コード例 #1
0
def load_file():
    with open("去哪儿景点.csv", "r", encoding="utf-8") as csvfile:
        reader = csv.reader(csvfile)
        cityList = []
        #根据规则读取文件中的每一行文字
        for line in reader:
            if len(line[0].split('·')) > 1:
                city = City()
                city.cityName = line[0].split('·')[1]
                city.hotValue = float(line[5].split(' ')[1])
                foundRepeatCity = 0
                #获取城市名字cityName和热度信息hotValue
                #针对城市名字cityName做组合操作,也就是针对其做热点求和
                for originCity in cityList:
                    if originCity.cityName == city.cityName:
                        originCity.hotValue = originCity.hotValue + city.hotValue
                        foundRepeatCity = 1
                        break
                #过滤掉城市中没有在echart 备案信息
                if foundRepeatCity == 0 and Geo().get_coordinate(
                        name=city.cityName) != None and int(
                            city.hotValue) != 0:
                    cityList.append(city)
        # 生成输出信息,用来传入到echart中
        outputGeoData = []
        for city in cityList:
            if Geo().get_coordinate(name=city.cityName) != None and int(
                    city.hotValue) != 0:
                outputGeoDataRecord = (city.cityName, int(city.hotValue) * 5)
                outputGeoData.append(outputGeoDataRecord)
        print(outputGeoData)
    return outputGeoData
コード例 #2
0
def load_file():
    #打开csv文件
    with open("qunar.csv", "r") as csvfile:
        reader = csv.reader(csvfile)
        #开始绘图
        cityList = []
        #根据规则读取文件中的文字
        for line in reader:
            if len(line[0].split('·')) > 1:
                city = City()
                city.cityName = line[0].split('·')[1]
                city.hotValue = float(line[5].split(' ')[1])

                foundRepeatCity = 0
                #获取城市名字和热度信息
                #针对城市名字做联合操作,也就是针对其做热点求和
                for originCity in cityList:
                    if originCity.cityName == city.cityName:
                        originCity.hotValue = originCity.hotValue + city.hotValue
                        foundRepeatCity = 1
                        break
                if foundRepeatCity == 0 and Geo().get_coordinate(
                        name=city.cityName) != None and int(
                            city.hotValue) != 0:
                    cityList.append(city)
        #生成输出信息,传入图标
        outputGeoData = []
        for city in cityList:
            if Geo().get_coordinate(name=city.cityName) != None and round(
                    city.hotValue) != 0:
                outputGeoDataRecord = (city.cityName,
                                       int(city.hotValue) * 1.25)
                outputGeoData.append(outputGeoDataRecord)
    return outputGeoData
コード例 #3
0
def geo_scatter(df) -> Geo:
    if df.empty is False:
        index = df.max() / df.mean() / 50
        geo = (
            Geo()
                .add_schema(maptype="china")
        )
        for item in df.index:
            l = [[item, df.loc[item]]]
            geo.add(series_name=item,
                    data_pair=l,
                    symbol_size=df.loc[item] / df.mean() / index,
                    )
        geo.set_series_opts(label_opts=opts.LabelOpts(is_show=False))
        geo.set_global_opts(toolbox_opts=opts.ToolboxOpts(is_show=True),
                            legend_opts=opts.LegendOpts(is_show=False),
                            tooltip_opts=opts.TooltipOpts(axis_pointer_type='cross'),
                            # visualmap_opts=opts.VisualMapOpts(),
                            # title_opts=opts.TitleOpts(title="Geo-基本示例"),
                            )
    else:
        geo = (
            Geo()
                .add_schema(maptype="china")
        )
    return geo
コード例 #4
0
ファイル: show.py プロジェクト: HuangChenglee/qunar-spider
def load_file():
    # 打开csv文件
    with open('result.csv', 'r', encoding='UTF-8') as csvfile:
        reader = csv.reader(csvfile)
        cityList = []
        # 根据规则读取文件中的每一行文字
        for line in reader:
            if len(line[0].split('·')) > 1:
                city = City()
                city.cityName = line[0].split('·')[1]
                city.hotValue = float(line[5].split(' ')[1])
                foundRepeatCity = 0
                # 获取城市名字cityName和热度信息hotValue
                # 针对城市名字cityName做聚合操作,也就是针对其做热点求和
                for originCity in cityList:
                    if originCity.cityName == city.cityName:
                        originCity.hotValue = originCity.hotValue + city.hotValue
                        foundRepeatCity += 1
                        break
                # 过滤城市列表中 没有在echart 备案过的城市
                if foundRepeatCity == 0 and Geo().get_coordinate(
                        name=city.cityName) is not None and int(
                            city.hotValue) != 0:
                    cityList.append(city)
        # 生成输出信息,用来传入到echarts中
        outputGeoData = []
        for city in cityList:
            if Geo().get_coordinate(name=city.cityName) is not None and int(
                    city.hotValue) != 0:
                outputGeoDataRecord = (city.cityName, int(city.hotValue) * 5)
                outputGeoData.append(outputGeoDataRecord)
        print(outputGeoData)
    return outputGeoData
コード例 #5
0
ファイル: draw_map.py プロジェクト: wxjing4me/DingHelper
    def drawGeoMap(self, aStuData):

