def draw_multiple_pie(month, day):
max_width, max_height = 1400, 3000
pie = Pie(init_opts=opts.InitOpts(width='{}px'.format(max_width),
height='{}px'.format(max_height)))
pie.set_global_opts(legend_opts=opts.LegendOpts(is_show=False),
title_opts=opts.TitleOpts(
title='2020-%02d-%d 全国各省份城市确诊病例' % (month, day)))
h_center, v_center = 10, 40
horizontal_step, vertical_step = 350, 320
for p in get_province_data(month, day):
title = '%s-%d例' % (p['provinceShortName'], p['confirmedCount'])
labels = [city['cityName'] for city in p['cities']]
counts = [city['confirmedCount'] for city in p['cities']]
if len(labels) == 0:
continue
pie.add(title, [list(z) for z in zip(labels, counts)],
radius=[5, 80],
center=[h_center + 150, v_center + 110]).set_series_opts(
label_opts=opts.LabelOpts(formatter="{b}: {c}"),
tooltip_opts=opts.TooltipOpts())
h_center += horizontal_step
if h_center + 200 > max_width:
h_center = 10
v_center += vertical_step
root = 'html-charts/%d%d' % (month, day)
create_dir(root)
pie.render('%s/省份信息.html' % root)
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("你认识的好友比例", title_pos='center')
pie.add("",
name_list,
num_list,
is_label_show=True,
legend_orient="vertical",
legend_pos="left")
pie.render('data/你认识的好友比例.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 bingtu(shopNames, nums):
attr = shopNames
v1 = nums
pie = Pie("笔记本店铺饼图展示")
pie.add("", attr, v1, is_label_show=True)
pie.show_config()
pie.render("D:\\scrapy\\jingdong\\shops.html")
def show_pie_charts(df):
score_perc = df['star'].value_counts() / df['star'].value_counts().sum(
) # 评分占比 = 评分1-5的个数(分别) / 评分总个数
score_perc = np.round(score_perc * 100, 2)
score_perc = score_perc.sort_index() # Series也可以排序
# 聚合后类型为Series，转成Dataframe
# df_score = pd.DataFrame(list(zip(score_perc.index, score_perc.values)), columns=['score', 'percentage']).sort_values('score')
pie1 = Pie(init_opts=opts.InitOpts(width='1350px', height='750px'))
pie1.add(
series_name='评分占比',
data_pair=[*zip(score_perc.index, score_perc.values)
], # Series: zip打包为一个元组对象，用*解压成元组，再[]转成列表
# data_pair=[*zip(df_score['score'], df_score['percentage'])], # Dataframe
label_opts=opts.LabelOpts(formatter='{c}%'), # formatter='{c}%'百分比
radius=['35%', '70%'] # 是什么意思
)
pie1.set_global_opts(
title_opts=opts.TitleOpts(title='总体评分分布'),
legend_opts=opts.LegendOpts(orient='vertical',
pos_top='15%',
pos_left='2%'), # 图例的位置：水平/垂直
toolbox_opts=opts.ToolboxOpts()) # 右上角的工具栏，保存图片等等
pie1.set_colors(['#D7655A', '#FFAF34', '#3B7BA9', '#EF9050', '#6FB27C'])
pie1.render('charts/pie_chart.html')
def subject_pie():
# 学科占比图
subject_count = [("物理", 11931), ("化学", 5414), ("生物", 3153), ("政治", 761),
("历史", 1057), ("地理", 1015)]
subject_pie = Pie().add("", subject_count).set_global_opts(title_opts=opts.TitleOpts(title="学科比例图")) \
.set_series_opts(label_opts=opts.LabelOpts(formatter="{b}: {c}"))
subject_pie.render("subject_pie.html")
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 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 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 get_github_id_sum(self):
select_sql = "select github_id,sum(zh_sum) as total from zh_trans where flag = " \
+ str(self.flag) + " and merge_time between '" + self.begin_time + "' and '" + \
self.end_time + "' group by github_id order by total desc"
# 连接数据库
conn = sqlite3.connect(self.db)
# 创建一个 cursor
cursor = conn.cursor()
cursor.execute(select_sql)
data = cursor.fetchall()
all_data = []
all_author = []
all_value = []
total = 0
for zh in data:
all_author.append(zh[0])
all_value.append((zh[1]))
all_data.append([zh[0], zh[1]])
total += zh[1]
if self.flag == 0:
series_name = "开始时间：" + self.begin_time + " 结束时间：" + self.end_time + "\n istio.io 新增中文翻译字数统计 总参与人数为：" + str(
len(all_data)) + "\n istio.io 新增中文翻译字数统计 总翻译字数为：" + str(total)
else:
series_name = "开始时间：" + self.begin_time + " 结束时间：" + self.end_time + "\n istio.io 更新中文翻译字数统计 总参与人数为：" + str(
len(all_data)) + "\n istio.io 更新中文翻译字数统计 总翻译字数为：" + str(total)
generated_log(series_name, self.flag)
# 饼图
pie = Pie()
pie.add(
"",
data_pair=all_data,
center=["40%", "62%"],
radius=["0%", "45%"],
rosetype='radius').set_global_opts(
title_opts=opts.TitleOpts(title=""),
legend_opts=opts.LegendOpts(
orient="vertical", pos_top="5%",
pos_right="6%")).set_series_opts(label_opts=opts.LabelOpts(
