Geographic Location Information Visualization And Spatial-temporal Statistical Analysis Based On E-commerce Sales Data

The arrival of the era of "big data" has made people's research in urban studies,people's daily life habits,and other fields increasingly perfect.Traditional data acquisition methods use questionnaires,interviews,and other methods that are time-consuming and labor-intensive,and they are visualizing and expressing data.Chart analysis often uses static analysis charts such as excel tables,showing that the results are not intuitive and clear.In response to this situation,this article captures the Marquette Micro-sales sales data(a total of 66 days between October 27,2016 and December 31,2016)to understand the distribution characteristics and living habits of residents and residents based on e-commerce sales data.Distribution in the space-time range.The main work and innovations are as follows:1.Front-end visualization of e-commerce sales dataThis article uses the Python code language to encapsulate the acquired e-commerce sales data into the database.The hypertext preprocessor PHP is used to compile the database interface.The data needed in the database is extracted and output in the JSON data format.The Ajax asynchronous acquisition is used to facilitate the acquisition and processing of researchers.Combining the front-end code language HTML5,CSS3,JavaScript and Echarts visualization library to obtain an intuitive and dynamic visual expression of the e-commerce sales data,laying a foundation for the analysis of the data afterwards.2.Time-space analysis of e-commerce sales dataIn terms of space,this paper analyzes the geographic map of geographic distribution of e-commerce sales data,and combines it with the provincial administrative divisions of China and the population and GDP of each province to understand the spatial activities of e-commerce sales activities.In terms of time,this paper visually expresses and analyzes the time distribution law of sales data in units of weeks and the time distribution law ofsales data in days,and combines it with the time law of daily work and life of residents to understand them.Law of activity time and daily work life rules.3,spatial statistical analysis of product attributesIn accordance with the principles of spatial statistics,combined with spatial statistics tools and methods,according to the attribute characteristics of logistics attributes,color attributes,size attributes in e-commerce sales data,understand the distribution of different attributes in spatial geography,and understand the spatial distribution of attributes related to residents position.