        sno, sname = aStuData['info'].split(SPLIT_CHAR)
        sdata = aStuData['data']

        try:
            geo = Geo()

            def add_data(date, location):
                # print(location)
                try:
                    longitude, latitude, address = location
                except:
                    longitude, latitude, address = DEFAULT_Location
                geo.add_coordinate(date, longitude, latitude)
                geo.add(date, [(date, address)], type_=ChartType.EFFECT_SCATTER)

            geo.add_schema(maptype="china")

            # add data
            for date, data in sdata.items():
                add_data(date, data)

            title = f'{sno} {sname} 位置动态'

            geo.set_series_opts(label_opts=opts.LabelOpts(is_show=False))
            geo.set_global_opts(legend_opts=opts.LegendOpts(orient='vertical', pos_left='left', pos_top='10%'), title_opts=opts.TitleOpts(title=title))

            html_path = ospath_join(self.mapsDir, f'{sno}_{sname}.html')
            geo.render(html_path)
        except Exception as e:
            log.error(f'地图生成失败: {sno} {sname} - 可能是包含了文件名不可用的特殊字符', exc_info=True)
            self._signal.emit(f'错误:{sno} {sname} 地图生成失败!可能原因:工号或提交人姓名中包含文件名不可用的特殊字符,如:*。请修改后重试!')
コード例 #6
0
def base_info():
    geo = Geo()
    geo.add_schema(maptype="河南")  # 加入自定义的点,格式为
    # 地图形式 type_=ChartType.HEATMAP
    geo.add("geo", data, type_=ChartType.EFFECT_SCATTER)
    # is_show:是否显示经纬度
    geo.set_series_opts(label_opts=opts.LabelOpts(is_show=False))
    geo.set_global_opts(visualmap_opts=opts.VisualMapOpts(max_=10),
                        title_opts=opts.TitleOpts(title="Geo-河南省地图"))

    return geo
コード例 #7
0
def draw_map(data_pair, data_coordinate) -> Geo:   # ->常常出现在python函数定义的函数名后面,为函数添加元数据,描述函数的返回类型,从而方便开发人员使用。
    g = Geo()
    # 选择要显示的地图
    g.add_schema(maptype="重庆", center=[106.531638,29.561081], itemstyle_opts=opts.ItemStyleOpts(color="#575D57"))
    # 使用add_coordinate(name, lng, lat)添加坐标点和坐标名称
    for item in data_coordinate:
        g.add_coordinate(item['name'], item['lng'], item['lat'])
    # 将数据添加到定义的地图上
    g.add('', data_pair, type_=GeoType.EFFECT_SCATTER, symbol_size=5)                         # type_=ChartType.HEATMAP
    # 设置样式
    g.set_series_opts(label_opts=opts.LabelOpts(is_show=False))\
                                     .set_global_opts(visualmap_opts=opts.VisualMapOpts(min_=60, max_ = 200, is_piecewise=True),title_opts=opts.TitleOpts(title="重庆房源分布图"))
    return g
コード例 #8
0
def base_info():
    print(data)
    geo = Geo()
    geo.add_schema(maptype="china")  # 加入自定义的点,格式为
    # geo.add_coordinate("自定义点", 80.39770014211535,39.90779994986951)
    # 地图形式 type_=ChartType.HEATMAP
    geo.add("geo", data, type_=ChartType.EFFECT_SCATTER)
    # is_show:是否显示经纬度
    geo.set_series_opts(label_opts=opts.LabelOpts(is_show=False))
    geo.set_global_opts(visualmap_opts=opts.VisualMapOpts(),
                        title_opts=opts.TitleOpts(title="Geo-基本示例"))

    return geo
コード例 #9
0
def create_city_map(df):
    df1 = df[df["country"] == "中国"]
    df1 = df1.copy()
    df1["city"] = df1["city"].str.replace("市", "")

    df_num = df1.groupby("city")["city"].agg(
        count="count").reset_index().sort_values(by="count", ascending=False)
    df_city = df_num["city"].values.tolist()
    df_count = df_num["count"].values.tolist()

