_data)
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# 将城市进行分组计数变为y轴数据
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y_data = city.groupby('城市').count().reset_index()
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y_data = y_data['职位名称'].tolist()
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y_data.sort(reverse=True)
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y_data=y_data[:10]
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plt.bar(x_data, y_data,
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width=0.5,
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color='#9fe080',
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align="center",
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)
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# 显示数据标签
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for a,b in zip(x_data,y_data):
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plt.text(
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a, #标签的x坐标
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b, #标签的y坐标
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b, #标签的内容
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ha='center',
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va='bottom',
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fontsize=10)
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plt.title("就业机会前十的城市")
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plt.xlabel("城市")
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plt.show()
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