def get_pie(city, center1, center2):
data = df.loc[df['City'] == city, ['Date', 'AQI_Bucket']]
rank_message = data.groupby(['AQI_Bucket'])
rank_com = rank_message['AQI_Bucket'].agg(['count'])
rank_com.reset_index(inplace=True)
rank_com_last = rank_com.sort_values('count', ascending=False)
x = rank_com_last['AQI_Bucket']
y = rank_com_last['count']
pie = Pie(init_opts=opts.InitOpts(width='400px', height='300px'))
input_data = [list(z) for z in zip(x, y)]
pie.add(city, input_data, center=center1, radius=['15%', '30%'])
pie.set_series_opts(label_opts=opts.LabelOpts(formatter='{b}：{d}%'))
pie.set_global_opts(title_opts=opts.TitleOpts(
title=city,
pos_left=center2[0],
pos_top=center2[1],
),
legend_opts=opts.LegendOpts(is_show=False))
return pie
def mkhtml2(name1):
"""
饼图
:return:生成豆瓣top250电影产源国家数量占比分析图html文件
"""
# ORM查询
myresult = Test.objects.values('address').annotate(
count=Count('name')).order_by('-count')[:10]
# fetchall() 获取所有记录
namelist = []
# 将变量存在列表里
numlist = []
for name in myresult:
namelist.append(name['address'])
numlist.append(name['count'])
pie = Pie()
pie.add(
"占比",
[list(z) for z in zip(namelist, numlist)],
center=["40%", "60%"],
)
pie.set_global_opts(
title_opts=opts.TitleOpts(title="豆瓣top250电影产源国家数量占比"),
legend_opts=opts.LegendOpts(pos_left="35%"),
)
# 设置显示的样子，加入了百分比
pie.set_series_opts(label_opts=opts.LabelOpts(formatter="{b}: {c} ({d}%)"))
pie.render(f'{name1}')
print(f'{name1}已生成')
def pie_set_colors():
obj_pie = Pie()
obj_pie.add("",[list(z) for z in zip(Faker.choose(), Faker.values())])
obj_pie.set_colors(["blue", "green", "yellow", "red", "pink", "orange", "purple"])
obj_pie.set_series_opts(label_opts=opts.LabelOpts(formatter="{b}: {c}"))
obj_pie.set_global_opts(title_opts=opts.TitleOpts(title="Pie-设置颜色",subtitle ="副标题"))
return obj_pie
def analyze_remark_name():
close_partner_dict = {
'宝宝,糙糙,仙女,亲爱,老婆': 0,
'老公': 0,
'父亲,爸': 0,
'母亲,妈': 0,
'闺蜜,死党,基友': 0
}
# 遍历好友数据
for user in friends:
for key in close_partner_dict.keys():
# 判断该好友备注名是否包含close_partner_dict中的任意一个key
name = key.split(',')
for sub_name in name:
if (sub_name in user.remark_name):
close_partner_dict[key] += 1
break
name_list = ['最重要的她', '最重要的他', '爸爸', '妈妈', '死党']
num_list = [x for x in close_partner_dict.values()]
pie = Pie()
pie.add("可能是你最亲密的人", [list(z) for z in zip(name_list, num_list)])
pie.set_global_opts(title_opts=opts.TitleOpts(title="可能是你最亲密的人"))
pie.set_series_opts(label_opts=opts.LabelOpts(formatter="{b}: {c}"))
pie.render('data/你最亲密的人.html')
def statistics_friends():
# 初始化
unknown, known_male, known_female, known_other = 0, 0, 0, 0
# 遍历
for user in friends:
# 备注不为空
if ((user.remark_name).strip()):
if (user.sex == 1):
known_male += 1
elif (user.sex == 2):
known_female += 1
else:
known_other += 1
else:
unknown += 1
name_list = ['未设置备注的好友', '设置备注的男性好友', '设置备注的女性好友', '设置备注的其他好友']
num_list = [unknown, known_male, known_female, known_other]
pie = Pie()
pie.add("你认识的好友比例", [list(z) for z in zip(name_list, num_list)])
pie.set_global_opts(title_opts=opts.TitleOpts(title="你认识的好友比例"))
pie.set_series_opts(label_opts=opts.LabelOpts(formatter="{b}: {c}"))