    # 初始化配置
    geo = Geo(init_opts=opts.InitOpts(width="800px", height="400px"))
    # 中国地图
    geo.add("", [list(z) for z in zip(df_city, df_count)], "china")
    # 设置全局配置项,标题、工具箱(下载图片)、颜色图例
    geo.set_global_opts(
        title_opts=opts.TitleOpts(title="抖音大V城市分布情况",
                                  pos_left="center",
                                  pos_top="0"),
        toolbox_opts=opts.ToolboxOpts(is_show=True,
                                      feature={"saveAsImage": {}}),
        # 设置数值范围0-600,is_piecewise标签值连续
        visualmap_opts=opts.VisualMapOpts(is_piecewise=True))
    geo.set_series_opts(label_opts=opts.LabelOpts(is_show=False))
    map.render("抖音大V城市分布情况.html")
コード例 #10
0
ファイル: ShowData.py プロジェクト: vin-zhou/CrawlerPlay
def load_file():
    with open("qunar.csv", "r") as csvfile:
        reader = csv.reader(csvfile)
        city_list = []
        # 逐行读取
        for line in reader:
            if len(line[0].split('·')) > 1:
                city = City()
                city.city_name = line[0].split('·')[1]
                city.hot_value = float(line[5].split(' ')[1])
                found_repeat_city = 0
                # 按城市热点求和
                for origin_city in city_list:
                    if origin_city.city_name == city.city_name:
                        origin_city.hot_value += city.hot_value
                        found_repeat_city = 1
                        break
                # 过滤掉城市没有在echart备案的信息
                if found_repeat_city == 0 \
                        and Geo().get_coordinate(name=city.city_name) is not None \
                        and int(city.hot_value) != 0:
                    city_list.append(city)
        # 生成输入信息,用来传入到echart中
        output_geo_data = []
        for city in city_list:
            output_geo_data_record = (city.city_name, int(city.hot_value * 5))
            output_geo_data.append(output_geo_data_record)
        print(output_geo_data)
    return output_geo_data
コード例 #11
0
def map_985_211():
    global wid, hei
    df = pd.read_csv('data/211_985.csv')  #前39所为985
    df_985 = df.iloc[:39]
    df_211 = df.iloc[39:]

    df_985_num = df_985.groupby('所在地').count().iloc[:, 0]
    df_211_num = df_211.groupby('所在地').count().iloc[:, 0]

