oppot703天气预报总是显示无可用天气数据_百度知道
oppot703天气预报总是显示无可用天气数据
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出门在外也不愁当前位置：
＞＞＞中央电视台在今年六月份某一天发布的天气预报显示我国内地31个直..
中央电视台在今年六月份某一天发布的天气预报显示我国内地31个直辖市和省会城市的最高气温（℃）情况如下表：那么能够显示这些城市在这一天数据的分布情况，可绘制（ ）A．条形图B．扇形图C．折线图D．直方图
题型：单选题难度：中档来源：不详
根据统计图各自的特点，结合题意，要反映这些城市在这一天数据的分布情况，可绘制条形图．故选A．
马上分享给同学
据魔方格专家权威分析，试题“中央电视台在今年六月份某一天发布的天气预报显示我国内地31个直..”主要考查你对&&中位数和众数，频数与频率&&等考点的理解。关于这些考点的“档案”如下：
现在没空？点击收藏，以后再看。
因为篇幅有限，只列出部分考点，详细请访问。
中位数和众数频数与频率
中位数：一般地，n个数据按大小顺序排列，处于最中间位置的一个数据（或最中间位置的两个数据的平均数）叫这组数据的中位数。 众数：在一组数据中，出现次数最多的数据。 中位数的位置：当样本数为奇数时，中位数=(N+1)/2;当样本数为偶数时，中位数为N/2与1+N/2的均值众数性质：用众数代表一组数据，可靠性较差，不过，众数不受极端数据的影响，并且求法简便。在一组数据中，如果个别数据有很大的变动，选择中位数表示这组数据的“集中趋势”就比较适合。当数值或被观察者没有明显次序（常发生于非数值性资料）时特别有用，由于可能无法良好定义算术平均数和中位数。例子：{鸡、鸭、鱼、鱼、鸡、鱼}的众数是鱼。众数算出来是销售最常用的，代表最多的&众数是在一组数据中,出现次数最多的数据&两组数据中,都是1,2出现次数最多&所以1,2是众数&众数： 一般来说，一组数据中，出现次数最多的数就叫这组数据的众数。 例如：1，2，3，3，4的众数是3。&但是，如果有两个或两个以上个数出现次数都是最多的，那么这几个数都是这组数据的众数。 例如：1，2，2，3，3，4的众数是2和3。 还有，如果所有数据出现的次数都一样，那么这组数据没有众数。 例如：1，2，3，4，5没有众数。在高斯分布中，众数位于峰值。平均数、中位数和众数的特征： （1）平均数、中位数、众数都是表示一组数据“平均水平”的平均数。 （2）平均数能充分利用数据提供的信息，在生活中较为常用，但它容易受极端数字的影响，且计算较繁。 （3）中位数的优点是计算简单，受极端数字影响较小，但不能充分利用所有数字的信息。 中位数算出来可避免极端数据，代表着数据总体的中等情况。（4）众数的可靠性较差，它不受极端数据的影响，求法简便，当一组数据中个别数据变动较大时，适宜选择众数来表示这组数据的“集中趋势”。平均数、中位数和众数异同：一、相同点平均数、中位数和众数这三个统计量的相同之处主要表现在：都是来描述数据集中趋势的统计量；都可用来反映数据的一般水平；都可用来作为一组数据的代表。二、不同点它们之间的区别，主要表现在以下方面。1、定义不同平均数：一组数据的总和除以这组数据个数所得到的商叫这组数据的平均数。中位数：将一组数据按大小顺序排列，处在最中间位置的一个数叫做这组数据的中位数 。众数：在一组数据中出现次数最多的数叫做这组数据的众数。2、求法不同平均数：用所有数据相加的总和除以数据的个数,需要计算才得求出。中位数：将数据按照从小到大或从大到小的顺序排列，如果数据个数是奇数，则处于最中间位置的数就是这组数据的中位数；如果数据的个数是偶数，则中间两个数据的平均数是这组数据的中位数。它的求出不需或只需简单的计算。众数：一组数据中出现次数最多的那个数，不必计算就可求出。3、个数不同在一组数据中，平均数和中位数都具有惟一性，但众数有时不具有惟一性。在一组数据中，可能不止一个众数，也可能没有众数。4、呈现不同平均数：是一个“虚拟”的数，是通过计算得到的，它不是数据中的原始数据。中位数：是一个不完全“虚拟”的数。当一组数据有奇数个时，它就是该组数据排序后最中间的那个数据，是这组数据中真实存在的一个数据；但在数据个数为偶数的情况下，中位数是最中间两个数据的平均数，它不一定与这组数据中的某个数据相等，此时的中位数就是一个虚拟的数。众& 数：是一组数据中的原数据 ，它是真实存在的。5、代表不同平均数：反映了一组数据的平均大小，常用来一代表数据的总体 “平均水平”。中位数：像一条分界线，将数据分成前半部分和后半部分，因此用来代表一组数据的“中等水平”。众数：反映了出现次数最多的数据，用来代表一组数据的“多数水平”。这三个统计量虽反映有所不同，但都可表示数据的集中趋势，都可作为数据一般水平的代表。6、特点不同平均数：与每一个数据都有关,其中任何数据的变动都会相应引起平均数的变动。主要缺点是易受极端值的影响，这里的极端值是指偏大或偏小数，当出现偏大数时，平均数将会被抬高，当出现偏小数时，平均数会降低。中位数：与数据的排列位置有关，某些数据的变动对它没有影响；它是一组数据中间位置上的代表值，不受数据极端值的影响。众数：与数据出现的次数有关，着眼于对各数据出现的频率的考察，其大小只与这组数据中的部分数据有关，不受极端值的影响,其缺点是具有不惟一性，一组数据中可能会有一个众数，也可能会有多个或没有 。7、作用不同平均数：是统计中最常用的数据代表值，比较可靠和稳定，因为它与每一个数据都有关，反映出来的信息最充分。平均数既可以描述一组数据本身的整体平均情况，也可以用来作为不同组数据比较的一个标准。