pyecharts 兼容 Python2 和 Python3。目前版本为 0.1.2
pip install pyecharts
首先开始来绘制你的第一个图表
from pyecharts import Bar bar = Bar("我的第一个图表", "这里是副标题") bar.add("服装", ["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"], [5, 20, 36, 10, 75, 90]) bar.show_config() bar.render()
Tip： 可以按右边的下载按钮将图片下载到本地
add() show_config() render() 基本上所有的图表类型都是这样绘制的：
chart_name = Type() 初始化具体类型图表。add() 添加数据及配置项。render() 生成 .html 文件。from pyecharts import Bar bar = Bar("标记线和标记点示例") bar.add("商家A", attr, v1, mark_point=["average"]) bar.add("商家B", attr, v2, mark_line=["min", "max"]) bar.render()
from pyecharts import Bar bar = Bar("x 轴和 y 轴交换") bar.add("商家A", attr, v1) bar.add("商家B", attr, v2, is_convert=True) bar.render()
from pyecharts import EffectScatter v1 = [10, 20, 30, 40, 50, 60] v2 = [25, 20, 15, 10, 60, 33] es = EffectScatter("动态散点图示例") es.add("effectScatter", v1, v2) es.render()
es = EffectScatter("动态散点图各种图形示例") es.add("", [10], [10], symbol_size=20, effect_scale=3.5, effect_period=3, symbol="pin") es.add("", [20], [20], symbol_size=12, effect_scale=4.5, effect_period=4,symbol="rect") es.add("", [30], [30], symbol_size=30, effect_scale=5.5, effect_period=5,symbol="roundRect") es.add("", [40], [40], symbol_size=10, effect_scale=6.5, effect_brushtype=‘fill‘,symbol="diamond") es.add("", [50], [50], symbol_size=16, effect_scale=5.5, effect_period=3,symbol="arrow") es.add("", [60], [60], symbol_size=6, effect_scale=2.5, effect_period=3,symbol="triangle") es.render()
from pyecharts import Funnel attr = ["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"] value = [20, 40, 60, 80, 100, 120] funnel = Funnel("漏斗图示例") funnel.add("商品", attr, value, is_label_show=True, label_pos="inside", label_text_color="#fff") funnel.render()
from pyecharts import Gauge gauge = Gauge("仪表盘示例") gauge.add("业务指标", "完成率", 66.66) gauge.show_config() gauge.render()
from pyecharts import Geo data = [ ("海门", 9),("鄂尔多斯", 12),("招远", 12),("舟山", 12),("齐齐哈尔", 14),("盐城", 15), ("赤峰", 16),("青岛", 18),("乳山", 18),("金昌", 19),("泉州", 21),("莱西", 21), ("日照", 21),("胶南", 22),("南通", 23),("拉萨", 24),("云浮", 24),("梅州", 25)...] geo = Geo("全国主要城市空气质量", "data from pm2.5", title_color="#fff", title_pos="center", width=1200, height=600, background_color=‘#404a59‘) attr, value = geo.cast(data) geo.add("", attr, value, visual_range=[0, 200], visual_text_color="#fff", symbol_size=15, is_visualmap=True) geo.show_config() geo.render()
from pyecharts import Geo data = [("海门", 9), ("鄂尔多斯", 12), ("招远", 12), ("舟山", 12), ("齐齐哈尔", 14), ("盐城", 15)] geo = Geo("全国主要城市空气质量", "data from pm2.5", title_color="#fff", title_pos="center", width=1200, height=600, background_color=‘#404a59‘) attr, value = geo.cast(data) geo.add("", attr, value, type="effectScatter", is_random=True, effect_scale=5) geo.show_config() geo.render()
from pyecharts import Graph nodes = [{"name": "结点1", "symbolSize": 10}, {"name": "结点2", "symbolSize": 20}, {"name": "结点3", "symbolSize": 30}, {"name": "结点4", "symbolSize": 40}, {"name": "结点5", "symbolSize": 50}, {"name": "结点6", "symbolSize": 40}, {"name": "结点7", "symbolSize": 30}, {"name": "结点8", "symbolSize": 20}] links = [] for i in nodes: for j in nodes: links.append({"source": i.get(‘name‘), "target": j.get(‘name‘)}) graph = Graph("关系图-环形布局示例") graph.add("", nodes, links, is_label_show=True, repulsion=8000, layout=‘circular‘, label_text_color=None) graph.show_config() graph.render()
