其实真正能让自己走远的，都是自律、积极和勤奋。
文章目录
一、柱形图
代码如下：
代码语言：txt复制from pyecharts.charts import Bar
from pyecharts.faker import Faker
from pyecharts.globals import ThemeType, CurrentConfig
from pyecharts import options as opts
CurrentConfig.ONLINE_HOST = 'D:/python/pyecharts-assets-master/assets/'
# 链式调用
c = (
Bar(
init_opts=opts.InitOpts( # 初始配置项
theme=ThemeType.MACARONS,
animation_opts=opts.AnimationOpts(
animation_delay=1000, animation_easing="cubicOut" # 初始动画延迟和缓动效果
))
)
.add_xaxis(xaxis_data=Faker.choose()) # x轴
.add_yaxis(series_name="商家A", yaxis_data=Faker.values()) # y轴
.add_yaxis(series_name="商家B", yaxis_data=Faker.values()) # y轴
.set_global_opts(
title_opts=opts.TitleOpts(title='标题', subtitle='副标题', # 标题配置和调整位置
title_textstyle_opts=opts.TextStyleOpts(
font_family='SimHei', font_size=25, font_weight='bold', color='red',
), pos_left="90%", pos_top="10",
),
xaxis_opts=opts.AxisOpts(name='x轴名称', axislabel_opts=opts.LabelOpts(rotate=45)), # 设置x名称和Label rotate解决标签名字过长使用
yaxis_opts=opts.AxisOpts(name='y轴名称'),
)
.render("bar_001.html")
)运行效果如下：
代码如下：
代码语言：txt复制import pandas as pd
import collections
from pyecharts import options as opts
from pyecharts.charts import Bar
from pyecharts.globals import ThemeType, CurrentConfig
import random
CurrentConfig.ONLINE_HOST = 'D:/python/pyecharts-assets-master/assets/'
df = pd.read_excel("hotel.xlsx")
area = list(df['酒店地址'])
area_list = []
for i in area:
_index = i.find("区")
# 字符串切片得到行政区名
i = i[:_index 1]
area_list.append(i)
area_count = collections.Counter(area_list)
area_dic = dict(area_count)
# 两个列表对应 行政区 对应的酒店数量
area = [x for x in list(area_dic.keys())][0:10]
nums = [y for y in list(area_dic.values())][:10]
# 定制风格
bar = Bar(init_opts=opts.InitOpts(theme=ThemeType.MACARONS))
colors = ['red', '#0000CD', '#000000', '#008000', '#FF1493', '#FFD700', '#FF4500', '#00FA9A', '#191970', '#9932CC']
random.shuffle(colors)
# 配置y轴数据 Baritem
y = []
for i in range(10):
y.append(
opts.BarItem(
value=nums[i],
itemstyle_opts=opts.ItemStyleOpts(color=colors[i]) # 设置每根柱子的颜色
)
)
bar.add_xaxis(xaxis_data=area)
bar.add_yaxis("酒店数量", yaxis_data=y)
bar.set_global_opts(xaxis_opts=opts.AxisOpts(
name='行政区',
axislabel_opts=opts.LabelOpts(rotate=45)
),
yaxis_opts=opts.AxisOpts(
name='酒店数量', min_=0, max_=330, # y轴刻度的最小值 最大值
),
title_opts=opts.TitleOpts(
title="行政区-酒店数量",
title_textstyle_opts=opts.TextStyleOpts(
font_family="KaiTi", font_size=25, color="black"
)
))
# 标记最大值 最小值 平均值 标记平均线
bar.set_series_opts(label_opts=opts.LabelOpts(is_show=False),
markpoint_opts=opts.MarkPointOpts(
data=[
opts.MarkPointItem(type_="max", name="最大值"),
opts.MarkPointItem(type_="min", name="最小值"),
opts.MarkPointItem(type_="average", name="平均值")]),
markline_opts=opts.MarkLineOpts(
data=[
opts.MarkLineItem(type_="average", name="平均值")]))
bar.render("行政区酒店数量最多的Top10.html")运行效果如下：
代码如下：
代码语言：txt复制from pyecharts import options as opts
from pyecharts.charts import Bar
from pyecharts.faker import Faker
from pyecharts.globals import ThemeType, CurrentConfig
CurrentConfig.ONLINE_HOST = 'D:/python/pyecharts-assets-master/assets/'
c = (
Bar(init_opts=opts.InitOpts(theme=ThemeType.DARK))