因此，它在生活中应用最广泛，比如我们经常所说的平均成绩、平均身高、平均体重等。中位数：作为一组数据的代表，可靠性比较差，因为它只利用了部分数据。但当一组数据的个别数据偏大或偏小时，用中位数来描述该组数据的集中趋势就比较合适。众数：作为一组数据的代表，可靠性也比较差，因为它也只利用了部分数据。。在一组数据中，如果个别数据有很大的变动，且某个数据出现的次数最多，此时用该数据（即众数）表示这组数据的“集中趋势”就比较适合。中位数、众数的求法： 中位数：①将数据按大小顺序排列；②当数据个数为奇数时，中间的那个数据就是中位数；当数据个数为偶数时，居于中间的两个数据的平均数才是中位数。 众数：找出频数最多的数据，若几个数据频数最多且相同，此时众数就是这几个数据。 频数：一般我们称落在不同小组中的数据个数为该组的频数。频率：频数与数据总数的比值为频率。频率反映了各组频数的大小在总数中所占的分量。频数：在一组依大小顺序排列的测量值中，当按一定的组距将其分组时出现在各组内的测量值的数目。如有一组测量数据，数据的总个数N=148最小的测量值xmin=0.03，最大的测量值xmax=31.67，按组距为△x=3.000将148个数据分为11组，其中分布在15.05～18.05范围内的数据有26个，则称该数据组的频数为26。
频率：如在979324中，‘9’出现的频数是3，出现的频率是3/18=16.7%频数也称“次数”，对总数据按某种标准进行分组，统计出各个组内含个体的个数。而频率则每个小组的频数与数据总数的比值。 在变量分配数列中，频数（频率）表明对应组标志值的作用程度。频数（频率）数值越大表明该组标志值对于总体水平所起的作用也越大，反之，频数（频率）数值越小，表明该组标志值对于总体水平所起的作用越小。
发现相似题
与“中央电视台在今年六月份某一天发布的天气预报显示我国内地31个直..”考查相似的试题有：
148059197056418252364909147346151762嗨 朋友 欢迎你来到 龙果果的圈圈！要“知其然知其所以然”才能每天进步！
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首先看下官方给出的三个数据接口:
接口地址：
全国各城市代码如下
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"编码": ""
"市名": "兴义",
"编码": ""
"市名": "铜仁",
"编码": ""
"市名": "毕节",
"编码": ""
"市名": "六盘水",
"编码": ""
"市名": "遵义",
"编码": ""
"市名": "凯里",
"编码": ""
"省": "云南",
"市名": "昆明",
"编码": ""
"市名": "红河",
"编码": ""
"市名": "文山",
"编码": ""
"市名": "玉溪",
"编码": ""
"市名": "楚雄",
"编码": ""
"市名": "普洱",
"编码": ""
"市名": "昭通",
"编码": ""
"市名": "临沧",
"编码": ""
"市名": "怒江",
"编码": ""
"市名": "香格里拉",
"编码": ""
"市名": "丽江",
"编码": ""
"市名": "德宏",
"编码": ""
"市名": "景洪",
"编码": ""
"市名": "大理",
"编码": ""
"市名": "曲靖",
"编码": ""
"市名": "保山",
"编码": ""
"省": "内蒙古",
"市名": "呼和浩特",
"编码": ""
"市名": "乌海",
"编码": ""
"市名": "集宁",
"编码": ""
"市名": "通辽",
"编码": ""
"市名": "阿拉善左旗",
"编码": ""
"市名": "鄂尔多斯",
"编码": ""
"市名": "临河",
"编码": ""
"市名": "锡林浩特",
"编码": ""
"市名": "呼伦贝尔",
"编码": ""
"市名": "乌兰浩特",
"编码": ""
"市名": "包头",
"编码": ""
"市名": "赤峰",
"编码": ""
"省": "江西",
"市名": "南昌",
"编码": ""
"市名": "上饶",
"编码": ""
"市名": "抚州",
"编码": ""
"市名": "宜春",
"编码": ""
"市名": "鹰潭",
"编码": ""
"市名": "赣州",
"编码": ""
"市名": "景德镇",
"编码": ""
"市名": "萍乡",
"编码": ""
"市名": "新余",
"编码": ""
"市名": "九江",
"编码": ""
"市名": "吉安",
"编码": ""
"省": "湖北",
"市名": "武汉",
"编码": ""
"市名": "黄冈",
"编码": ""
"市名": "荆州",
"编码": ""
"市名": "宜昌",
"编码": ""
"市名": "恩施",
"编码": ""
"市名": "十堰",
"编码": ""
"市名": "神农架",
"编码": ""
"市名": "随州",
"编码": ""
"市名": "荆门",
"编码": ""
"市名": "天门",
"编码": ""
"市名": "仙桃",
"编码": ""
"市名": "潜江",
"编码": ""
"市名": "襄樊",
"编码": ""
"市名": "鄂州",
"编码": ""
"市名": "孝感",
"编码": ""
"市名": "黄石",
"编码": ""
"市名": "咸宁",