pie.render('data/你认识的好友比例.html')
def Pie_base(sql, titl) -> Pie:
pie = Pie()
# engine = create_engine("mysql+pymysql://root:root@localhost:3306/mysql", encoding="utf-8")
# session = sessionmaker(bind=engine)
# # sql= "select gzlx as 故障类型,count(1) as 数量 from b_epos where rq BETWEEN '%s' and '%s' group by gzlx"% (rq1, rq2)
# df = pd.read_sql(sql, engine)
# rows=df.values.tolist()
# headers=df.columns.tolist()
with SQLPoll() as db:
students = db.fetch_all(sql, None)
headers = []
for student in students:
headers = list(student.keys())
break
c = []
rows = []
for student in students:
c = list(student.values())
rows += [c]
if len(rows) == 0:
rows = [['无', 0]]
pie.add("", rows)
pie.set_global_opts(title_opts=opts.TitleOpts(title=titl))
pie.set_series_opts(label_opts=opts.LabelOpts(formatter="{b}: {d}%"))
return pie
def MutiplePieCharts(datas):
height_i = '450'
if len(datas) > 3:
height_i = height_i + (350 * (len(datas) // 3))
height = str(height_i) + 'px'
pie = Pie(init_opts=opts.InitOpts(width="100%", height=height))
left_i = 1
right_i = 1
for data in datas:
right = str(300 * right_i) + 'px'
if left_i == 1:
left = '20%'
left_i = 2
elif left_i == 2:
left = '50%'
left_i = 3
else:
left = '80%'
right_i += 1
left_i = 1
pie.add(
data[0],
data[1],
center=[left, right],
radius=120,
)
pie.set_global_opts(title_opts=opts.TitleOpts(title="磁盘使用率"), )
pie.set_series_opts(label_opts=opts.LabelOpts(formatter="{b}: {c}"), )
return pie.render_embed()
def draw_category_pie(inner,
outside,
inner_title="分类报表",
outer_title='小类报表',
width=2000) -> Pie:
pie = Pie()
inner_radius = "70%"
outer_radius = "80%"
pie.add(
series_name=inner_title,
data_pair=inner,
radius=["0%", inner_radius],
label_opts=opts.LabelOpts(position="inner"),
)
pie.add(
series_name=outer_title,
radius=[inner_radius, outer_radius],
data_pair=outside,
label_opts=opts.LabelOpts(
position="outside",
formatter="{b}:\n{c}({d}%)",
border_width=1,
border_radius=4,
),
)
pie.set_global_opts(legend_opts=opts.LegendOpts(pos_left="left",
orient="vertical"), )
pie.set_series_opts(tooltip_opts=opts.TooltipOpts(
trigger="item", formatter="{a} <br/>{b}: {c} ({d}%)"))
return pie
def order_chart():
# 今日各状态订单总金额
pie2 = Pie()
pie2.add("", list(order_status_total.items()))
pie2.set_global_opts(title_opts=opts.TitleOpts(title="今日各状态订单总金额"))
pie2.set_series_opts(label_opts=opts.LabelOpts(formatter="{b}: {c}"))
return pie2.dump_options_with_quotes()
def create_gender(data):
df = data.copy()
# 修改数值
df.loc[df.gender == '0', 'gender'] = '未知'
df.loc[df.gender == '1', 'gender'] = '男性'
df.loc[df.gender == '2', 'gender'] = '女性'
# 根据性别分组
gender_message = df.groupby(['gender'])
# 对分组后的结果进行计数
gender_com = gender_message['gender'].agg(['count'])
gender_com.reset_index(inplace=True)
# 饼图数据
attr = gender_com['gender']
v1 = gender_com['count']
# 初始化配置
pie = Pie(init_opts=opts.InitOpts(width="800px", height="400px"))
# 添加数据，设置半径
pie.add("", [list(z) for z in zip(attr, v1)], radius=["40%", "75%"])
# 设置全局配置项，标题、图例、工具箱(下载图片)
pie.set_global_opts(title_opts=opts.TitleOpts(title="抖音大V性别分布情况",