    c = (
        Geo(init_opts=opts.InitOpts(width=wid, height=hei)).add_schema(
            maptype="china").add("985",
                                 list(df_985_num.iteritems()),
                                 type_=ChartType.HEATMAP).add(
                                     "211",
                                     list(df_211_num.iteritems()),
                                     type_=ChartType.HEATMAP).
        set_global_opts(
            title_opts=opts.TitleOpts(title="985_211全国分布"),
            visualmap_opts=opts.VisualMapOpts(max_=5),
            #     visualmap_opts=opts.VisualMapOpts(is_piecewise=True,pieces=[
            #   {"min":10, "max": 30},
            #   {"min": 5, "max": 10},
            # {"value": 4},
            #   {"value": 3},
            # {"min": 2,"max": 2},
            #   {"value": 1, "label": '1 一枝独秀', "color": 'grey'},
            # ]
            # )
        ))
    return c
コード例 #12
0
ファイル: geo_charts.py プロジェクト: zdj-j/Job_Spider
def geo_charts(content):
    """绘制世界地图"""
    zip_data = content[0]
    start_city = content[1]
    geo = (Geo().add_schema(
        maptype="china",
        itemstyle_opts=opts.ItemStyleOpts(color="#323c48",
                                          border_color="#00000"),
    ).add(
        "",
        data_pair=zip_data,
        type_=ChartType.EFFECT_SCATTER,
        color="white",
    ).add(
        "geo",
        data_pair=start_city,
        type_=GeoType.LINES,
        effect_opts=opts.EffectOpts(symbol=SymbolType.RECT,
                                    symbol_size=6,
                                    color="yellow",
                                    is_show=True),
        linestyle_opts=opts.LineStyleOpts(curve=0.2),
    ).set_series_opts(label_opts=opts.LabelOpts(
        is_show=False)).set_global_opts(title_opts=opts.TitleOpts(
            title="Python开发工程师可视化界面")))
    return geo
コード例 #13
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def geo_lines_background() -> Geo:
    c = (
        Geo()
        .add_schema(
            maptype="china",
            itemstyle_opts=opts.ItemStyleOpts(color="#323c48", border_color="#111"),
        )
        .add(
            "",
            [("广州", 55), ("北京", 66), ("杭州", 77), ("重庆", 88)],
            type_=ChartType.EFFECT_SCATTER,
            color="white",
        )
        .add(
            "geo",
            [("广州", "上海"), ("广州", "北京"), ("广州", "杭州"), ("广州", "重庆")],
            type_=ChartType.LINES,
            effect_opts=opts.EffectOpts(
                symbol=SymbolType.ARROW, symbol_size=6, color="blue"
            ),
            linestyle_opts=opts.LineStyleOpts(curve=0.2),
        )
        .set_series_opts(label_opts=opts.LabelOpts(is_show=False))
        .set_global_opts(title_opts=opts.TitleOpts(title="Geo-Lines-background"))
    )
    return c
コード例 #14
0
ファイル: geo_lines.py プロジェクト: pccode21/Module
def geo_lines() -> Geo:
    c = (
        Geo()
        .add_schema(maptype="china")
        .add(
            "",
            [("北京", 1), ("重庆", 2), ("长沙", 3), ("长春", 4), ("成都", 5), ("大连", 6), ("广州", 7), ("贵阳", 8),
            ("合肥", 9), ("杭州", 10), ("哈尔滨", 11), ("海口", 12), ("济南", 13), ("昆明", 14), ("柳州", 15), ("绵阳", 16),
            ("潞西市", 17), ("南宁", 18), ("南京", 19), ("沈阳", 20), ("三亚", 21), ("上海", 22), ("天津", 23), ("徐州", 24),
            ("义乌", 25), ("郑州", 26), ("张家界", 27)],
            type_=ChartType.EFFECT_SCATTER,
            color="#ffa022"
        )
        .add(
            "",
            [("揭阳", "北京"), ("揭阳", "重庆"), ("揭阳", "长沙"), ("揭阳", "长春"), ("揭阳", "成都"),
            ("揭阳", "大连"), ("揭阳", "广州"), ("揭阳", "贵阳"), ("揭阳", "合肥"), ("揭阳", "杭州"),
            ("揭阳", "哈尔滨"), ("揭阳", "海口"), ("揭阳", "济南"), ("揭阳", "昆明"), ("揭阳", "柳州"),
            ("揭阳", "绵阳"), ("揭阳", "潞西市"), ("揭阳", "南宁"), ("揭阳", "南京"), ("揭阳", "沈阳"),("揭阳", "三亚"),
            ("揭阳", "上海"), ("揭阳", "天津"), ("揭阳", "徐州"),("揭阳", "义乌"),("揭阳", "郑州"), ("揭阳", "张家界")],
            type_=ChartType.LINES,
            effect_opts=opts.EffectOpts(
                symbol=symbol_list[0], symbol_size=15, color='#a6c84c', period=6, trail_length=0, is_show=True
                # 特效图形的标记。有 RECT', 'DIAMOND', 'ARROW' 可选
            ),
            linestyle_opts=opts.LineStyleOpts(curve=0.2, color='#46bee9', width=1, opacity=0.5),
        )
        .set_series_opts(label_opts=opts.LabelOpts(is_show=False))
        .set_global_opts(title_opts=opts.TitleOpts(title="揭阳出发国内航线", subtitle="数能工作室制作", pos_left="center",
                        title_textstyle_opts=opts.TextStyleOpts(color='black',font_size=20, font_weight="bold"),
                        subtitle_textstyle_opts=opts.TextStyleOpts(color='black',font_size=15),item_gap=15))
        )
    return c
コード例 #15
0
def geo_sichuan(title) -> Geo:
    c = (Geo().add_schema(maptype='四川').add(
        title, [list(z) for z in zip(Data.sichuan_city, Data.values())],
        type_=ChartType.HEATMAP).set_global_opts(
            visualmap_opts=opts.VisualMapOpts(max_=42, is_piecewise=True),
            title_opts=opts.TitleOpts(title='四川温度变化情况')))
    return c
コード例 #16
0
ファイル: LgCrawler.py プロジェクト: zhuby1973/map
    def city(self):