"编码": ""
"省": "四川",
"市名": "成都",
"编码": ""
"市名": "自贡",
"编码": ""
"市名": "绵阳",
"编码": ""
"市名": "南充",
"编码": ""
"市名": "达州",
"编码": ""
"市名": "遂宁",
"编码": ""
"市名": "广安",
"编码": ""
"市名": "巴中",
"编码": ""
"市名": "泸州",
"编码": ""
"市名": "宜宾",
"编码": ""
"市名": "内江",
"编码": ""
"市名": "资阳",
"编码": ""
"市名": "乐山",
"编码": ""
"市名": "眉山",
"编码": ""
"市名": "凉山",
"编码": ""
"市名": "雅安",
"编码": ""
"市名": "甘孜",
"编码": ""
"市名": "阿坝",
"编码": ""
"市名": "德阳",
"编码": ""
"市名": "广元",
"编码": ""
"市名": "攀枝花",
"编码": ""
"省": "宁夏",
"市名": "银川",
"编码": ""
"市名": "中卫",
"编码": ""
"市名": "固原",
"编码": ""
"市名": "石嘴山",
"编码": ""
"市名": "吴忠",
"编码": ""
"省": "青海",
"市名": "西宁",
"编码": ""
"市名": "黄南",
"编码": ""
"市名": "海北",
"编码": ""
"市名": "果洛",
"编码": ""
"市名": "玉树",
"编码": ""
"市名": "海西",
"编码": ""
"市名": "海东",
"编码": ""
"市名": "海南",
"编码": ""
"省": "山东",
"市名": "济南",
"编码": ""
"市名": "潍坊",
"编码": ""
"市名": "临沂",
"编码": ""
"市名": "菏泽",
"编码": ""
"市名": "滨州",
"编码": ""
"市名": "东营",
"编码": ""
"市名": "威海",
"编码": ""
"市名": "枣庄",
"编码": ""
"市名": "日照",
"编码": ""
"市名": "莱芜",
"编码": ""
"市名": "聊城",
"编码": ""
"市名": "青岛",
"编码": ""
"市名": "淄博",
"编码": ""
"市名": "德州",
"编码": ""
"市名": "烟台",
"编码": ""
"市名": "济宁",
"编码": ""
"市名": "泰安",
"编码": ""
"省": "陕西",
"市名": "西安",
"编码": ""
"市名": "延安",
"编码": ""
"市名": "榆林",
"编码": ""
"市名": "铜川",
"编码": ""
"市名": "商洛",
"编码": ""
"市名": "安康",
"编码": ""
"市名": "汉中",
"编码": ""
"市名": "宝鸡",
"编码": ""
"市名": "咸阳",
"编码": ""
"市名": "渭南",
"编码": ""
"省": "山西",
"市名": "太原",
"编码": ""
"市名": "临汾",
"编码": ""
"市名": "运城",
"编码": ""
"市名": "朔州",
"编码": ""
"市名": "忻州",
"编码": ""
"市名": "长治",
"编码": ""
"市名": "大同",
"编码": ""
"市名": "阳泉",
"编码": ""
"市名": "晋中",
"编码": ""
"市名": "晋城",
"编码": ""
"市名": "吕梁",
"编码": ""
"省": "新疆",
"市名": "乌鲁木齐",
"编码": ""
"市名": "石河子",
"编码": ""
"市名": "昌吉",
"编码": ""
"市名": "吐鲁番",
"编码": ""
"市名": "库尔勒",
"编码": ""
"市名": "阿拉尔",
"编码": ""
"市名": "阿克苏",
"编码": ""
"市名": "喀什",
"编码": ""
"市名": "伊宁",
"编码": ""
"市名": "塔城",
"编码": ""
"市名": "哈密",
"编码": ""
"市名": "和田",
"编码": ""
"市名": "阿勒泰",
"编码": ""
"市名": "阿图什",
"编码": ""
"市名": "博乐",
"编码": ""
"市名": "克拉玛依",
"编码": ""
"省": "西藏",
"市名": "拉萨",
"编码": ""
"市名": "山南",
"编码": ""
"市名": "阿里",
"编码": ""
"市名": "昌都",
"编码": ""
"市名": "那曲",
"编码": ""
"市名": "日喀则",
"编码": ""
"市名": "林芝",
"编码": ""
"省": "台湾",
"市名": "台北县",
"编码": ""
"市名": "高雄",
"编码": ""
"市名": "台中",
"编码": ""
"省": "海南",
"市名": "海口",
"编码": ""
"市名": "三亚",
"编码": ""
"市名": "东方",
"编码": ""
"市名": "临高",
"编码": ""
"市名": "澄迈",
"编码": ""
"市名": "儋州",
"编码": ""
"市名": "昌江",
"编码": ""
"市名": "白沙",
"编码": ""
"市名": "琼中",
"编码": ""
"市名": "定安",