pos_left="center"),
legend_opts=opts.LegendOpts(orient="vertical",
pos_left="left"),
toolbox_opts=opts.ToolboxOpts(
is_show=True, feature={"saveAsImage": {}}))
# 设置系列配置项，标签样式
pie.set_series_opts(
label_opts=opts.LabelOpts(is_show=True, formatter="{b}:{d}%"))
pie.render("抖音大V性别分布情况.html")
def sexAnalyse(itemname_, itemnamelist_, itemnumlist_):
totle = itemnumlist_[0] + itemnumlist_[1] + itemnumlist_[2]
subtitle = "共有:%d个好友" % totle
pie = Pie()#新建饼图对象
pie.add("",[list(z) for z in zip(itemnamelist_,itemnumlist_)],center=["35%", "50%"])#饼图对象数据添加
pie.set_global_opts(title_opts=opts.TitleOpts(title=subtitle),legend_opts=opts.LegendOpts(pos_left="15%"),)
pie.set_series_opts(label_opts=opts.LabelOpts(formatter="{b}: {c}"))
outFileName = itemname_+ '.html'
pie.render(outFileName)#保存饼图对象
def pie_render_air(self):
"""
* 实心圆一个，仅支持一份参数；
"""
# c = Pie(init_opts=opts.InitOpts(width="1600px", height="800px"))
c = Pie()
c.add(
series_name=self.y_name,
# radius=["40%", "55%"], # 半圆的尺寸；
radius=[0, "55%"],
data_pair=self.inner_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,
},
},
),
)
c.set_global_opts(title_opts=opts.TitleOpts(title=self.title),
legend_opts=opts.LegendOpts(pos_left=self.pos_left,
orient="vertical"))
c.set_series_opts(tooltip_opts=opts.TooltipOpts(
trigger="item", formatter="{a} <br/>{b}: {c} ({d}%)"))
return c
def sex_chart(data, movie_id):
list = []
data = data['gender'].value_counts()
for key, v in enumerate(data):
list.append([sex[key], v])
pie = Pie()
pie.add("", list)
pie.set_global_opts(title_opts=opts.TitleOpts(title="评论用户性别分布饼图"))
pie.set_series_opts(label_opts=opts.LabelOpts(formatter="{b}: {c}"))
pie.render('user_sex_' + movie_id + '.html')
def show_pie(id):
attr = ["成功（含熔断）", "失败", "限流"]
counts = [len(sync.success), len(sync.fail), sync.limit]
c = Pie(init_opts=opts.InitOpts(
width='1200px', height='800px', page_title='page'))
c.add("", [list(attr) for attr in zip(attr, counts)])
c.set_colors(["green", "red", "blue"])
c.set_global_opts(title_opts=opts.TitleOpts(title="成功失败数量饼图"))
c.set_series_opts(label_opts=opts.LabelOpts(formatter="{b}: {c}"))
c.render('成功失败数量饼图{}.html'.format(id + 1))
def pie_render_genre(self):
c = Pie()
c.add(self.y_name, self.inner_data_pair, center=["35%", "50%"])
c.set_global_opts(title_opts=opts.TitleOpts(title=self.title),
legend_opts=opts.LegendOpts(pos_left=self.pos_left,
orient="vertical"))
c.set_series_opts(tooltip_opts=opts.TooltipOpts(
trigger="item", formatter="{a} <br/>{b}: {c} ({d}%)"),
label_opts=opts.LabelOpts(formatter="{b}: {d}%"))
return c
def pie_radius():
obj_pie = Pie()
# radius=["40%", "75%"]饼图的半径，数组的第一项是内半径，第二项是外半径
obj_pie.add("",[list(z) for z in zip(Faker.choose(), Faker.values())],radius=["40%", "75%"],)
obj_pie.set_series_opts(label_opts=opts.LabelOpts(formatter="{b}: {c}"))
obj_pie.set_global_opts(
title_opts=opts.TitleOpts(title="Pie-Radius",subtitle ="副标题"),
# 让图例legend显示到左侧
legend_opts=opts.LegendOpts(orient="vertical", pos_top="15%", pos_left="2%"),
)
return obj_pie
def pie():
pie = Pie(init_opts=opts.InitOpts(