from pyecharts import Graph import json with open("..\json\weibo.json", "r", encoding="utf-8") as f: j = json.load(f) nodes, links, categories, cont, mid, userl = j graph = Graph("微博转发关系图", width=1200, height=600) graph.add("", nodes, links, categories, label_pos="right", repulsion=50, is_legend_show=False, line_curve=0.2, label_text_color=None) graph.show_config() graph.render()
from pyecharts import Line attr = ["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"] v1 = [5, 20, 36, 10, 10, 100] v2 = [55, 60, 16, 20, 15, 80] line = Line("折线图示例") line.add("商家A", attr, v1, mark_point=["average"]) line.add("商家B", attr, v2, is_smooth=True, mark_line=["max", "average"]) line.show_config() line.render()
line = Line("折线图-阶梯图示例") line.add("商家A", attr, v1, is_step=True, is_label_show=True) line.show_config() line.render()
line = Line("折线图-面积图示例") line.add("商家A", attr, v1, is_fill=True, line_opacity=0.2, area_opacity=0.4, symbol=None) line.add("商家B", attr, v2, is_fill=True, area_color=‘#000‘, area_opacity=0.3, is_smooth=True) line.show_config() line.render()
from pyecharts import Liquid liquid = Liquid("水球图示例") liquid.add("Liquid", [0.6]) liquid.show_config() liquid.render()
from pyecharts import Liquid liquid = Liquid("水球图示例") liquid.add("Liquid", [0.6, 0.5, 0.4, 0.3], is_liquid_animation=False, shape=‘diamond‘) liquid.show_config() liquid.render()
from pyecharts import Map value = [20, 190, 253, 77, 65] attr = [‘汕头市‘, ‘汕尾市‘, ‘揭阳市‘, ‘阳江市‘, ‘肇庆市‘] map = Map("广东地图示例", width=1200, height=600) map.add("", attr, value, maptype=‘广东‘, is_visualmap=True, visual_text_color=‘#000‘) map.show_config() map.render()
from pyecharts import Parallel c_schema = [ {"dim": 0, "name": "data"}, {"dim": 1, "name": "AQI"}, {"dim": 2, "name": "PM2.5"}, {"dim": 3, "name": "PM10"}, {"dim": 4, "name": "CO"}, {"dim": 5, "name": "NO2"}, {"dim": 6, "name": "CO2"}, {"dim": 7, "name": "等级", "type": "category", "data": [‘优‘, ‘良‘, ‘轻度污染‘, ‘中度污染‘, ‘重度污染‘, ‘严重污染‘]} ] data = [ [1, 91, 45, 125, 0.82, 34, 23, "良"], [2, 65, 27, 78, 0.86, 45, 29, "良"], [3, 83, 60, 84, 1.09, 73, 27, "良"], [4, 109, 81, 121, 1.28, 68, 51, "轻度污染"], [5, 106, 77, 114, 1.07, 55, 51, "轻度污染"], [6, 109, 81, 121, 1.28, 68, 51, "轻度污染"], [7, 106, 77, 114, 1.07, 55, 51, "轻度污染"], [8, 89, 65, 78, 0.86, 51, 26, "良"], [9, 53, 33, 47, 0.64, 50, 17, "良"], [10, 80, 55, 80, 1.01, 75, 24, "良"], [11, 117, 81, 124, 1.03, 45, 24, "轻度污染"], [12, 99, 71, 142, 1.1, 62, 42, "良"], [13, 95, 69, 130, 1.28, 74, 50, "良"], [14, 116, 87, 131, 1.47, 84, 40, "轻度污染"] ] parallel = Parallel("平行坐标系-用户自定义指示器") parallel.config(c_schema=c_schema) parallel.add("parallel", data) parallel.show_config() parallel.render()
from pyecharts import Pie attr = ["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"] v1 = [11, 12, 13, 10, 10, 10] pie = Pie("饼图示例") pie.add("", attr, v1, is_label_show=True) pie.show_config() pie.render()