"编码": ""
"市名": "屯昌",
"编码": ""
"市名": "琼海",
"编码": ""
"市名": "文昌",
"编码": ""
"市名": "保亭",
"编码": ""
"市名": "万宁",
"编码": ""
"市名": "陵水",
"编码": ""
"市名": "西沙",
"编码": ""
"市名": "南沙岛",
"编码": ""
"市名": "乐东",
"编码": ""
"市名": "五指山",
"编码": ""
"市名": "琼山",
"编码": ""
"省": "湖南",
"市名": "长沙",
"编码": ""
"市名": "株洲",
"编码": ""
"市名": "衡阳",
"编码": ""
"市名": "郴州",
"编码": ""
"市名": "常德",
"编码": ""
"市名": "益阳",
"编码": ""
"市名": "娄底",
"编码": ""
"市名": "邵阳",
"编码": ""
"市名": "岳阳",
"编码": ""
"市名": "张家界",
"编码": ""
"市名": "怀化",
"编码": ""
"市名": "黔阳",
"编码": ""
"市名": "永州",
"编码": ""
"市名": "吉首",
"编码": ""
"市名": "湘潭",
"编码": ""
"省": "江苏",
"市名": "南京",
"编码": ""
"市名": "镇江",
"编码": ""
"市名": "苏州",
"编码": ""
"市名": "南通",
"编码": ""
"市名": "扬州",
"编码": ""
"市名": "宿迁",
"编码": ""
"市名": "徐州",
"编码": ""
"市名": "淮安",
"编码": ""
"市名": "连云港",
"编码": ""
"市名": "常州",
"编码": ""
"市名": "泰州",
"编码": ""
"市名": "无锡",
"编码": ""
"市名": "盐城",
"编码": ""
"省": "黑龙江",
"市名": "哈尔滨",
"编码": ""
"市名": "牡丹江",
"编码": ""
"市名": "佳木斯",
"编码": ""
"市名": "绥化",
"编码": ""
"市名": "黑河",
"编码": ""
"市名": "双鸭山",
"编码": ""
"市名": "伊春",
"编码": ""
"市名": "大庆",
"编码": ""
"市名": "七台河",
"编码": ""
"市名": "鸡西",
"编码": ""
"市名": "鹤岗",
"编码": ""
"市名": "齐齐哈尔",
"编码": ""
"市名": "大兴安岭",
"编码": ""
"省": "吉林",
"市名": "长春",
"编码": ""
"市名": "延吉",
"编码": ""
"市名": "四平",
"编码": ""
"市名": "白山",
"编码": ""
"市名": "白城",
"编码": ""
"市名": "辽源",
"编码": ""
"市名": "松原",
"编码": ""
"市名": "吉林",
"编码": ""
"市名": "通化",
"编码": ""
"省": "辽宁",
"市名": "沈阳",
"编码": ""
"市名": "鞍山",
"编码": ""
"市名": "抚顺",
"编码": ""
"市名": "本溪",
"编码": ""
"市名": "丹东",
"编码": ""
"市名": "葫芦岛",
"编码": ""
"市名": "营口",
"编码": ""
"市名": "阜新",
"编码": ""
"市名": "辽阳",
"编码": ""
"市名": "铁岭",
"编码": ""
"市名": "朝阳",
"编码": ""
"市名": "盘锦",
"编码": ""
"市名": "大连",
"编码": ""
"市名": "锦州",
"编码": ""
&appSettings&
&!--根据IP获取城市的网址--&
&add key = "GetCityByIP" value = "/cityjson"/&
&!--获取天气的网址--&
&add key = "GetWeather" value = ".cn/data/{0}.html"/&
&/appSettings&
给出数据下载
2. 图片接口&
这个图就是天气现象0（晴）的图片，其他天气现象的图片依此类推。c打头的图片是20*20像素的，b打头的是50*46像素的，d打头的是反白的图标，29*20像素，n打头的是夜间反白图标，29*20像素，注意这里的文件名是两位数字！ 也许还有更多的图标，等待大家发掘啦~
对于第三个接口，返回信息比较全面，也是以json格式提供，格式如下
{"weatherinfo": {
//基本信息;
"city":"北京","city_en":"beijing",
"date_y":"日", "date":"", "week":"星期四", "fchh":"11", "cityid":"",
//摄氏温度
"temp1":"2℃~-7℃",
"temp2":"1℃~-7℃",
"temp3":"4℃~-7℃",
"temp4":"7℃~-5℃",
"temp5":"5℃~-3℃",
"temp6":"5℃~-2℃",
//华氏温度;
"tempF1":"35.6℉~19.4℉",
"tempF2":"33.8℉~19.4℉",
"tempF3":"39.2℉~19.4℉",
"tempF4":"44.6℉~23℉",
"tempF5":"41℉~26.6℉",
"tempF6":"41℉~28.4℉",
