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