from pyecharts import Pie attr = ["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"] v1 = [11, 12, 13, 10, 10, 10] v2 = [19, 21, 32, 20, 20, 33] pie = Pie("饼图-玫瑰图示例", title_pos=‘center‘, width=900) pie.add("商品A", attr, v1, center=[25, 50], is_random=True, radius=[30, 75], rosetype=‘radius‘) pie.add("商品B", attr, v2, center=[75, 50], is_random=True, radius=[30, 75], rosetype=‘area‘, is_legend_show=False, is_label_show=True) pie.show_config() pie.render()
from pyecharts import Polar radius = [‘周一‘, ‘周二‘, ‘周三‘, ‘周四‘, ‘周五‘, ‘周六‘, ‘周日‘] polar = Polar("极坐标系-堆叠柱状图示例", width=1200, height=600) polar.add("A", [1, 2, 3, 4, 3, 5, 1], radius_data=radius, type=‘barRadius‘, is_stack=True) polar.add("B", [2, 4, 6, 1, 2, 3, 1], radius_data=radius, type=‘barRadius‘, is_stack=True) polar.add("C", [1, 2, 3, 4, 1, 2, 5], radius_data=radius, type=‘barRadius‘, is_stack=True) polar.show_config() polar.render()
from pyecharts import Polar radius = [‘周一‘, ‘周二‘, ‘周三‘, ‘周四‘, ‘周五‘, ‘周六‘, ‘周日‘] polar = Polar("极坐标系-堆叠柱状图示例", width=1200, height=600) polar.add("", [1, 2, 3, 4, 3, 5, 1], radius_data=radius, type=‘barAngle‘, is_stack=True) polar.add("", [2, 4, 6, 1, 2, 3, 1], radius_data=radius, type=‘barAngle‘, is_stack=True) polar.add("", [1, 2, 3, 4, 1, 2, 5], radius_data=radius, type=‘barAngle‘, is_stack=True) polar.show_config() polar.render()
from pyecharts import Radar schema = [ ("销售", 6500), ("管理", 16000), ("信息技术", 30000), ("客服", 38000), ("研发", 52000), ("市场", 25000)] v1 = [[4300, 10000, 28000, 35000, 50000, 19000]] v2 = [[5000, 14000, 28000, 31000, 42000, 21000]] radar = Radar() radar.config(schema) radar.add("预算分配", v1, is_splitline=True, is_axisline_show=True) radar.add("实际开销", v2, label_color=["#4e79a7"], is_area_show=False) radar.show_config() radar.render()
value_bj = [ [55, 9, 56, 0.46, 18, 6, 1], [25, 11, 21, 0.65, 34, 9, 2], [56, 7, 63, 0.3, 14, 5, 3], [33, 7, 29, 0.33, 16, 6, 4]...] value_sh = [ [91, 45, 125, 0.82, 34, 23, 1], [65, 27, 78, 0.86, 45, 29, 2], [83, 60, 84, 1.09, 73, 27, 3], [109, 81, 121, 1.28, 68, 51, 4]...] c_schema= [{"name": "AQI", "max": 300, "min": 5}, {"name": "PM2.5", "max": 250, "min": 20}, {"name": "PM10", "max": 300, "min": 5}, {"name": "CO", "max": 5}, {"name": "NO2", "max": 200}, {"name": "SO2", "max": 100}] radar = Radar() radar.config(c_schema=c_schema, shape=‘circle‘) radar.add("北京", value_bj, item_color="#f9713c", symbol=None) radar.add("上海", value_sh, item_color="#b3e4a1", symbol=None) radar.show_config() radar.render()
from pyecharts import Scatter v1 = [10, 20, 30, 40, 50, 60] v2 = [10, 20, 30, 40, 50, 60] scatter = Scatter("散点图示例") scatter.add("A", v1, v2) scatter.add("B", v1[::-1], v2) scatter.show_config() scatter.render()
from pyecharts import Scatter scatter = Scatter("散点图示例") v1, v2 = scatter.draw("../images/pyecharts-0.png") scatter.add("pyecharts", v1, v2, is_random=True) scatter.show_config() scatter.render()