//天气描述;
"weather1":"晴",
"weather2":"晴",
"weather3":"晴",
"weather4":"晴转多云",
"weather5":"多云",
"weather6":"多云转阴",
//天气描述图片序号
"img1":"0",
"img2":"99",
"img3":"0",
"img4":"99",
"img5":"0",
"img6":"99",
"img7":"0",
"img8":"1",
"img9":"1",
"img10":"99",
"img11":"1",
"img12":"2",
"img_single":"0",
//图片名称;
"img_title1":"晴",
"img_title2":"晴",
"img_title3":"晴",
"img_title4":"晴",
"img_title5":"晴",
"img_title6":"晴",
"img_title7":"晴",
"img_title8":"多云",
"img_title9":"多云",
"img_title10":"多云",
"img_title11":"多云",
"img_title12":"阴",
"img_title_single":"晴",
//风速描述
"wind1":"北风3-4级转微风",
"wind2":"微风",
"wind3":"微风",
"wind4":"微风",
"wind5":"微风",
"wind6":"微风",
//风速级别描述
"fx1":"北风",
"fx2":"微风",
"fl1":"3-4级转小于3级",
"fl2":"小于3级",
"fl3":"小于3级",
"fl4":"小于3级",
"fl5":"小于3级",
"fl6":"小于3级",
//今天穿衣指数;
"index":"冷",
"index_d":"天气冷，建议着棉衣、皮夹克加羊毛衫等冬季服装。年老体弱者宜着厚棉衣或冬大衣。",
//48小时穿衣指数
"index48":"冷",
"index48_d":"天气冷，建议着棉衣、皮夹克加羊毛衫等冬季服装。年老体弱者宜着厚棉衣或冬大衣。",
//紫外线及48小时紫外线
"index_uv":"弱",
"index48_uv":"弱",
"index_xc":"适宜",
"index_tr":"一般",
//舒适指数
"index_co":"较不舒适",
"st1":"1",
"st2":"-8",
"st3":"2",
"st4":"-4",
"st5":"5",
"st6":"-5",
"index_cl":"较不宜",
"index_ls":"基本适宜",
"index_ag":"极不易发"}}
3. JSON接口 真没想到~居然有JSON接口~JSON在iPhone上分析起来要比XML简单很多 .cn/data/.html 这个是北京的JSON数据，那个HTML的名字是根据上文XML中的url得到的。这个JSON中包含了实时数据、7天天气预报、气象指数等丰富的数据
using System.Collections.G
using System.L
using System.W
using System.Web.UI;
using System.Web.UI.WebC
using System.C
using Newtonsoft.Json.L
using Newtonsoft.J
using System.T
using System.IO;
using System.Runtime.S
namespace posite
public partial class weather : System.Web.UI.Page
protected void Page_Load(object sender, EventArgs e)
Response.Clear();
Response.Charset = "utf-8";
Response.ContentEncoding = Encoding.UTF8;
string city = readRemoteWeatherApi();
string cityCode = GetCityCode(city);
if (Request.QueryString["type"] != null && Request.QueryString["type"] == "js")
Response.ContentType = "text/javascript";
Response.Charset = "utf-8";
Response.Write(string.Format("var myWeather={0};", ReadWeatherJosnByCode(cityCode)));
Response.End();
YemlWeather ye = ReadWeatherByCode(cityCode);
/// &summary&
/// 获取自己的IP对应的城市ID
/// &/summary&
/// &returns&&/returns&
private string readRemoteWeatherApi()
string cityJson = string.E
string provincesAndCity = string.E
string provinces = string.E
string city = string.E
using (System.Net.WebClient wc = new System.Net.WebClient())
