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超详细Pyecharts 1.x 教程,让你的图表动起来~
作者:木木小宇宙
来源:Python数据分析实战与AI干货
大家好,我是朱小五
今天交流群有同学问Pyecharts1.x版本的使用方法,小五正好分享一篇,是对这个库新版本的系统讲解,值得细看!
当然详细版最好还是看文档
文档:https://pyecharts.org/#/
示例:https://gallery.pyecharts.org/
01 前言
Pyecharts在1.x版本之后迎来重大更新,与老版本(0.5X)已是两个完全不同的版本,所以很多小伙伴在使用Pyecharts出现了类似'pyecharts' has no attribute 'xxx'
的报错,那是因为你安装了1.x的版本却使用了0.5x的调用方法。
当然如果你更习惯使用0.5X版本的可以通过如下语句来进行安装:pip install pyecharts==0.5.11
安装1.x版本(仅支持Python 3.6+):pip install pyecharts
本文将会介绍Pyecharts1.x版本的使用方法,本文所有语句均基于v1.6.2
,通过以下语句查询使用pyecharts版本:
import pyecharts
print(pyecharts.__version__)
02 基本使用
链式调用
pyecharts在v1.x之后支持链式调用,具体语句如下:
from pyecharts.charts import Bar
from pyecharts import options as opts
# 示例数据
cate = ['Apple', 'Huawei', 'Xiaomi', 'Oppo', 'Vivo', 'Meizu']
data1 = [123, 153, 89, 107, 98, 23]
data2 = [56, 77, 93, 68, 45, 67]
# 1.x版本支持链式调用
bar = (Bar()
.add_xaxis(cate)
.add_yaxis('电商渠道', data1)
.add_yaxis('门店', data2)
.set_global_opts(title_opts=opts.TitleOpts(title="Bar-基本示例", subtitle="我是副标题"))
)
bar.render_notebook()
注:其实这运行结果都是动态的,这里只放上截图,可在自己电脑上Jupyter 中运
行查看!
全局配置
可以通过全局配置(.set_global_opts():
)控制以下区域
系列配置
可以通过系列配置(.set_global_opts():
)控制图表中的文本,线样式,标记等.
"""
系列配置项使用示例:
1. 不显示数值
2. 标记每个系列的最大值
"""
bar = (Bar()
.add_xaxis(cate)
.add_yaxis('电商渠道', data1)
.add_yaxis('门店', data2)
.set_series_opts(label_opts=opts.LabelOpts(is_show=False),
markpoint_opts=opts.MarkPointOpts(data=[opts.MarkPointItem(type_="max", name="最大值"),]))
.set_global_opts(title_opts=opts.TitleOpts(title="Bar-基本示例", subtitle="我是副标题"))
)
bar.render_notebook()
03 饼图
from pyecharts.charts import Pie
from pyecharts import options as opts
# 示例数据
cate = ['Apple', 'Huawei', 'Xiaomi', 'Oppo', 'Vivo', 'Meizu']
data = [153, 124, 107, 99, 89, 46]
pie = (Pie()
.add('', [list(z) for z in zip(cate, data)],
radius=["30%", "75%"],
rosetype="radius")
.set_global_opts(title_opts=opts.TitleOpts(title="Pie-基本示例", subtitle="我是副标题"))
.set_series_opts(label_opts=opts.LabelOpts(formatter="{b}: {d}%"))
)
pie.render_notebook()
04 折线图
from pyecharts.charts import Line
from pyecharts import options as opts
# 示例数据
cate = ['Apple', 'Huawei', 'Xiaomi', 'Oppo', 'Vivo', 'Meizu']
data1 = [123, 153, 89, 107, 98, 23]
data2 = [56, 77, 93, 68, 45, 67]
"""
折线图示例:
1. is_smooth 折线 OR 平滑
2. markline_opts 标记线 OR 标记点
"""
line = (Line()
.add_xaxis(cate)
.add_yaxis('电商渠道', data1,
markline_opts=opts.MarkLineOpts(data=[opts.MarkLineItem(type_="average")]))
.add_yaxis('门店', data2,
is_smooth=True,
markpoint_opts=opts.MarkPointOpts(data=[opts.MarkPointItem(name="自定义标记点",
coord=[cate[2], data2[2]], value=data2[2])]))
.set_global_opts(title_opts=opts.TitleOpts(title="Line-基本示例", subtitle="我是副标题"))
)
line.render_notebook()
05 漏斗图
from pyecharts.charts import Funnel
from pyecharts import options as opts
# 示例数据
cate = ['访问', '注册', '加入购物车', '提交订单', '付款成功']
data = [30398, 15230, 10045, 8109, 5698]
"""
漏斗图示例:
1. sort_控制排序,默认降序;
2. 标签显示位置
"""
funnel = (Funnel()
.add("用户数", [list(z) for z in zip(cate, data)],
sort_='ascending',
label_opts=opts.LabelOpts(position="inside"))
.set_global_opts(title_opts=opts.TitleOpts(title="Funnel-基本示例", subtitle="我是副标题"))