theme=ThemeType.PURPLE_PASSION, width="1280px", height="1080px"))
pie.add(
"",
[list(z) for z in zip(data["项目简称"].to_list(), data["母婴"].to_list())],
radius=["40%", "75"])
pie.set_global_opts(
title_opts=opts.TitleOpts(title="各类母婴产品", pos_bottom='50%'))
pie.set_series_opts(label_opts=opts.LabelOpts(formatter="{b}:{c}"))
pie.render('../graph/5.4(各类母婴产品盈利).html')
def get_message_type_frequency(file_path, wxid):
"""
:param file_path: 经过预处理后的message表存储位置
:param wxid: 待查询人的微信id
:return:
"""
# file_path = r'D:\wechet-anayze\pre-message-2.txt'
message = pd.read_csv(file_path, sep=',', encoding='utf-8', low_memory=False)
# wxid = ''
# 进行数据筛选，选择message表中与所需微信id一致的数据
message = message[message['talker'] == wxid]
# 根据消息类型统计每种类型的频次（索引为数字编码）
chat_type_count = message['type'].groupby(message['type']).size()
# 消息类型对应关系
message_type = {'1': '文本内容', "3": "图片及视频", "34": "语音消息", "42": "名片信息", "43": "图片及视频",
"47": "表情包", "48": "定位信息", "49": "小程序链接", "10000": "消息撤回提醒", "1048625": "网络照片",
"16777265": "链接信息", "419430449": "微信转账", "436207665": "红包", "469762097": "红包",
"-1879048186": "位置共享"}
# 集合对象，功能与chat_type_count相同，存储（聊天类型：频次）信息（索引为对应中文类型）
chat_type_count_dict = {}
# 根据消息类型代码
for key in chat_type_count.index:
if str(key) in message_type.keys():
print(message_type.get(str(key)))
chat_type_count_dict[message_type.get(str(key))] = chat_type_count[key]
else:
chat_type_count_dict[key] = chat_type_count[key]
print("结果集类型: ", type(chat_type_count_dict))
print(chat_type_count_dict)
x_data = []
y_data = []
for key in chat_type_count_dict:
temp = [str(key), chat_type_count_dict.get(key)]
x_data.append(str(key))
y_data.append(int(chat_type_count_dict.get(key)))
a1 = []
for z in zip(x_data, y_data):
a1.append(z)
pie = Pie(init_opts=opts.InitOpts(width="1600px", height="600px", page_title="消息类型统计"))
pie.add(
"",
data_pair=a1,
center=["35%", "60%"],
)
pie.set_global_opts(
title_opts=opts.TitleOpts(title="Pie-调整位置"),
legend_opts=opts.LegendOpts(pos_left="15%"),
)
pie.set_series_opts(label_opts=opts.LabelOpts(formatter="{b}:{c}"))
pie.render("message_type_count.html")
def drawPie(title, data, savepath='./results'):
if not os.path.exists(savepath):
os.mkdir(savepath)
pie = Pie()
attrs = [i for i, j in data.items()]
values = [j for i, j in data.items()]
pie.add("", [list(z) for z in zip(attrs, values)])
pie.set_global_opts(title_opts=opts.TitleOpts(title="评分情况"),
legend_opts=opts.LegendOpts(pos_left=160))
pie.set_series_opts(label_opts=opts.LabelOpts(formatter="{b}:{c}"))
pie.render(os.path.join(savepath, '%s.html' % title))
def level_pie(data):
level_list = [[i, j]
for i, j in enumerate(data['userlevel'].value_counts())]
pie = Pie()
pie.add("", level_list, radius=["40%", "75%"])
pie.set_global_opts(title_opts=opts.TitleOpts(title="等级分布"),
legend_opts=opts.LegendOpts(orient="vertical",
pos_top="15%",
pos_left="2%"))
pie.set_series_opts(label_opts=opts.LabelOpts(formatter="{b}: {c}"))
pie.render("等级分布.html")
def generate_pie_html(dict_rows, key, value):
data = []
for row in dict_rows:
data.append([row[key], round(row[value], 2)])