string url = ConfigurationManager.AppSettings["GetCityByIP"];
cityJson = wc.DownloadString(url);
cityJson = cityJson.Replace("var returnCitySN = ", "");
cityJson = cityJson.Replace(";", "");
JObject JObjtCity = (JObject)JsonConvert.DeserializeObject(cityJson);
provincesAndCity = JObjtCity["cname"].ToString();
provinces = provincesAndCity.Substring(0, provincesAndCity.IndexOf("省") + 1);
int n = provincesAndCity.IndexOf("省") + 1;
city = provincesAndCity.Substring(n, provincesAndCity.Length - 2 - n);
catch (Exception ex)
/// &summary&
/// 读取天气预报接口获取天气信息YemlWeather实体信息
/// &/summary&
/// ¶m name="citycode"&&/param&
/// &returns&读取天气预报接口获取天气信息YemlWeather实体信息&/returns&
public YemlWeather ReadWeatherByCode(string citycode)
YemlWeather WeatherInfo = new YemlWeather();
byte[] cityJson = null;
using (System.Net.WebClient wc = new System.Net.WebClient())
cityJson = wc.DownloadData(string.Format(".cn/data/{0}.html", citycode));
Encoding enc = Encoding.GetEncoding("utf-8");
string jsonStr = enc.GetString(cityJson);
WeatherInfo = (YemlWeather)JsonConvert.DeserializeObject(jsonStr, typeof(YemlWeather));
catch (Exception ex)
return WeatherI
/// &summary&
/// 读取天气预报接口获取天气信息json字符串
/// &/summary&
/// ¶m name="citycode"&&/param&
/// &returns&读取天气预报接口获取天气信息json字符串&/returns&
public string ReadWeatherJosnByCode(string citycode)
byte[] cityJson = null;
using (System.Net.WebClient wc = new System.Net.WebClient())
cityJson = wc.DownloadData(string.Format(".cn/data/{0}.html", citycode));
Encoding enc = Encoding.GetEncoding("utf-8");
string jsonStr = enc.GetString(cityJson);
return jsonS
catch (Exception ex)
/// &summary&
/// 根据城市名称返回城市代号
/// 城市名称可以有多种形式，如：
/// 安康市
/// 陕西安康
/// 陕西安康市
/// 陕西省安康市
/// &/summary&
/// ¶m name="cityName"&城市名称&/param&
/// &returns&&/returns&
private string GetCityCode(string cityName)
StreamReader sr = File.OpenText(string.Format("{0}/App_Data/CityCode.Json.txt", HttpContext.Current.Request.MapPath("~")));
string strCityCodeJson = sr.ReadToEnd();
JArray JObjtCityCode = (JArray)JsonConvert.DeserializeObject(strCityCodeJson);
bool isFound = false;
string cityCode = string.E
for (int i = 0; i & JObjtCityCode.C i++)
JArray citys = ConvterJArray(JObjtCityCode[i]["市"]);
for (int j = 0; j & citys.C j++)
//此为了实现多种城市形式匹配，所以添加多个判断
string _city = citys[j]["市名"].ToString().Replace("\"", "");
string _provice = JObjtCityCode[i]["省"].ToString().Replace("\"", "");
