外贸电力景气指数数据
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1.数据适用范围：浙江省。 2.数据内容：基于数据中台，对电力用户的档案清单、出口数据、用电量、负荷等数据开展分析应用。 3.数据应用场景：利用用电统计数据、出口统计数据等打造外贸电力景气指数，形成第一手监测分析结论，直观、客观反映浙江省外贸企业经营情况，为浙江省积极应对外贸复杂形势提供有力支撑。 4.数据简介：基于浙江省外贸各行业的用电统计数据、出口统计数据等，构建外贸电力景气指数，分别为整体、特征和感应指数。整体指数主要监测全口径规上外贸型制造业出口及用电情况，用来反映整体态势。特征指数一方面监测浙江省前10大规上外贸型行业用电情况，另一方面按地域特色和产业链分布，监测5大产业集群，包括杭州数字经济、宁波高端装备、舟山化工、金华五金、绍兴纺织。感应指数动态监测中小型企业整体用电和港口物流情况，用以反映民营经济活力和外贸出口形势。1.数据清洗：对数据集进行清洗，包括去除异常数据、处理缺失值。 2.算法模型：本数据产品构建了电力外贸景气指数模型，该模型根据整体指数、特征指数、中小企业指数和物流指数）等维度的分析结果来评价外贸企业经营情况与景气程度，具体计算指标和算法如下。 （1）整体指数（取浙江省规上外贸型制造业数据） 整体指数=（浙江省当月日均出口额/浙江省去年日均出口额*100%）*0.5+（浙江省当月日均用电量/浙江省去年日均用电量*100%）*0.5。 （数值字段单位：浙江省当月日均出口额：亿元，浙江省去年日均出口额：亿元；浙江省当月日均用电量：万千瓦时，浙江省去年日均用电量：万千瓦时） （2）特征指数（取各地市特色行业规上外贸型制造业） 特征指数=（地市特色行业当月日均用电量/地市特色行业去年日均用电量*100%）*0.5+（地市特色行业当月日均用电量同比值）*100%*0.5。 （数值字段单位：地市特色行业当月日均用电量：万千瓦时，地市特色行业去年日均用电量：万千瓦时；地市特色行业当月日均用电量同比值：%） (3)中小企业指数、物流指数（取浙江省中小型企业数据和宁波舟山港数据） 中小企业指数=（中小企业当月日均用电量/中小企业去年日均用电量*100%）*0.5+（中小企业当月日均用电量同比值*100%）*0.5。 （数值字段单位：中小企业当月日均用电量：万千瓦时，中小企业去年日均用电量：万千瓦时；中小企业当月日均用电量同比值：%） 物流指数=（宁波舟山港当月日均出口重箱进港区量/宁波舟山港去年日均出口重箱进港区量*100%）*0.5+（宁波舟山港当月日均用电量/宁波舟山港去年日均用电量*100%）*0.5。 （数值字段单位：宁波舟山港当月日均出口重箱进港区量：标准箱，宁波舟山港去年日均出口重箱进港区量：标准箱；宁波舟山港当月日均用电量：万千瓦时；宁波舟山港去年日均用电量：万千瓦时）
1. Scope of Application: Zhejiang Province. 2. Data Content: Based on the data middle platform, conduct analysis and applications on data such as archive lists, export data, electricity consumption and load of power users. 3. Application Scenarios: Use electricity consumption statistics, export statistics and other data to build a foreign trade electricity prosperity index, form first-hand monitoring and analysis conclusions, intuitively and objectively reflect the operation status of foreign trade enterprises in Zhejiang Province, and provide solid support for Zhejiang Province to actively respond to the complex foreign trade situation. 4. Data Introduction: Based on electricity consumption statistics and export statistics of various foreign trade industries in Zhejiang Province, a foreign trade electricity prosperity index is constructed, which is divided into three types: overall index, characteristic index and sentiment index. The overall index mainly monitors the export and electricity consumption of full-scope above-designated-size foreign trade manufacturing enterprises, to reflect the overall trend. The characteristic index, on one hand, monitors the electricity consumption of the top 10 above-designated-size foreign trade industries in Zhejiang Province; on the other hand, it monitors 5 major industrial clusters according to regional characteristics and industrial chain distribution, including Hangzhou's digital economy, Ningbo's high-end equipment, Zhoushan's chemical industry, Jinhua's hardware and Shaoxing's textile industry. The sentiment index dynamically monitors the overall electricity consumption of small and medium-sized enterprises (SMEs) and port logistics status, to reflect the vitality of the private economy and the foreign trade export situation. 1. Data Cleaning: Clean the dataset, including removing abnormal data and handling missing values. 