pie = Pie(init_opts=opts.InitOpts(theme=ThemeType.SHINE))
pie.add("", data)
# pie.set_global_opts(title_opts=opts.TitleOpts(title="我的摊大饼策略分布"))
pie.set_global_opts(legend_opts=opts.LegendOpts(is_show=False))
pie.set_series_opts(label_opts=opts.LabelOpts(formatter="{b}: {d}%"))
pie_html = pie.render_embed('template.html', env)
return pie_html
def pie_radius_chart(data_pie):
c = Pie()
c.add(series_name='類別', data_pair=data_pie, radius=['40%', '75%'])
c.set_global_opts(title_opts=opts.TitleOpts(title='各種類占比'),
legend_opts=opts.LegendOpts(orient='vertical',
pos_top='15%',
pos_left='2%'))
c.set_series_opts(tooltip_opts=opts.TooltipOpts(
trigger='item', formatter='{a} <br/> {b}:{c} ({d}%)'),
label_opts=opts.LabelOpts(formatter="{b}:{c}%"))
return c
def pie_position():
obj_pie = Pie()
# center=["35%", "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
# 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
obj_pie.add("",[list(z) for z in zip(Faker.choose(), Faker.values())],center=["35%", "50%"])
obj_pie.set_series_opts(label_opts=opts.LabelOpts(formatter="{b}: {c}"))
obj_pie.set_global_opts(
title_opts=opts.TitleOpts(title="Pie-设置位置",subtitle ="副标题"),
legend_opts=opts.LegendOpts(pos_left="15%"),
)
return obj_pie
def data_analysis(self):
from pyecharts import options as opts # 导入包
from pyecharts.charts import Pie
from pyecharts.render import make_snapshot
c = Pie() # 绘制饼状图
c.add(
"",
[list(z) for z in zip(self.location_name, self.location_times)],
radius=["40%", "75%"], # 内半径和外半径占比
)
c.set_global_opts(title_opts=opts.TitleOpts(title="壁纸拍摄地址分布图"),)
c.set_series_opts(label_opts=opts.LabelOpts(formatter="{b}: {c}"))
c.render('壁纸拍摄地址分布图.html')
def pie_charts() -> Pie:
# 创建实例对象
pie = Pie(init_opts=opts.InitOpts(width='1000px', height='600px'))
# 添加数据
pie.add(series_name="访问来源", data_pair=data_pie)
# 设置全局项
pie.set_global_opts(title_opts=opts.TitleOpts(
title="课程不同的来源销售分析", pos_left='center', pos_top=20))
#设置每项数据占比
pie.set_series_opts(tooltip_opts=opts.TooltipOpts(
trigger='item', formatter="{a} <br/> {b}:{c} ({d}%)"))
return pie
def pieChart(df):
def randomcolor(kind):
colors = []
for i in range(kind):
#colArr = ['1', '2', '3', '4', '5', '6', '7', '8', '9', 'A', 'B', 'C', 'D', 'E', 'F','G','H','I','K','L','M','N']
colArr = [
'1', '2', '3', '4', '5', '6', '7', '8', '9', 'A', 'B', 'C',
'D', 'E', 'F'
]
color = ''
for i in range(6):
color += colArr[random.randint(0, 14)]
colors.append('#' + color)
return colors
all_columns = df.columns
type_of_plot = st.selectbox("Select Type of Plot",
["PIE1", "PIE2", "PIE3"])
columns_to_plot = st.selectbox("Select 1 column", all_columns, key='a')
columns_to_plot1 = st.selectbox("Select 1 column", all_columns, key='b')
if st.button("Generate Plot"):
#st.success("Generating Customizable Plot of {} for {}".format(type_of_plot))
if type_of_plot == 'PIE1':
cje = df[columns_to_plot].tolist()
other_var = df[columns_to_plot1].tolist()
color_series = randomcolor(len(cje))
pie = Pie()
pie.add('', [list(z) for z in zip(cje, other_var)],
radius=['30%', '135%'],
center=['50%', '65%'],