from pyecharts import WordCloud name = [‘Sam S Club‘, ‘Macys‘, ‘Amy Schumer‘, ‘Jurassic World‘, ‘Charter Communications‘, ‘Chick Fil A‘, ‘Planet Fitness‘, ‘Pitch Perfect‘, ‘Express‘, ‘Home‘, ‘Johnny Depp‘, ‘Lena Dunham‘, ‘Lewis Hamilton‘, ‘KXAN‘, ‘Mary Ellen Mark‘, ‘Farrah Abraham‘, ‘Rita Ora‘, ‘Serena Williams‘, ‘NCAA baseball tournament‘, ‘Point Break‘] value = [10000, 6181, 4386, 4055, 2467, 2244, 1898, 1484, 1112, 965, 847, 582, 555, 550, 462, 366, 360, 282, 273, 265] wordcloud = WordCloud(width=1300, height=620) wordcloud.add("", name, value, word_size_range=[20, 100]) wordcloud.show_config() wordcloud.render()
用户还可以自定义结合 Line/Bar 图表
需使用 get_series() 和 custom() 方法
get_series() """ 获取图表的 series 数据 """ custom(series) ‘‘‘ 追加自定义图表类型 ‘‘‘
先用 get_series() 获取数据，再使用 custom() 将图表结合在一起
from pyecharts import Bar, Line attr = [‘A‘, ‘B‘, ‘C‘, ‘D‘, ‘E‘, ‘F‘] v1 = [10, 20, 30, 40, 50, 60] v2 = [15, 25, 35, 45, 55, 65] v3 = [38, 28, 58, 48, 78, 68] bar = Bar("Line - Bar 示例") bar.add("bar", attr, v1) line = Line() line.add("line", v2, v3) bar.custom(line.get_series()) bar.show_config() bar.render()
用极坐标系画出一个爱心
import math from pyecharts import Polar data = [] for i in range(101): theta = i / 100 * 360 r = 5 * (1 + math.sin(theta / 180 * math.pi)) data.append([r, theta]) hour = [i for i in range(1, 25)] polar = Polar("极坐标系示例", width=1200, height=600) polar.add("Love", data, angle_data=hour, boundary_gap=False,start_angle=0) polar.show_config() polar.render()
用极坐标系画出一朵小花
import math from pyecharts import Polar data = [] for i in range(361): t = i / 180 * math.pi r = math.sin(2 * t) * math.cos(2 * t) data.append([r, i]) polar = Polar("极坐标系示例", width=1200, height=600) polar.add("Flower", data, start_angle=0, symbol=None, axis_range=[0, None]) polar.show_config() polar.render()
还可以给小花涂上颜色
import math from pyecharts import Polar data = [] for i in range(361): t = i / 180 * math.pi r = math.sin(2 * t) * math.cos(2 * t) data.append([r, i]) polar = Polar("极坐标系示例", width=1200, height=600) polar.add("Color-Flower", data, start_angle=0, symbol=None, axis_range=[0, None], area_color="#f71f24", area_opacity=0.6) polar.show_config() polar.render()
用散点图画出一个爱心
from pyecharts import Scatter scatter = Scatter("散点图示例", width=800, height=480) v1 ,v2 = scatter.draw("../images/love.png") scatter.add("Love", v1, v2) scatter.render()
用散点图画出一个火辣的 Bra
from pyecharts import Scatter scatter = Scatter("散点图示例", width=1000, height=480) v1 ,v2 = scatter.draw("../images/cup.png") scatter.add("Cup", v1, v2) scatter.render()
用散点图画出一个性感的 Bra
from pyecharts import Scatter scatter = Scatter("散点图示例", width=1000, height=480) v1 ,v2 = scatter.draw("../images/cup.png") scatter.add("Cup", v1, v2, label_color=["#000"]) scatter.render()
某地最低温和最高气温折线图
from pyecharts import Line attr = [‘周一‘, ‘周二‘, ‘周三‘, ‘周四‘, ‘周五‘, ‘周六‘, ‘周日‘, ] line = Line("折线图示例") line.add("最高气温", attr, [11, 11, 15, 13, 12, 13, 10], mark_point=["max", "min"], mark_line=["average"]) line.add("最低气温", attr, [1, -2, 2, 5, 3, 2, 0], mark_point=["max", "min"], mark_line=["average"], yaxis_formatter="°C") line.show_config() line.render()
饼图嵌套
from pyecharts import Pie pie = Pie("饼图示例", title_pos=‘center‘, width=1000, height=600) pie.add("", [‘A‘, ‘B‘, ‘C‘, ‘D‘, ‘E‘, ‘F‘], [335, 321, 234, 135, 251, 148], radius=[40, 55],is_label_show=True) pie.add("", [‘H‘, ‘I‘, ‘J‘], [335, 679, 204], radius=[0, 30], legend_orient=‘vertical‘, legend_pos=‘left‘) pie.show_config() pie.render()
