1 from pyecharts import pie, bar, gauge, effectscatter, wordcloud, map, grid, line, timeline 2 import random
make_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
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')
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')
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())
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')
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')
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')
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')
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')
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')