        sql = 'select city, count(1) counts from jobs group by city'
        results = self.query(sql)

        c = (Geo().add_schema(maptype="china").add(
            "城市热力图",
            list(results),
            type_=ChartType.HEATMAP,
        ).set_series_opts(label_opts=opts.LabelOpts(
            is_show=False)).set_global_opts(
                visualmap_opts=opts.VisualMapOpts(), ).render("拉钩城市热力图.html"))

        sql = 'select city,counts from (select city, count(1) counts from jobs group by city) a order by counts desc limit 20'
        results = self.query(sql)
        citys = []
        values = []
        for row in results:
            citys.append(row[0])
            values.append(row[1])
        c = (Bar().add_xaxis(citys).add_yaxis(
            "各城市的招聘数量 Top 20",
            values).set_global_opts(xaxis_opts=opts.AxisOpts(
                name_rotate=60, name="城市",
                axislabel_opts={"rotate": 45})).render("拉钩城市招聘图.html"))
コード例 #17
0
def hotpoint(movie_name):
    #读取城市数据
    with open(movie_name + '\\' + movie_name + 'dbplaces.txt',
              'r+',
              encoding='utf-8-sig') as f:
        heat_1 = f.read()
        for i in heat_1:
            if i in string.punctuation:
                heat_1 = heat_1.replace(i, "")
        heat = heat_1.split()
        heat_dic = Counter(heat)
    #整理数据
    heat_list = []
    for place, times in heat_dic.items():
        c_word = (place, times)
        heat_list.append(c_word)
    #出图
    heat_map = (Geo().add_schema(maptype="china").add(
        "", heat_list).set_series_opts(label_opts=opts.LabelOpts(
            is_show=False)).set_global_opts(
                visualmap_opts=opts.VisualMapOpts(),
                title_opts=opts.TitleOpts(title=movie_name + " 豆瓣观影热点图",
                                          subtitle=None),
                toolbox_opts=opts.ToolboxOpts(is_show=True)))

    heat_map.render(movie_name + '\\' + movie_name + 'dbhotpoint.html')
コード例 #18
0
    def city_info(self):
        dict_city = dict()
        for friend in self.friends:
            key = friend['City']
            if key not in dict_city.keys():
                dict_city[key] = 1
            else:
                dict_city[key] += 1
        city = []
        # max_num = 0  # 某个城市中最多的人数
        for key, value in dict_city.items():
            # 其他地区
            if len(key) == 0:
                continue
            # 过滤英文等非市级
            if len(key) >= 3:
                continue
            city.append(tuple((key, value)))
            # if value > max_num:
            #     max_num = value

        # 地图标注
        # geo = Geo("微信好友城市分布图", "data from WeChat", title_color="#fff", title_pos="center",
        #           width=1200, height=600, background_color='#404a59')
        # attr, value = geo.cast(city)
        # geo.add("", attr, value, visual_range=[0, 50], visual_text_color="#fff", symbol_size=15, is_visualmap=True)
        # geo.show_config()
        geo = (Geo().add_schema(maptype="china").add("人数", ))
        geo.render("city.html")
コード例 #19
0
ファイル: app.py プロジェクト: LEETONGTONG/Python_project
def geo_base() -> Geo:
    c = (Geo().add_schema(
        maptype="china",
        itemstyle_opts=opts.ItemStyleOpts(
            color="#323c48", border_color="#111")).add(
                "人/平方千米", zip(list(df.地区), list(df.人口密度))).set_series_opts(
                    label_opts=opts.LabelOpts(is_show=False)).set_global_opts(
                        title_opts=opts.TitleOpts(title="2018年36个主要城市的人口密度情况"),
                        visualmap_opts=opts.VisualMapOpts(max_=2306.6,
                                                          min_=18.7,
                                                          is_piecewise=True,
                                                          pieces=[{
                                                              'min':
                                                              924,
                                                              'max':
                                                              2306.593060
                                                          }, {
                                                              'min':
                                                              602,
                                                              'max':
                                                              923.156006
                                                          }, {
                                                              'min':
                                                              362,
                                                              'max':
                                                              600.689035
                                                          }, {
                                                              'min':
                                                              18.781760,
                                                              'max':
                                                              361.142947
                                                          }])))
    return c
コード例 #20
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def show_covid():
    covid = (Geo().add_schema(maptype="澳大利亚").add_coordinate(
        "Sydney", 151.207,
        -33.868).add_coordinate("Melbourne", 144.963, -37.814).add_coordinate(
            "Brisbane", 153.028,
            -27.468).add_coordinate("Perth", 115.861, -31.952).add_coordinate(
                "Adelaide", 138.599, -34.929).add_coordinate(
                    "Cold Coast", 153.431,
                    -28).add_coordinate("Newcastle", 151.78, -32.93).add(
                        "geo",
                        [list(z) for z in zip(geo_city, geo_cov)
                         ]).set_series_opts(label_opts=opts.LabelOpts(
                             is_show=False)).set_global_opts(
                                 visualmap_opts=opts.VisualMapOpts(
                                     type_="size",
                                     max_=500,
                                     min_=0,
                                     range_text=[
                                         'Highly discussed', 'Rarely discussed'
                                     ]),
                                 title_opts=opts.TitleOpts(
                                     title="Twitter Covid Map"),
                                 legend_opts=opts.LegendOpts(is_show=False)))