饼图再嵌套
import random from pyecharts import Pie attr = [‘A‘, ‘B‘, ‘C‘, ‘D‘, ‘E‘, ‘F‘] pie = Pie("饼图示例", width=1000, height=600) pie.add("", attr, [random.randint(0, 100) for _ in range(6)], radius=[50, 55], center=[25, 50],is_random=True) pie.add("", attr, [random.randint(20, 100) for _ in range(6)], radius=[0, 45], center=[25, 50],rosetype=‘area‘) pie.add("", attr, [random.randint(0, 100) for _ in range(6)], radius=[50, 55], center=[65, 50],is_random=True) pie.add("", attr, [random.randint(20, 100) for _ in range(6)], radius=[0, 45], center=[65, 50],rosetype=‘radius‘) pie.show_config() pie.render()
某地的降水量和蒸发量柱状图
from pyecharts import Bar attr = ["{}月".format(i) for i in range(1, 13)] v1 = [2.0, 4.9, 7.0, 23.2, 25.6, 76.7, 135.6, 162.2, 32.6, 20.0, 6.4, 3.3] v2 = [2.6, 5.9, 9.0, 26.4, 28.7, 70.7, 175.6, 182.2, 48.7, 18.8, 6.0, 2.3] bar = Bar("柱状图示例") bar.add("蒸发量", attr, v1, mark_line=["average"], mark_point=["max", "min"]) bar.add("降水量", attr, v2, mark_line=["average"], mark_point=["max", "min"]) bar.show_config() bar.render()
各类电影中"好片"所占的比例
from pyecharts import Pie pie = Pie(‘各类电影中"好片"所占的比例‘, "数据来着豆瓣", title_pos=‘center‘) pie.add("", ["剧情", ""], [25, 75], center=[10, 30], radius=[18, 24], label_pos=‘center‘, is_label_show=True, label_text_color=None, ) pie.add("", ["奇幻", ""], [24, 76], center=[30, 30], radius=[18, 24], label_pos=‘center‘, is_label_show=True, label_text_color=None, legend_pos=‘left‘) pie.add("", ["爱情", ""], [14, 86], center=[50, 30], radius=[18, 24], label_pos=‘center‘, is_label_show=True, label_text_color=None) pie.add("", ["惊悚", ""], [11, 89], center=[70, 30], radius=[18, 24], label_pos=‘center‘, is_label_show=True, label_text_color=None) pie.add("", ["冒险", ""], [27, 73], center=[90, 30], radius=[18, 24], label_pos=‘center‘, is_label_show=True, label_text_color=None) pie.add("", ["动作", ""], [15, 85], center=[10, 70], radius=[18, 24], label_pos=‘center‘, is_label_show=True, label_text_color=None) pie.add("", ["喜剧", ""], [54, 46], center=[30, 70], radius=[18, 24], label_pos=‘center‘, is_label_show=True, label_text_color=None) pie.add("", ["科幻", ""], [26, 74], center=[50, 70], radius=[18, 24], label_pos=‘center‘, is_label_show=True, label_text_color=None) pie.add("", ["悬疑", ""], [25, 75], center=[70, 70], radius=[18, 24], label_pos=‘center‘, is_label_show=True, label_text_color=None) pie.add("", ["犯罪", ""], [28, 72], center=[90, 70], radius=[18, 24], label_pos=‘center‘, is_label_show=True, label_text_color=None, is_legend_show=True, legend_top="center") pie.show_config() pie.render()
用极坐标系画出一个蜗牛壳
import math from pyecharts import Polar data = [] for i in range(5): for j in range(101): theta = j / 100 * 360 alpha = i * 360 + theta r = math.pow(math.e, 0.003 * alpha) data.append([r, theta]) polar = Polar("极坐标系示例") polar.add("", data, symbol_size=0, symbol=‘circle‘, start_angle=-25, is_radiusaxis_show=False, area_color="#f3c5b3", area_opacity=0.5, is_angleaxis_show=False) polar.show_config() polar.render()
原文：https://www.cnblogs.com/Dominic-Ji/p/9925760.html