.add_xaxis(xaxis_data=Faker.days_attrs)
.add_yaxis("商家A", yaxis_data=Faker.days_values)
.set_global_opts(
title_opts=opts.TitleOpts(title="Bar-DataZoom（slider inside）"),
datazoom_opts=[opts.DataZoomOpts(), opts.DataZoomOpts(type_="inside")],
)
.render("bar_datazoom_both.html")
)运行效果如下：
二、饼图
代码如下：
代码语言：txt复制from pyecharts import options as opts
from pyecharts.charts import Pie
from pyecharts.faker import Faker
from pyecharts.globals import CurrentConfig
CurrentConfig.ONLINE_HOST = 'D:/python/pyecharts-assets-master/assets/'
c = (
Pie()
.add(
"",
[list(z) for z in zip(Faker.choose(), Faker.values())],
# 饼图的中心（圆心）坐标，数组的第一项是横坐标，第二项是纵坐标
# 默认设置成百分比，设置成百分比时第一项是相对于容器宽度，第二项是相对于容器高度
center=["35%", "50%"],
)
.set_colors(["blue", "green", "yellow", "red", "pink", "orange", "purple"]) # 设置颜色
.set_global_opts(
title_opts=opts.TitleOpts(title="Pie-设置颜色-调整图例位置"),
legend_opts=opts.LegendOpts(type_="scroll", pos_left="70%", orient="vertical"), # 调整图例位置
)
.set_series_opts(label_opts=opts.LabelOpts(formatter="{b}: {c}"))
.render("pie_set_color.html")
)运行效果如下：
代码如下：
代码语言：txt复制import pyecharts.options as opts
from pyecharts.charts import Pie
from pyecharts.globals import CurrentConfig
CurrentConfig.ONLINE_HOST = 'D:/python/pyecharts-assets-master/assets/'
x_data = ["深度学习", "数据分析", "Web开发", "爬虫", "图像处理"]
y_data = [688, 888, 560, 388, 480]
data_pair = [list(z) for z in zip(x_data, y_data)]
data_pair.sort(key=lambda x: x[1])
c = (
# 宽 高 背景颜色
Pie(init_opts=opts.InitOpts(width="1200px", height="800px", bg_color="#2c343c"))
.add(
series_name="学习方向", # 系列名称
data_pair=data_pair, # 系列数据项，格式为 [(key1, value1), (key2, value2)]
rosetype="radius", # radius：扇区圆心角展现数据的百分比，半径展现数据的大小
radius="55%", # 饼图的半径
center=["50%", "50%"], # 饼图的中心（圆心）坐标，数组的第一项是横坐标，第二项是纵坐标
label_opts=opts.LabelOpts(is_show=False, position="center"), # 标签配置项
)
.set_global_opts(
title_opts=opts.TitleOpts(
title="Customized Pie",
pos_left="center",
pos_top="20",
title_textstyle_opts=opts.TextStyleOpts(color="#fff"),
),
legend_opts=opts.LegendOpts(is_show=False),
)
.set_series_opts(
tooltip_opts=opts.TooltipOpts(
trigger="item", formatter="{a} <br/>{b}: {c} ({d}%)" # 'item': 数据项图形触发，主要在散点图，饼图等无类目轴的图表中使用
),
label_opts=opts.LabelOpts(color="rgba(255, 255, 255, 0.3)"),
)
.render("customized_pie.html")
)运行效果如下：
三、环图
代码如下：
代码语言：txt复制from pyecharts import options as opts
from pyecharts.charts import Pie
from pyecharts.faker import Faker
from pyecharts.globals import CurrentConfig
CurrentConfig.ONLINE_HOST = 'D:/python/pyecharts-assets-master/assets/'
c = (
Pie()
.add(
"",
[list(z) for z in zip(Faker.choose(), Faker.values())],
# 饼图的半径，数组的第一项是内半径，第二项是外半径
# 默认设置成百分比，相对于容器高宽中较小的一项的一半
radius=["40%", "60%"],
)
.set_colors(["blue", "green", " #800000", "red", "#000000", "orange", "purple"])
.set_global_opts(
title_opts=opts.TitleOpts(title="Pie-Radius"),
legend_opts=opts.LegendOpts(orient="vertical", pos_top="15%", pos_left="2%"),
)
.set_series_opts(label_opts=opts.LabelOpts(formatter="{b}: {c}"))
.render("pie_radius.html")
)运行效果如下：
代码如下：
代码语言：txt复制from pyecharts import options as opts
from pyecharts.charts import Pie