    return covid
コード例 #21
0
ファイル: myCharts.py プロジェクト: TeslaHou/Export_pdf
 def geoHeatMap(self,area=None,data=None,maptype='china',title='热力图示例',subtitle='副标题'):
     '''
     热力图
     param area: 省份的列表   type list  例如 ['吉林', '辽宁', '河北', '河南']
     param data: 对应的值     type list  例如 [63,10,2,30]
     应用场景  省份或者城市排行榜
     # ['黑龙江', '吉林', '辽宁', '河北', '河南', '山东', '山西', '安徽', '江西', '江苏', '浙江', '福建', '台湾', '广东',
     # '湖南', '湖北', '海南', '云南', '贵州', '四川', '青海', '甘肃', '陕西', '内蒙古', '新疆', '广西', '宁夏', '西藏',
     # '北京','天津','上海','重庆','香港','澳门']
     '''
     area = area or Faker.provinces
     data = data or Faker.values()
     c = (
         Geo()
         .add_schema(maptype=maptype)
         .add(
             "geo",
             [list(z) for z in zip(area, data)],
             type_=ChartType.HEATMAP,
         )
         # .set_series_opts(label_opts=opts.LabelOpts(is_show=True))
         .set_series_opts(label_opts=opts.LabelOpts(is_show=False))
         .set_global_opts(
             visualmap_opts=opts.VisualMapOpts(),
             title_opts=opts.TitleOpts(title=title,subtitle=subtitle),
         )
     )
     chart_name = f'static/chart{self.index}_heatmap'
     make_snapshot(snapshot,c.render(f'{chart_name}.html'),f'{chart_name}.png',is_remove_html=True)
     self.index += 1
コード例 #22
0
def geo_getmap() -> Geo:

    c = (
        Geo().add_schema(
            maptype="china",
            itemstyle_opts=opts.ItemStyleOpts(color="#323c48",
                                              border_color="#111"),
        ).add(
            "",
            allcases,
            type_=ChartType.EFFECT_SCATTER,
            # symbol_size="size",
            color="white",
        ).add(
            "",
            traces,
            type_=ChartType.LINES,
            # effect_opts=opts.EffectOpts(
            #     symbol=SymbolType.ARROW, symbol_size=6, color="red"
            # ),
            linestyle_opts=opts.LineStyleOpts(curve=0.2),
        ).set_series_opts(label_opts=opts.LabelOpts(
            is_show=False)).set_global_opts(title_opts=opts.TitleOpts(
                title="2019-nCoV Trace Map(China)")))
    make_snapshot(snapshot, c.render(), "tracemap.png")
コード例 #23
0
def ocean_export_lines():
    data = pd.read_csv(r"F:\ftp\erbranch\OEin24hrs\data.csv")
    chargeable_weight = []
    origin_dest = []
    for index, row in data.iterrows():
        chargeable_weight.append([row['DEST CITY'], row['CW']])
        origin_dest.append([row['ORIGIN CITY'], row['DEST CITY']])
    min_data = min([d[1] for d in chargeable_weight])
    max_data = max([d[1] for d in chargeable_weight])
    c = (
        Geo().add_schema(maptype="world", is_roam=False).add_coordinate_json(
            json_file=current_app.config['STATIC_PATH'] + r"\world_cities.json"
        ).add(
            "Chargeable Weight",
            chargeable_weight,
            type_=GeoType.EFFECT_SCATTER,
        ).set_series_opts(label_opts=opts.LabelOpts(is_show=False)).add(
            "geo",
            origin_dest,
            type_=GeoType.LINES,
            # is_polyline = True,
            # effect_opts=opts.EffectOpts(symbol=SymbolType.DIAMOND, symbol_size=5, color="blue",),
            linestyle_opts=opts.LineStyleOpts(curve=0.3,
                                              width=2,
                                              opacity=0.2,
                                              color='Red'),
        ).set_series_opts(label_opts=opts.LabelOpts(
            is_show=False)).set_global_opts(title_opts=opts.TitleOpts(
                title="TSN Ocean Export LINES in 24 Hrs"),
                                            visualmap_opts=opts.VisualMapOpts(
                                                min_=min_data, max_=max_data)))
    return render_template('dashboard/ocean_export_lines.html',
                           geo=c.dump_options())
コード例 #24
0
ファイル: run.py プロジェクト: qimiao1/scapy
def geo_line() -> Bar:
    db = getattr(g, "_db", None)
    col = db.trafficmodels
    users = col.distinct("user")
    list_place = []
    for user in users:
        place = col.find_one({"user": user}, {"place": 1})["place"]
        places = get_all_IP(user)