if (_city.ToString() == cityName
|| String.Format("{0}市", _city) == cityName
|| String.Format("{0}{1}", _provice, _city) == cityName
|| String.Format("{0}{1}市", _provice, _city) == cityName
|| String.Format("{0}省{1}", _provice, _city) == cityName
|| String.Format("{0}省{1}市", _provice, _city) == cityName)
cityCode = citys[j]["编码"].ToString();
isFound = true;
isFound = false;
if (isFound)
return cityCode.Replace("\"", "");
private JArray ConvterJArray(JToken token)
//jtoken 就是一个对象 可以转换层字符串
// 同时对于json 部分时间就是一个jtoken 对象 经转换 成一个jarray 对象
// 就可以知道他的lenght 同时循环处理内部
string tokenTos = token.ToString();
JArray op = (JArray)JsonConvert.DeserializeObject(tokenTos);
[DataContract]
public class WeatherInformation
[JsonProperty("city")]
public string City
[JsonProperty("city_en")]
public string CityEn
[JsonProperty("date_y")]
public string Date_y
[JsonProperty("date")]
public string Date
[JsonProperty("week")]
public string Week
[JsonProperty("fchh")]
public string Fchh
[JsonProperty("cityid")]
public string CityId
[JsonProperty("temp1")]
public string Temp1
[JsonProperty("temp2")]
public string Temp2
[JsonProperty("temp3")]
public string Temp3
[JsonProperty("temp4")]
public string Temp4
[JsonProperty("temp5")]
public string Temp5
[JsonProperty("temp6")]
public string Temp6
[JsonProperty("tempF1")]
public string TempF1
[JsonProperty("tempF2")]
public string TempF2
[JsonProperty("tempF3")]
public string TempF3
[JsonProperty("tempF4")]
public string TempF4
[JsonProperty("tempF5")]
public string TempF5
[JsonProperty("tempF6")]
public string TempF6
[JsonProperty("weather1")]
public string Weather1
[JsonProperty("weather2")]
public string Weather2
[JsonProperty("weather3")]
public string Weather3
[JsonProperty("weather4")]
public string Weather4
[JsonProperty("weather5")]
public string Weather5
[JsonProperty("weather6")]
public string Weather6
[JsonProperty("img1")]
public string Img1
[JsonProperty("img2")]
public string Img2
[JsonProperty("img3")]
public string Img3
[JsonProperty("img4")]
public string Img4
[JsonProperty("img5")]
public string Img5
[JsonProperty("img6")]
public string Img6
[JsonProperty("img7")]
public string Img7
[JsonProperty("img8")]
public string Img8
[JsonProperty("img9")]
public string Img9
[JsonProperty("img10")]
public string Img10
[JsonProperty("img11")]
public string Img11
[JsonProperty("img12")]
public string Img12
[JsonProperty("wind1")]