from pyecharts.faker import Faker
from pyecharts.globals import CurrentConfig
CurrentConfig.ONLINE_HOST = 'D:/python/pyecharts-assets-master/assets/'
c = (
Pie()
.add(
"",
[list(z) for z in zip(Faker.choose(), Faker.values())],
radius=["40%", "60%"],
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(title_opts=opts.TitleOpts(title="Pie-富文本示例"))
.render("pie_rich_label.html")
)运行效果如下：
四、玫瑰图
代码如下：
代码语言：txt复制from pyecharts import options as opts
from pyecharts.charts import Pie
from pyecharts.faker import Faker
from pyecharts.globals import CurrentConfig
CurrentConfig.ONLINE_HOST = 'D:/python/pyecharts-assets-master/assets/'
labels = ['可乐', '雪碧', '橙汁', '奶茶', '冰啤酒', '柠檬水']
values = [6, 12, 28, 52, 72, 96]
v = Faker.choose()
c = (
Pie()
.add(
"",
[list(z) for z in zip(v, Faker.values())],
radius=["40%", "75%"],
center=["22%", "50%"],
rosetype="radius",
label_opts=opts.LabelOpts(is_show=False),
)
.add(
"",
[list(z) for z in zip(labels, values)],
radius=["40%", "75%"],
center=["70%", "50%"],
rosetype="area",
)
.set_global_opts(title_opts=opts.TitleOpts(title="Pie-玫瑰图示例"),
legend_opts=opts.LegendOpts(is_show=False)
)
.render("pie_rosetype.html")
)
from pyecharts import options as opts
from pyecharts.charts import Pie
from pyecharts.globals import CurrentConfig
import pandas as pd
CurrentConfig.ONLINE_HOST = 'D:/python/pyecharts-assets-master/assets/'
provinces = ['北京','上海','黑龙江','吉林','辽宁','内蒙古','新疆','西藏','青海','四川','云南','陕西','重庆',
'贵州','广西','海南','澳门','湖南','江西','福建','安徽','浙江','江苏','宁夏','山西','河北','天津']
num = [1,1,1,17,9,22,23,42,35,7,20,21,16,24,16,21,37,12,13,14,13,7,22,8,16,13,13]
color_series = ['#FAE927','#E9E416','#C9DA36','#9ECB3C','#6DBC49',
'#37B44E','#3DBA78','#14ADCF','#209AC9','#1E91CA',
'#2C6BA0','#2B55A1','#2D3D8E','#44388E','#6A368B'
'#7D3990','#A63F98','#C31C88','#D52178','#D5225B',
'#D02C2A','#D44C2D','#F57A34','#FA8F2F','#D99D21',
'#CF7B25','#CF7B25','#CF7B25']
# 创建DataFrame
df = pd.DataFrame({'provinces': provinces, 'num': num})
# 降序排序
df.sort_values(by='num', ascending=False, inplace=True)
# 提取数据
v = df['provinces'].values.tolist()
d = df['num'].values.tolist()
# 绘制饼图
pie1 = Pie(init_opts=opts.InitOpts(width='1250px', height='750px'))
# 设置颜色
pie1.set_colors(color_series)
pie1.add("", [list(z) for z in zip(v, d)],
radius=["30%", "100%"],
center=["50%", "50%"],
rosetype="area"
)
# 设置全局配置项
pie1.set_global_opts(title_opts=opts.TitleOpts(title='多省区市n确诊病例连续多日',subtitle='零新增',
title_textstyle_opts=opts.TextStyleOpts(font_size=25,color= '#0085c3'),
subtitle_textstyle_opts= opts.TextStyleOpts(font_size=50,color= '#003399'),
pos_right= 'center',pos_left= 'center',pos_top='42%',pos_bottom='center'
),
legend_opts=opts.LegendOpts(is_show=False),
toolbox_opts=opts.ToolboxOpts())
# 设置系列配置项
pie1.set_series_opts(label_opts=opts.LabelOpts(is_show=True, position="inside", font_size=12,
formatter="{b}:{c}天", font_style="italic",
font_weight="bold", font_family="SimHei"
),
)
# 渲染在html页面上
pie1.render('南丁格尔玫瑰图示例.html')运行效果如下：
作者：叶庭云 微信公众号：修炼Python CSDN：https://yetingyun.blog.csdn.net/ 本文仅用于交流学习，未经作者允许，禁止转载，更勿做其他用途，违者必究。 觉得文章对你有帮助、让你有所收获的话，期待你的点赞呀，不足之处，也可以在评论区多多指正。