        for p in places:
            list_place.append([place, p])
    c = (Geo().add_schema(maptype="world").add_coordinate_json(
        json_file="world_country.json").add(
            "交互图",
            list_place,
            type_=ChartType.LINES,
            effect_opts=opts.EffectOpts(symbol=SymbolType.DIAMOND,
                                        symbol_size=6,
                                        color="blue"),
            linestyle_opts=opts.LineStyleOpts(
                curve=0.2,
                opacity=0.2,
            )).set_series_opts(label_opts=opts.LabelOpts(
                is_show=False)).set_global_opts(
                    title_opts=opts.TitleOpts(title="总交互图"),
                    tooltip_opts=opts.TooltipOpts(is_show=True)))
    return c
コード例 #25
0
ファイル: test_geo.py プロジェクト: DrLiLab/utiChartsOfChina
def _geo_chart() -> Geo:
    return (
        Geo()
        .add_schema(maptype="china", center=[39, 117.7], zoom=9)
        .add("geo", [list(z) for z in zip(Faker.provinces, Faker.values())])
        .set_global_opts(visualmap_opts=opts.VisualMapOpts())
    )
コード例 #26
0
 def geoLineCity(self, data) -> Geo:
     # 指定城市航班连接城市图
     count = len(data[0])
     city_Geoline = (
         Geo(init_opts=opts.InitOpts(
             width='1000px', height='500px')).add_schema(
                 maptype="china", zoom=1.1).add_coordinate_json(
                     self.geo_file).add("",
                                        data[1],
                                        symbol_size=6,
                                        color='#725e82')  # 标记点大小与颜色
         .add(
             "",
             data[0],
             type_=ChartType.LINES,
             linestyle_opts=opts.LineStyleOpts(curve=0.1,
                                               width=1,
                                               color='#1685a9'),  # 连线的宽度与颜色
             effect_opts=opts.EffectOpts(is_show=False))  # 关闭涟漪效果
         .set_series_opts(label_opts=opts.LabelOpts(
             is_show=False)).set_global_opts(title_opts=opts.TitleOpts(
                 title="{}民航班机航线图".format(data[0][0][0]),
                 subtitle='{},{}共有直飞全国{}个城市的航班'.format(
                     self.today_ymd, data[0][0][0], count))))
     return city_Geoline
def workarea_chart(df):
    # 统计各地区出现次数, 并转换为元组的形式
    data = Counter(df.workarea).most_common()
    print(data)
    # 生成地理坐标图
    # geo = Geo("岗位各地区需求量", title_color="#fff", title_pos="center", width=1200, height=600, background_color='#404a59')
    # attr, value = geo.cast(data)
    # print(attr)
    # print(value)
    # 添加数据点
    # # type="effectScatter", is_random=True, effect_scale=5  使点具有发散性
    # geo.add('', attr, value, type="effectScatter", visual_range=[0, 100], visual_text_color='#fff', symbol_size=5, is_visualmap=True, is_piecewise=True)
    # geo.show_config()
    # geo.render()
    geo = (
        Geo()
            .add_schema(maptype="china")
            .add("", data)
            .set_series_opts(label_opts=opts.LabelOpts(is_show=False))
            .set_global_opts(
            visualmap_opts=opts.VisualMapOpts(),
            title_opts=opts.TitleOpts(title="岗位城市分布图"),
        )
    )
    geo.render("./chart/workarea_chart.html")
コード例 #28
0
ファイル: 可视化.py プロジェクト: 18208107/flight
def geo_lines() -> Geo:
    c = (
        Geo(
                init_opts=opts.InitOpts(width="1000px",height="700px",theme=ThemeType.PURPLE_PASSION)