public string Wind1
[JsonProperty("wind2")]
public string Wind2
[JsonProperty("wind3")]
public string Wind3
[JsonProperty("wind4")]
public string Wind4
[JsonProperty("wind5")]
public string Wind5
[JsonProperty("wind6")]
public string Wind6
[JsonProperty("fx1")]
public string Fx1
[JsonProperty("fx2")]
public string Fx2
[JsonProperty("fl1")]
public string Fl1
[JsonProperty("fl2")]
public string Fl2
[JsonProperty("fl3")]
public string Fl3
[JsonProperty("fl4")]
public string Fl4
[JsonProperty("fl5")]
public string Fl5
[JsonProperty("fl6")]
public string Fl6
[JsonProperty("img_single")]
public string Img_single
[JsonProperty("img_title_single")]
public string Img_title_single
[JsonProperty("img_title1")]
public string Img_title1
[JsonProperty("img_title2")]
public string Img_title2
[JsonProperty("img_title3")]
public string Img_title3
[JsonProperty("img_title4")]
public string Img_title4
[JsonProperty("img_title5")]
public string Img_title5
[JsonProperty("img_title6")]
public string Img_title6
[JsonProperty("img_title7")]
public string Img_title7
[JsonProperty("img_title8")]
public string Img_title8
[JsonProperty("img_title9")]
public string Img_title9
[JsonProperty("img_title10")]
public string Img_title10
[JsonProperty("img_title11")]
public string Img_title11
[JsonProperty("img_title12")]
public string Img_title12
[JsonProperty("index")]
public string Index
[JsonProperty("index_d")]
public string Index_d
[JsonProperty("index48")]
public string Index48
[JsonProperty("index48_d")]
public string Index48_d
[JsonProperty("index_uv")]
public string Index_uv
[JsonProperty("index48_uv")]
public string Index48_uv
[JsonProperty("index_xc")]
public string Index_xc
[JsonProperty("index_tr")]
public string Index_tr
[JsonProperty("index_co")]
public string Index_co
[JsonProperty("st1")]
public string St1
[JsonProperty("st2")]
public string St2
[JsonProperty("st3")]
public string St3
[JsonProperty("st4")]
public string St4
[JsonProperty("st5")]
public string St5
[JsonProperty("st6")]
public string St6
[JsonProperty("index_cl")]
public string Index_cl
[JsonProperty("index_ls")]
public string Index_ls
[JsonProperty("index_ag")]
public string Index_ag
/// &summary&
/// 天气实体类
/// &/summary&
[DataContract]
public class YemlWeather
[JsonProperty("weatherinfo")]
public WeatherInformation weatherinfo { get; set; }
我序列化json用的是
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