pyecharts绘制各种图表
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- 1、pyecharts绘制饼图(显示百分比)
- 2、pyecharts绘制柱状图
- 3、pyecharts绘制折线图
- 4、pyecharts绘制柱形折线组合图
- 5、pyecharts绘制散点图
- 6、pyecharts绘制玫瑰图
- 7、pyecharts绘制词云图
- 8、pyecharts绘制雷达图
- 9、pyecharts绘制散点图
- 10、pyecharts绘制嵌套饼图
- 11、pyecharts绘制中国地图
- 12、pyecharts绘制世界地图
1、pyecharts绘制饼图(显示百分比)
from pyecharts import options as opts
from pyecharts.charts import Pie
label=['Mac口红','Tom Ford口红','圣罗兰','纪梵希','花西子','迪奥','阿玛尼','香奈儿']
values = [300,300,300,300,44,300,300,300]
def pie_base():
c = (
Pie()
.add("",[list(z) for z in zip(label,values)])
.set_global_opts(title_opts = opts.TitleOpts(title="口红品牌分析"))
.set_series_opts(label_opts=opts.LabelOpts(formatter="{b}:{c} {d}%"))
)
return c
pie_base().render()
2、pyecharts绘制柱状图
from pyecharts.globals import ThemeType
from pyecharts import options as opts
from pyecharts.charts import Bar
l1=['星期一','星期二','星期三','星期四','星期五','星期七','星期日']
l2=[100,200,300,400,500,400,300]
bar = (
Bar(init_opts=opts.InitOpts(theme=ThemeType.LIGHT))
.add_xaxis(l1)
.add_yaxis("柱状图标签", l2)
.set_global_opts(title_opts=opts.TitleOpts(title="柱状图-基本示例", subtitle="副标题"))
)
bar.render()
3、pyecharts绘制折线图
import pyecharts.options as opts
from pyecharts.charts import Line
x=['星期一','星期二','星期三','星期四','星期五','星期七','星期日']
y1=[100,200,300,400,100,400,300]
y2=[200,300,200,100,200,300,400]
line=(
Line()
.add_xaxis(xaxis_data=x)
.add_yaxis(series_name="y1线",y_axis=y1,symbol="arrow",is_symbol_show=True)
.add_yaxis(series_name="y2线",y_axis=y2)
.set_global_opts(title_opts=opts.TitleOpts(title="Line-双折线图"))
)
line.render()
4、pyecharts绘制柱形折线组合图
from pyecharts import options as opts
from pyecharts.charts import Bar, Grid, Line
x_data = ["{}月".format(i) for i in range(1, 13)]
bar = (
Bar()
.add_xaxis(x_data)
.add_yaxis(
"降雨量",
[2.0, 4.9, 7.0, 23.2, 25.6, 76.7, 135.6, 162.2, 68.6, 22.0, 6.6, 4.3],
yaxis_index=0,
color="#5793f3",
)
.extend_axis(
yaxis=opts.AxisOpts(
name="降雨量",
type_="value",
min_=0,
max_=250,
position="right",
axisline_opts=opts.AxisLineOpts(
linestyle_opts=opts.LineStyleOpts(color="#d14a61")
),
axislabel_opts=opts.LabelOpts(formatter="{value} ml"),
)
)
.extend_axis(
yaxis=opts.AxisOpts(
type_="value",
name="温度",
min_=0,
max_=25,
position="left",
axisline_opts=opts.AxisLineOpts(
linestyle_opts=opts.LineStyleOpts(color="#d14a61")
),
axislabel_opts=opts.LabelOpts(formatter="{value} °C"),
splitline_opts=opts.SplitLineOpts(
is_show=True, linestyle_opts=opts.LineStyleOpts(opacity=1)
),
)
)
.set_global_opts(
yaxis_opts=opts.AxisOpts(
name="降雨量",
min_=0,
max_=250,
position="right",
offset=0,
axisline_opts=opts.AxisLineOpts(
linestyle_opts=opts.LineStyleOpts(color="#5793f3")
),
axislabel_opts=opts.LabelOpts(formatter="{value} ml"),
),
title_opts=opts.TitleOpts(title="Grid-多 Y 轴示例"),
tooltip_opts=opts.TooltipOpts(trigger="axis", axis_pointer_type="cross"),
)
)
line = (
Line()
.add_xaxis(x_data)
.add_yaxis(
"平均温度",
[2.0, 2.2, 3.3, 4.5, 6.3, 10.2, 20.3, 23.4, 23.0, 16.5, 12.0, 6.2],
yaxis_index=2,
color="#675bba",
label_opts=opts.LabelOpts(is_show=False),
)
)
bar.overlap(line)
grid = Grid()
grid.add(bar, opts.GridOpts(pos_left="5%", pos_right="20%"), is_control_axis_index=True)
grid.render()
5、pyecharts绘制散点图
