导入类库
1 from pyecharts import Pie, Bar, Gauge, EffectScatter, WordCloud, Map, Grid, Line, Timeline
2 import randommake_point：标注，类似于matplotlib的text
is_stack：堆叠，将同一图表中的不同图像堆叠显示
is_label_show：显示每个数据的标注
is_datazoom_show：数据缩放显示
地图
1 value = [120, 110]
2 attr = [u'河南', u'浙江']
3 map = Map(u'Map 结合 VisualMap 示例', width=1200, height=600)
4 map.use_theme('dark')
5 map.add('', attr, value, maptype=u'china', is_visualmap=True, visual_text_color='#000')
6 map.render('map.html')堆叠柱状图
1 attr = ['衬衫', '羊毛衫', '雪纺衫', '裤子', '高跟鞋', '袜子']
2 v1 = [5, 20, 36, 10, 75, 90]
3 v2 = [10, 25, 8, 60, 20, 80]
4 bar = Bar('柱状图数据堆叠示例')
5 bar.add('商家A', attr, v1, mark_point=['average'], is_stack=True)
6 bar.add('商家B', attr, v2, mark_point=['min', 'max'], is_stack=True)
7 bar.render('bar.html')收缩柱状图
1 attr = ['{}天'.format(i) for i in range(30)]
2 v1 = [random.randint(1, 30) for _ in range(30)]
3 bar = Bar('Bar - datazoom - slider示例')
4 bar.use_theme('dark')
5 bar.add('', attr, v1, is_label_show=True, is_datazoom_show=True, is_more_utils=True)
6 bar.render('bar_slider.html')
7 # 上面可以通过下面一句链式调用
8 # (Bar().add().add().render())仪表盘
1 gauge = Gauge('仪表盘示例')
2 gauge.add('业务指标', '完成率', 66.66)
3 gauge.render('gauge.html')散点图
1 v1 = [10, 20, 30, 40, 50, 60]
2 v2 = [25, 20, 15, 10, 60, 33]
3 es = EffectScatter('动态散点图示例')
4 es.add('effectScatter', v1, v2)
5 es.render('effectScatter.html')词云
1 name = [u'网络', u'数据分析.txt', u'hadoop', u'flask']
2 value = [10000, 6000, 4000, 3000]
3 wd = WordCloud(width=1300, height=620)
4 wd.add('', name, value, word_size_range=(20, 100))
5 wd.render('wordcloud.html')饼图
1 attr = ['衬衫', '羊毛衫', '雪纺衫', '裤子', '高 跟鞋', '袜子']
2 v1 = [11, 12, 13, 10, 10, 10]
3 pie = Pie('饼图示例')
4 # pie.use_theme('dark')
5 pie.add('服装', attr, v1, is_label_show=True)
6 pie.render('pie.html')网格容器
1 attr = ['衬衫', '羊毛衫', '雪纺衫', '裤子', '高 跟鞋', '袜子']
2 v1 = [5, 20, 36, 10, 75, 90]
3 v2 = [10, 25, 8, 60, 20, 80]
4 bar = Bar('柱状图示例', height=720)
5 bar.add('商家A', attr, v1, is_stack=True)
6 bar.add('商家B', attr, v2, is_stack=True)
7 line = Line('折线图示例', title_top='50%')
8 attr = ['周一', '周二', '周三', '周四', '周五', '周六', '周日']
9 line.add('最高气温',
10 attr,
11 [11, 11, 15, 13, 12, 13, 10],
12 mark_point=['max', 'min'],
13 mark_line=['average'],
14 )
15 line.add('最低气温',
16 attr,
17 [1, -2, 2, 5, 3, 2, 0],
18 mark_point=['max', 'min'],
19 mark_line=['average'],
20 legend_top='50%'
21 )
22 grid = Grid()
23 grid.add(bar, grid_bottom='60%')
24 grid.add(line, grid_top='60%')
25 grid.render('grid.html')时间线
1 attr = ["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"]
2 pie_1 = Pie("2012 年销量比例", "数据纯属虚构")
3 pie_1.add("秋季", attr, [random.randint(10, 100) for _ in range(6)],
4 is_label_show=True, radius=[30, 55], rosetype='radius')
5
6 pie_2 = Pie("2013 年销量比例", "数据纯属虚构")
7 pie_2.add("秋季", attr, [random.randint(10, 100) for _ in range(6)],
8 is_label_show=True, radius=[30, 55], rosetype='radius')
9
10 pie_3 = Pie("2014 年销量比例", "数据纯属虚构")
11 pie_3.add("秋季", attr, [random.randint(10, 100) for _ in range(6)],
12 is_label_show=True, radius=[30, 55], rosetype='radius')
13
14 pie_4 = Pie("2015 年销量比例", "数据纯属虚构")
15 pie_4.add("秋季", attr, [random.randint(10, 100) for _ in range(6)],
16 is_label_show=True, radius=[30, 55], rosetype='radius')
17
18 pie_5 = Pie("2016 年销量比例", "数据纯属虚构")
19 pie_5.add("秋季", attr, [random.randint(10, 100) for _ in range(6)],
20 is_label_show=True, radius=[30, 55], rosetype='radius')
21
22 timeline = Timeline(is_auto_play=True, timeline_bottom=0)
23 timeline.use_theme('dark')
24 timeline.add(pie_1, '2012 年')
25 timeline.add(pie_2, '2013 年')
26 timeline.add(pie_3, '2014 年')
27 timeline.add(pie_4, '2015 年')
28 timeline.add(pie_5, '2016 年')
29 timeline.render('timeline.html')