rosetype='area')
pie.set_global_opts(title_opts=opts.TitleOpts(
title='Population Generale des 20 CJE de Montreal'),
legend_opts=opts.LegendOpts(is_show=False),
toolbox_opts=opts.ToolboxOpts())
pie.set_series_opts(
label_opts=opts.LabelOpts(is_show=True,
position='inside',
font_size=12,
formatter='{b}:{c}',
font_style='italic',
font_weight='bold',
font_family='Microsoft YaHei'))
pie.set_colors(color_series)
return pie
def pizza(info, componente, metrica="%", temaEscuro=False):
if (temaEscuro):
pie = Pie(init_opts=opts.InitOpts(theme=ThemeType.CHALK))
else:
pie = Pie(init_opts=opts.InitOpts(theme=ThemeType.VINTAGE))
pie.add(series_name=componente, data_pair=info)
pie.set_global_opts(title_opts=opts.TitleOpts(title="Média de uso de " + componente))
pie.set_series_opts(label_opts=opts.LabelOpts(formatter="{b}: {c} " + metrica))
make_snapshot(driver, pie.render("chart.html"), "chart.png")
abrirGrafico()
return 0
def pyechart_Pie_plot(self, filedata, para):
from pyecharts.charts import Pie
file_name = '南丁格尔玫瑰图.html'
path_plotly = self.path_dir_plotly_html + os.sep + file_name # 文件路径，前面是文件夹后面是文件名
costumeTheme = self.themedict[para['theme']]
# -----------------------------------------------------------------------
# 准备数据
df = pd.read_excel(filedata, sheet_name='sheet1')
# # 提取数据
v = df['provinces'].values.tolist()
d = df['num'].values.tolist()
color_series = df['color_series'].values.tolist()
# 降序排序
df.sort_values(by='num', ascending=False, inplace=True)
# 实例化Pie类
pie1 = Pie(init_opts=opts.InitOpts(
theme=costumeTheme, width=para['width'], height=para['height']))
# 设置颜色
pie1.set_colors(color_series)
# 添加数据，设置饼图的半径，是否展示成南丁格尔图
pie1.add("", [list(z) for z in zip(v, d)],
radius=["10%", "135%"],
center=["50%", "65%"],
rosetype="area")
# 设置全局配置项
pie1.set_global_opts(
title_opts=opts.TitleOpts(title=para["title"],
subtitle=para["subtitle"]),
toolbox_opts=opts.ToolboxOpts(feature=opts.ToolBoxFeatureOpts(
save_as_image=opts.ToolBoxFeatureSaveAsImageOpts(
background_color="white")))
#visualmap_opts=opts.VisualMapOpts(),
)
# 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="normal", # css的格式
font_weight="normal",
font_family="宋体"), )
# 生成html文档
pie1.render(path_plotly)
return path_plotly # 返回该HTML文件路径
def draw(list1, list2):
pie = Pie()
pie.add("", list(zip(list1, list2)))
pie.set_global_opts(
title_opts=opts.TitleOpts(title="消费者购买的HUAWEIP30颜色图例"), #标题
legend_opts=opts.LegendOpts(orient="vertical",
pos_top="15%",
pos_left="4%"),
)
pie.set_series_opts(
label_opts=opts.LabelOpts(formatter="{b}: {c}")) #图例显示（颜色+人数），例：亮黑色：46
pie.set_colors(
["lightblue", "black", "turquoise", "orangered", "lightpink"])
pie.render(desktop + "\\jd.huaweiP30.html")
return True
def gender_pie(data):
gender_list = []
for i, j in enumerate(data['gender'].value_counts()):
if i == 0:
i = '未知'
elif i == 1:
i = '男'
else:
i = '女'
gender_list.append([i, j])
pie = Pie()
pie.add("", gender_list)
pie.set_global_opts(title_opts=opts.TitleOpts(title="性别分布"))
pie.set_series_opts(label_opts=opts.LabelOpts(formatter="{b}: {c}"))
pie.render("性别分布.html")