2. Algorithm Model: This data product constructs a foreign trade electricity prosperity index model, which evaluates the operation status and prosperity level of foreign trade enterprises based on the analysis results of dimensions such as the overall index, characteristic index, SME index and logistics index. The specific calculation indicators and algorithms are as follows. (1) Overall Index (using data of above-designated-size foreign trade manufacturing enterprises in Zhejiang Province) Overall Index = [(Average daily export value of Zhejiang Province in the current month / Average daily export value of Zhejiang Province in the same period last year * 100%) * 0.5] + [(Average daily electricity consumption of Zhejiang Province in the current month / Average daily electricity consumption of Zhejiang Province in the same period last year * 100%) * 0.5] (Unit of numerical fields: Average daily export value of Zhejiang Province in the current month: 100 million yuan; Average daily export value of Zhejiang Province in the same period last year: 100 million yuan; Average daily electricity consumption of Zhejiang Province in the current month: 10,000 kilowatt-hours (kWh); Average daily electricity consumption of Zhejiang Province in the same period last year: 10,000 kilowatt-hours (kWh)) (2) Characteristic Index (using data of above-designated-size foreign trade manufacturing enterprises in local characteristic industries) Characteristic Index = [(Average daily electricity consumption of local characteristic industries in the current month / Average daily electricity consumption of local characteristic industries in the same period last year * 100%) * 0.5] + [(Year-on-year growth rate of average daily electricity consumption of local characteristic industries in the current month * 100%) * 0.5] (Unit of numerical fields: Average daily electricity consumption of local characteristic industries in the current month: 10,000 kilowatt-hours (kWh); Average daily electricity consumption of local characteristic industries in the same period last year: 10,000 kilowatt-hours (kWh); Year-on-year growth rate of average daily electricity consumption of local characteristic industries in the current month: %) (3) SME Index and Logistics Index (using data of small and medium-sized enterprises in Zhejiang Province and data of Ningbo Zhoushan Port) SME Index = [(Average daily electricity consumption of SMEs in the current month / Average daily electricity consumption of SMEs in the same period last year * 100%) * 0.5] + [(Year-on-year growth rate of average daily electricity consumption of SMEs in the current month * 100%) * 0.5] (Unit of numerical fields: Average daily electricity consumption of SMEs in the current month: 10,000 kilowatt-hours (kWh); Average daily electricity consumption of SMEs in the same period last year: 10,000 kilowatt-hours (kWh); Year-on-year growth rate of average daily electricity consumption of SMEs in the current month: %) Logistics Index = [(Average daily volume of exported heavy containers entering the port area of Ningbo Zhoushan Port in the current month / Average daily volume of exported heavy containers entering the port area of Ningbo Zhoushan Port in the same period last year * 100%) * 0.5] + [(Average daily electricity consumption of Ningbo Zhoushan Port in the current month / Average daily electricity consumption of Ningbo Zhoushan Port in the same period last year * 100%) * 0.5] (Unit of numerical fields: Average daily volume of exported heavy containers entering the port area of Ningbo Zhoushan Port in the current month: Twenty-foot Equivalent Unit (TEU); Average daily volume of exported heavy containers entering the port area of Ningbo Zhoushan Port in the same period last year: Twenty-foot Equivalent Unit (TEU); Average daily electricity consumption of Ningbo Zhoushan Port in the current month: 10,000 kilowatt-hours (kWh); Average daily electricity consumption of Ningbo Zhoushan Port in the same period last year: 10,000 kilowatt-hours (kWh))