from pyecharts import options as opts
from pyecharts.charts import Scatter
week = ["周一","周二","周三","周四","周五","周六","周日"]
c =Scatter()
c.add_xaxis(week)
c.add_yaxis("商家A",[80,65,46,37,57,68,90])
c.set_global_opts(title_opts=opts.TitleOpts(title="一周的销售额(万元)"))
c.render()
6、pyecharts绘制玫瑰图
from pyecharts import options as opts
from pyecharts.charts import Pie
label=['Mac口红','Tom Ford口红','圣罗兰','纪梵希','花西子']
values = [100,200,250,350,400]
c = (
Pie()
.add(
"",
[list(z) for z in zip(label,values)],
radius=["30%", "75%"],
center=["50%", "50%"],
rosetype="radius",
label_opts=opts.LabelOpts(is_show=False),
)
.set_global_opts(title_opts=opts.TitleOpts(title="标题"))
.set_series_opts(label_opts=opts.LabelOpts(formatter="{b}:{c} {d}%"))
.render("玫瑰图.html")
)
7、pyecharts绘制词云图
from pyecharts import options as opts
from pyecharts.charts import WordCloud
from pyecharts.globals import SymbolType
words = [
("Sam S Club", 10000),
("Macys", 6181),
("Amy Schumer", 4386),
("Jurassic World", 4055),
("Charter Communications", 2467),
("Chick Fil A", 2244),
("Planet Fitness", 1868),
("Pitch Perfect", 1484),
("Express", 1112),
("Home", 865),
("Johnny Depp", 847),
("Lena Dunham", 582),
("Lewis Hamilton", 555),
("KXAN", 550),
("Mary Ellen Mark", 462),
("Farrah Abraham", 366),
("Rita Ora", 360),
("Serena Williams", 282),
("NCAA baseball tournament", 273),
("Point Break", 265),
]
c = (
WordCloud()
.add("", words, word_size_range=[20, 100], shape=SymbolType.DIAMOND)
.set_global_opts(title_opts=opts.TitleOpts(title="词云图"))
.render("wordcloud_diamond.html")
)
8、pyecharts绘制雷达图
from pyecharts import options as opts
from pyecharts.charts import Radar
v1 = [[8.5,50000,15000,8000,13000,5000]]
v2 = [[8.1,42000,13000,7000,15000,7000]]
def radar_base() ->Radar:
c = (
Radar()
.add_schema(
schema=[
opts.RadarIndicatorItem(name='KDA',max_=10),
opts.RadarIndicatorItem(name='输出', max_=60000),
opts.RadarIndicatorItem(name='经济', max_=20000),
opts.RadarIndicatorItem(name='生存', max_=10000),
opts.RadarIndicatorItem(name='推进', max_=20000),
opts.RadarIndicatorItem(name='刷野', max_=10000),
]
)
.add(
'射手',v1,
color='blue',
areastyle_opts=opts.AreaStyleOpts(
opacity=0.5,
color='blue'
),
)
.add(
'法师',v2,
color='red',
areastyle_opts=opts.AreaStyleOpts(
opacity=0.5,
color='red'
),
)
.set_series_opts(label_opts=opts.LabelOpts(is_show=False))
.set_global_opts(title_opts=opts.TitleOpts(title='英雄成长属性对比'))
)
return c
radar_base().render("雷达图.html")
9、pyecharts绘制散点图
from pyecharts import options as opts
from pyecharts.charts import Scatter
from pyecharts.commons.utils import JsCode
from pyecharts.faker import Faker
c = (
Scatter()
.add_xaxis(Faker.choose())
.add_yaxis(
"商家A",
[list(z) for z in zip(Faker.values(), Faker.choose())],
label_opts=opts.LabelOpts(
formatter=JsCode(
"function(params){return params.value[1] +' : '+ params.value[2];}"
)
),
)
.set_global_opts(
title_opts=opts.TitleOpts(title="Scatter散点图-多维度数据"),
tooltip_opts=opts.TooltipOpts(
formatter=JsCode(
"function (params) {return params.name + ' : ' + params.value[2];}"
)
),
visualmap_opts=opts.VisualMapOpts(
type_="color", max_=150, min_=20, dimension=1
),
)
.render("散点图.html")
)
10、pyecharts绘制嵌套饼图
import pyecharts.options as opts
from pyecharts.charts import Pie