horizontal_align=True, formatter="{b}: {c}"))
html_time = str(time.strftime('%Y-%m-%d',
time.localtime(time.time()))).replace(
"-", "")
if self.flag == 0:
pie.render(html_time + "page_pie_add.html")
else:
pie.render(html_time + "page_pie_update.html")
# 柱状图
bar = (Bar().add_xaxis(all_author).add_yaxis(
"github账户", all_value).set_global_opts(title_opts=opts.TitleOpts(
title="翻译统计")))
if self.flag == 0:
bar.render(html_time + "page_bar_add.html")
else:
bar.render(html_time + "page_bar_update.html")
cursor.close()
conn.commit()
conn.close()
def analyze_remark_name():
close_partner_dict = {
'宝宝,猪,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("可能是你最亲密的人")
pie.add("", name_list, num_list, is_label_show=True, is_legend_show=False)
pie.render('data/你最亲密的人.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 drawpie(self, title, infos):
from pyecharts.charts import Pie
from pyecharts import options as opts
pie = Pie(init_opts=dict(theme='westeros', page_title=title)).add(
title,
data_pair=tuple(zip(infos.keys(), infos.values())),
rosetype='area')
pie.set_global_opts(title_opts=opts.TitleOpts(title=title))
pie.render(os.path.join(self.savedir, '%s.html' % title))
def render_html(self) -> str:
"""渲染html"""
pie = Pie(init_opts=InitOpts(theme=ThemeType.LIGHT))
pie.add('KeyWords', self.result.items())
# pie.set_global_opts(title_opts=TitleOpts(title='主标题', subtitle='附标题'))
html = CacheModule.create_cache_path('html')
pie.render(html)
self.htmlpath = html
return 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 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 DrawPie(city_names):
attrs = []
values = []
for cn in city_names:
attrs.append(cn)
data = qr.get_data(cn)
values.append(data['QY'])
pie = Pie('部分城市相对气压饼图')
pie.add('', attrs, values, is_label_show=True)
pie.render('weatherPie.html')
def show(stat_sexs, my_friends):
"""
用pyecharts进行统计
:param stat_sexs:
:return:
"""
attr = ["男", "女", "未知"]
v1 = [stat_sexs[1], stat_sexs[2], stat_sexs[0]]
pie = Pie("微信{}好友男女比例".format(len(my_friends)))
pie.add("", attr, v1, is_label_show=True)
pie.render()
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 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 analysisSex(self, title='分析好友性别分布', friends_info=None):
sex_infos = {'男': 0, '女': 0, '未知': 0}
for item in friends_info.get('sex'):
if item == 0: sex_infos['未知'] += 1
elif item == 1: sex_infos['男'] += 1
elif item == 2: sex_infos['女'] += 1
pie = Pie(init_opts=dict(theme='westeros', page_title=title)).add(
title,
data_pair=tuple(zip(sex_infos.keys(), sex_infos.values())),
rosetype='area')
pie.set_global_opts(title_opts=opts.TitleOpts(title=title))
pie.render(os.path.join(self.savedir, '%s.html' % title))
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 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")
def score_pie(data):
score_list = []
for i, j in enumerate(data['score'].value_counts()):
if i == 0:
i = '0分' # 当数据项名称为0时，不在图表中展示，这个疑为 echarts 的 bug
score_list.append([i, j])
pie = Pie()
pie.add("", score_list, radius=["30%", "75%"], center=["50%", "50%"], rosetype="radius")
pie.set_global_opts(
title_opts=opts.TitleOpts(title="评分分布"),
legend_opts=opts.LegendOpts(
orient="vertical", pos_left="10%"
))
pie.set_series_opts(label_opts=opts.LabelOpts(formatter="{b}:{c}:{d}%"))
pie.render("评分分布.html")
def score_pie(data):
index = data['score'].value_counts().index.tolist()
values = data['score'].value_counts().values.tolist()
score_list = list(zip(index, values))
pie = Pie()
pie.add("",
score_list,
radius=["30%", "75%"],
center=["50%", "50%"],
rosetype="radius")
pie.set_global_opts(title_opts=opts.TitleOpts(title="评分分布"),
legend_opts=opts.LegendOpts(orient="vertical",
pos_left="10%"))
pie.set_series_opts(label_opts=opts.LabelOpts(formatter="{b}:{c}:{d}%"))
pie.render("评分分布.html")
def draw_pie_picture(data, to_file, svg_name, colors=None):
c = Pie(init_opts=opts.InitOpts(width="1600px", height="900px", bg_color='white')) \
.add("", data) \
.set_global_opts(legend_opts=opts.LegendOpts(is_show=False),
toolbox_opts=opts.ToolboxOpts(is_show=True)) \
.set_series_opts(label_opts=opts.LabelOpts(formatter="{b}: {c}", font_size=25)) \
.set_colors(colors)
make_snapshot(snapshot, c.render(to_file), svg_name) # 生成svg图片
