設(shè)計選題推薦:基于大數(shù)據(jù)的公交站點出行信息數(shù)據(jù)可視化分析|畢業(yè)設(shè)計選題|計算機畢設(shè)|選題推薦|畢設(shè)指導(dǎo)|項目定制|源碼|高質(zhì)量項目)
?作者主頁IT畢設(shè)夢工廠?個人簡介曾從事計算機專業(yè)培訓(xùn)教學(xué)擅長Java、Python、PHP、.NET、Node.js、GO、微信小程序、安卓Android等項目實戰(zhàn)。接項目定制開發(fā)、代碼講解、答辯教學(xué)、文檔編寫、降重等。?文末獲取源碼?精彩專欄推薦???Java項目Python項目安卓項目微信小程序項目文章目錄一、前言二、開發(fā)環(huán)境三、系統(tǒng)界面展示四、部分代碼設(shè)計五、論文參考六、系統(tǒng)視頻結(jié)語一、前言基于大數(shù)據(jù)的公交站點出行信息數(shù)據(jù)可視化分析系統(tǒng)是一套面向城市公交出行場景的數(shù)據(jù)分析與可視化平臺整體采用Hadoop與Spark構(gòu)建大數(shù)據(jù)處理鏈路借助HDFS完成原始出行數(shù)據(jù)的分布式存儲通過Spark SQL與Pandas、NumPy對公交站點出行數(shù)據(jù)進行清洗、聚合與統(tǒng)計計算后端基于Django或Spring Boot提供數(shù)據(jù)接口服務(wù)前端使用Vue、ElementUI與Echarts完成圖表渲染與交互展示數(shù)據(jù)庫采用MySQL存儲用戶信息與業(yè)務(wù)配置數(shù)據(jù)。系統(tǒng)功能涵蓋系統(tǒng)首頁、大屏可視化、用戶管理、公交站點出行數(shù)據(jù)、線路結(jié)構(gòu)分析、站點覆蓋分析、方向?qū)Ρ确治觥⑿蛱柼卣鞣治?、換乘樞紐分析、出行畫像分析、個人信息與修改密碼等模塊能夠從線路、站點、方向、換乘、人群畫像等多個維度對公交出行信息進行可視化呈現(xiàn)幫助使用者直觀了解公交站點的出行規(guī)律與線路運行特征也為計算機專業(yè)畢業(yè)設(shè)計提供了一個完整的大數(shù)據(jù)技術(shù)實踐案例。二、開發(fā)環(huán)境大數(shù)據(jù)框架HadoopSpark本次沒用Hive支持定制開發(fā)語言PythonJava兩個版本都支持后端框架DjangoSpring Boot(SpringSpringMVCMybatis)兩個版本都支持前端VueElementUIEchartsHTMLCSSJavaScriptjQuery詳細技術(shù)點Hadoop、HDFS、Spark、Spark SQL、Pandas、NumPy數(shù)據(jù)庫MySQL三、系統(tǒng)界面展示基于大數(shù)據(jù)的公交站點出行信息數(shù)據(jù)可視化分析系統(tǒng)界面展示四、部分代碼設(shè)計項目實戰(zhàn)-代碼參考frompyspark.sqlimportSparkSessionfrompyspark.sql.functionsimportcol,count,countDistinct,desc,when,sumasspark_sum,avg,roundasspark_roundfromdjango.httpimportJsonResponsefromdjango.views.decorators.httpimportrequire_GETfrom.modelsimportBusStationTravel,BusLineInfo,BusStationInfo sparkSparkSession.builder.appName(BusStationTravelAnalysis).master(local[*]).config(spark.sql.shuffle.partitions,4).getOrCreate()defget_station_travel_data(request):travel_dfspark.read.format(jdbc).option(url,jdbc:mysql://localhost:3306/bus_bigdata).option(dbtable,bus_station_travel).option(user,root).option(password,123456).load()travel_df.createOrReplaceTempView(bus_station_travel)result_dfspark.sql(SELECT station_id, station_name, COUNT(*) AS travel_count, COUNT(DISTINCT line_id) AS line_count, SUM(passenger_count) AS total_passenger FROM bus_station_travel GROUP BY station_id, station_name ORDER BY total_passenger DESC)result_listresult_df.collect()data[]forrowinresult_list:data.append({stationId:row[station_id],stationName:row[station_name],travelCount:row[travel_count],lineCount:row[line_count],totalPassenger:row[total_passenger]})returnJsonResponse({code:200,msg:公交站點出行數(shù)據(jù)查詢成功,data:data})defget_line_structure_analysis(request):line_dfspark.read.format(jdbc).option(url,jdbc:mysql://localhost:3306/bus_bigdata).option(dbtable,bus_line_info).option(user,root).option(password,123456).load()line_df.createOrReplaceTempView(bus_line_info)structure_dfspark.sql(SELECT