from pyecharts.globals import ThemeType
list1 = [300,55,400,110]
attr1 = ["学习", "运动","休息", "娱乐"]
list2 = [40,160,45,35,80,400,35,60]
attr2 = ["阅读", "上课", "运动", "讨论", "编程", "睡觉","听音乐", "玩手机"]
inner_data_pair = [list(z) for z in zip(attr1, list1)]
outer_data_pair = [list(z) for z in zip(attr2, list2)]
(
Pie(init_opts=opts.InitOpts(theme=ThemeType.LIGHT))
.add(
series_name="时长占比",
data_pair=inner_data_pair,
radius=[0, "30%"],
label_opts=opts.LabelOpts(position="inner"),
)
.add(
series_name="时长占比",
radius=["40%", "55%"],
data_pair=outer_data_pair,
label_opts=opts.LabelOpts(
position="outside",
formatter="{a|{a}}{abg|}\n{hr|}\n {b|{b}: }{c} {per|{d}%} ",
background_color="#eee",
border_color="#aaa",
border_width=1,
border_radius=4,
rich={
"a": {"color": "#999", "lineHeight": 22, "align": "center"},
"abg": {
"backgroundColor": "#e3e3e3",
"width": "100%",
"align": "right",
"height": 22,
"borderRadius": [4, 4, 0, 0],
},
"hr": {
"borderColor": "#aaa",
"width": "100%",
"borderWidth": 0.5,
"height": 0,
},
"b": {"fontSize": 16, "lineHeight": 33},
"per": {
"color": "#eee",
"backgroundColor": "#334455",
"padding": [2, 4],
"borderRadius": 2,
},
},
),
)
.set_global_opts(legend_opts=opts.LegendOpts(pos_left="left", orient="vertical"))
.set_series_opts(
tooltip_opts=opts.TooltipOpts(
trigger="item", formatter="{a}
{b}: {c} ({d}%)"
)
)
.render("嵌套饼图.html")
)
11、pyecharts绘制中国地图
from pyecharts import options as opts
from pyecharts.charts import Map
import random
ultraman = [
['四川', 0],
['台湾', 0],
['新疆', 0],
['江西', 0],
['河南', 0],
['辽宁', 0],
['青海', 0],
['福建', 0],
['西藏', 0]
]
monster = [
['广东', 0],
['北京', 0],
['上海', 0],
['台湾', 0],
['湖南', 0],
['浙江', 0],
['甘肃', 0],
['黑龙江', 0],
['江苏', 0]
]
def data_filling(array):
'''
作用:给数组数据填充随机数
'''
for i in array:
i[1] = random.randint(1,1000)
data_filling(ultraman)
data_filling(monster)
def create_china_map():
(
Map()
.add(
series_name="商家A",
data_pair=ultraman,
maptype="china",
is_selected=True,
is_roam=True,
is_map_symbol_show=False,
itemstyle_opts={
"normal": {"areaColor": "white", "borderColor": "red"},
"emphasis": {"areaColor": "pink"}
}
)
.add(
series_name="商家B",
data_pair=monster,
maptype="china",
)
.set_global_opts(
title_opts=opts.TitleOpts(title="中国地图"),
visualmap_opts=opts.VisualMapOpts(max_=1000, is_piecewise=False)
)
.set_series_opts(
label_opts=opts.LabelOpts(is_show=True, color="blue")
)
.render("中国地图.html")
)
create_china_map()
12、pyecharts绘制世界地图
from pyecharts import options as opts
from pyecharts.charts import Map
import random
ultraman = [
['Russia', 0],
['China', 0],
['United States', 0],
['Australia', 0]
]
monster = [
['India', 0],
['Canada', 0],
['France', 0],
['Brazil', 0]
]
def data_filling(array):
for i in array:
i[1] = random.randint(1,1000)
print(i)
data_filling(ultraman)
data_filling(monster)
def create_world_map():
'''
作用:生成世界地图
'''
(
Map()
.add(
series_name="商家A",
data_pair=ultraman,
maptype="world",
)
.add(
series_name="商家B",
data_pair=monster,
maptype="world",
)
.set_global_opts(
title_opts=opts.TitleOpts(title="世界地图"),
visualmap_opts=opts.VisualMapOpts(max_=1000, is_piecewise=False),
)
.set_series_opts(
label_opts=opts.LabelOpts(is_show=False, color="blue")
)
.render("世界地图.html")
)
create_world_map()