)
funnel.render_notebook()
06 热力图
from pyecharts.charts import HeatMap
from pyecharts import options as opts
from pyecharts.faker import Faker
import random
# 示例数据
data = [[i, j, random.randint(0, 50)] for i in range(24) for j in range(7)]
heat = (HeatMap()
.add_xaxis(Faker.clock)
.add_yaxis("访客数",
Faker.week,
data,
label_opts=opts.LabelOpts(is_show=True, position="inside"))
.set_global_opts(
title_opts=opts.TitleOpts(title="HeatMap-基本示例", subtitle="我是副标题"),
visualmap_opts=opts.VisualMapOpts(),
legend_opts=opts.LegendOpts(is_show=False))
)
heat.render_notebook()
07 地理图
16
17_map.render_notebook()
08 地理热点图
from pyecharts import options as opts
from pyecharts.charts import Map
import random
province = ['广东', '湖北', '湖南', '四川', '重庆', '黑龙江', '浙江', '山西', '河北', '安徽', '河南', '山东', '西藏']
data = [(i, random.randint(50, 150)) for i in province]
_map = (
Map()
.add("销售额", data, "china")
.set_global_opts(
title_opts=opts.TitleOpts(title="Map-基本示例"),
legend_opts=opts.LegendOpts(is_show=False),
visualmap_opts=opts.VisualMapOpts(max_=200, is_piecewise=True),
)
)
_map.render_notebook()
09 组合图标
from pyecharts import options as opts
from pyecharts.charts import Map, Bar, Grid
from pyecharts.globals import ChartType, ThemeType
import random
province = ['武汉', '十堰', '鄂州', '宜昌', '荆州', '孝感', '黄石', '咸宁', '仙桃']
data = [324, 125, 145, 216, 241, 244, 156, 278, 169]
bar = (Bar()
.add_xaxis(province)
.add_yaxis('营业额', data)
.set_series_opts(label_opts=opts.LabelOpts(is_show=False))
.set_global_opts(
title_opts=opts.TitleOpts(title="Grid-Bar")
)
)
line = (Line()
.add_xaxis(province)
.add_yaxis('营业额', data,
markline_opts=opts.MarkLineOpts(data=[opts.MarkLineItem(type_="average")]))
.set_global_opts(title_opts=opts.TitleOpts(title="Grid-Line", pos_top="48%"))
)
grid = (
Grid()
.add(bar, grid_opts=opts.GridOpts(pos_bottom="60%"))
.add(line, grid_opts=opts.GridOpts(pos_top="60%"))
)
grid.render_notebook()
10 主题设置
from pyecharts import options as opts
from pyecharts.charts import Bar
from pyecharts.globals import ThemeType
# 示例数据
cate = ['Apple', 'Huawei', 'Xiaomi', 'Oppo', 'Vivo', 'Meizu']
data1 = [123, 153, 89, 107, 98, 23]
data2 = [56, 77, 93, 68, 45, 67]
"""
主题设置:
默认white
"""
bar = (Bar(init_opts=opts.InitOpts(theme=ThemeType.ROMANTIC))
.add_xaxis(cate)
.add_yaxis('电商渠道', data1)
.add_yaxis('门店', data2)
.set_series_opts(label_opts=opts.LabelOpts(is_show=False),
markpoint_opts=opts.MarkPointOpts(data=[opts.MarkPointItem(type_="max", name="最大值"),]))
.set_global_opts(title_opts=opts.TitleOpts(title="Theme-ROMANTIC"))
)
bar.render_notebook()
11 时间轴
from pyecharts import options as opts
from pyecharts.charts import Bar, Timeline
from pyecharts.globals import ThemeType
# 示例数据
cate = ['Apple', 'Huawei', 'Xiaomi', 'Oppo', 'Vivo', 'Meizu']
tl = Timeline()
for i in range(2015, 2020):
bar = (
Bar()
.add_xaxis(cate)
.add_yaxis("线上", [random.randint(50, 150) for _ in cate])
.add_yaxis("门店", [random.randint(100, 200) for _ in cate])
.set_global_opts(title_opts=opts.TitleOpts("手机品牌{}年营业额".format(i)))
)
tl.add(bar, "{}年".format(i))
tl.render_notebook()
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