        )
        .add_schema(maptype="china")
        .add(
            "航班数量",
           df2,
            type_=ChartType.EFFECT_SCATTER,
            #color="#ffa022"
        )
        .add(
            "航线",
            df1,
            type_=ChartType.LINES,
            effect_opts=opts.EffectOpts(
                symbol=symbol_list[0], symbol_size=15, period=6, trail_length=0, is_show=True
            ),
            linestyle_opts=opts.LineStyleOpts(curve=0.2,  width=1, opacity=0.5),
        )
        .set_series_opts(label_opts=opts.LabelOpts(is_show=False))
        .set_global_opts(title_opts=opts.TitleOpts(title="国内航线", #pos_left="center",
                        title_textstyle_opts=opts.TextStyleOpts(font_size=30, font_weight="bold"),
                        #subtitle_textstyle_opts=opts.TextStyleOpts(color='black',font_size=15)
                                                   ))
        )
コード例 #29
0
ファイル: testPyecharts.py プロジェクト: 13033266796/Air
def geo_base() -> Geo:
    citys = [
        '北京', '天津', '上海', '重庆', '石家庄', '太原', '西安', '济南', '长春', '哈尔滨', '南京',
        '杭州', '合肥', '南昌', '福州', '武汉', '长沙', '成都', '贵阳', '昆明', '广州', "郑州", "沈阳",
        '海口', '兰州', '西宁', '呼和浩特', '乌鲁木齐', '拉萨', '南宁', '银川'
    ]
    a_list = [(citys[i], [i, i * 2]) for i in range(len(citys))]
    # print(a_list)
    c = (
        Geo(init_opts=opts.InitOpts(theme=ThemeType.WESTEROS))  # 地图主题
        .add_schema(
            maptype="china",
            is_roam=False,
            itemstyle_opts=opts.ItemStyleOpts(area_color='#E6E6FA'))  # 地图颜色
        .add("geo",
             [list(z) for z in zip(Faker.provinces, Faker.values())]).add(
                 "geo", [('南昌', 12), ('北京', 12), ('天津', 12), ('拉萨', 12),
                         ('呼和浩特', 12), ('桂林', 12), ('沈阳', 12), ('乌鲁木齐', 12),
                         ('海口', 12)],
                 type_="effectScatter",
                 itemstyle_opts=opts.ItemStyleOpts(
                     border_color='#8A2BE2'))  # 点的颜色
        .set_series_opts(label_opts=opts.LabelOpts(
            is_show=False)).set_global_opts(
                visualmap_opts=opts.VisualMapOpts(series_index=[0][0]),
                title_opts=opts.TitleOpts(title="Geo-基本示例"),
            ))
    return c
コード例 #30
0
 def visual(self):
     with open('price.json', 'r', encoding='utf-8') as f:
         data = json.loads(f.read())
     for n in data:
         price = data[n]['price']
         if not price.isdigit():     # 清除价格不规范的数据
             continue
         else:
             self.list_n.append((n, int(price)))
     house_map = (
         Geo(init_opts=opts.InitOpts(width='1200px', height='500px'))
         .add_schema(maptype="沈阳", center=[123.434039, 41.798102], zoom=6)
         # 从json文件导入坐标值
         .add_coordinate_json(r'position.json')
         .add('', self.list_n, symbol_size=10, color='#f20c00')
         .set_series_opts(label_opts=opts.LabelOpts(is_show=False))
         # 设置全局配置项
         .set_global_opts
         (
             visualmap_opts=opts.VisualMapOpts(type_='color', min_=5000, max_=18000),
             title_opts=opts.TitleOpts(title='沈阳市楼盘分布图',
                                       subtitle='数据来源:贝壳网(2020-01) 共{}个楼盘'.format(len(self.list_n))),
         )
         # 设置系列配置项
         .set_series_opts(label_opts=opts.LabelOpts(is_show=False))
     )
     return house_map