line_id, line_name, COUNT(station_id) AS station_total, SUM(CASE WHEN direction 上行 THEN 1 ELSE 0 END) AS up_station_count, SUM(CASE WHEN direction 下行 THEN 1 ELSE 0 END) AS down_station_count, AVG(station_distance) AS avg_distance FROM bus_line_info GROUP BY line_id, line_name ORDER BY station_total DESC)structure_liststructure_df.collect()data[]forrowinstructure_list:data.append({lineId:row[line_id],lineName:row[line_name],stationTotal:row[station_total],upStationCount:row[up_station_count],downStationCount:row[down_station_count],avgDistance:round(row[avg_distance],2)ifrow[avg_distance]else0})returnJsonResponse({code:200,msg:線路結(jié)構(gòu)分析成功,data:data})defget_transfer_hub_analysis(request):transfer_dfspark.read.format(jdbc).option(url,jdbc:mysql://localhost:3306/bus_bigdata).option(dbtable,bus_station_travel).option(user,root).option(password,123456).load()transfer_df.createOrReplaceTempView(bus_station_travel)hub_dfspark.sql(SELECT station_id, station_name, COUNT(DISTINCT line_id) AS transfer_line_count, SUM(passenger_count) AS total_passenger, COUNT(*) AS record_count FROM bus_station_travel GROUP BY station_id, station_name HAVING COUNT(DISTINCT line_id) 3 ORDER BY transfer_line_count DESC, total_passenger DESC)hub_listhub_df.collect()data[]forrowinhub_list:data.append({stationId:row[station_id],stationName:row[station_name],transferLineCount:row[transfer_line_count],totalPassenger:row[total_passenger],recordCount:row[record_count]})returnJsonResponse({code:200,msg:換乘樞紐分析成功,data:data})五、論文參考計算機畢業(yè)設(shè)計選題推薦-基于大數(shù)據(jù)的公交站點出行信息數(shù)據(jù)可視化分析系統(tǒng)-論文參考六、系統(tǒng)視頻基于大數(shù)據(jù)的公交站點出行信息數(shù)據(jù)可視化分析系統(tǒng)-項目視頻項目演示視頻結(jié)語計算機畢業(yè)設(shè)計選題推薦:基于大數(shù)據(jù)的公交站點出行信息數(shù)據(jù)可視化分析|畢業(yè)設(shè)計選題|計算機畢設(shè)|選題推薦|畢設(shè)指導(dǎo)|項目定制|源碼|高質(zhì)量項目大家可以幫忙點贊、收藏、關(guān)注、評論啦源碼獲取???精彩專欄推薦???Java項目Python項目安卓項目微信小程序項目 計算機畢業(yè)設(shè)計選題推薦:基于大數(shù)據(jù)的公交站點出行信息數(shù)據(jù)可視化分析|畢業(yè)設(shè)計選題|計算機畢設(shè)|選題推薦|畢設(shè)指導(dǎo)|項目定制|源碼|高質(zhì)量項目
?作者主頁IT畢設(shè)夢工廠?個人簡介曾從事計算機專業(yè)培訓(xùn)教學(xué)擅長Java、Python、PHP、.NET、Node.js、GO、微信小程序、安卓Android等項目實戰(zhàn)。接項目定制開發(fā)、代碼講解、答辯教學(xué)、文檔編寫、降重等。?文末獲取源碼?精彩專欄推薦???Java項目Python項目安卓項目微信小程序項目文章目錄一、前言二、開發(fā)環(huán)境三、系統(tǒng)界面展示四、部分代碼設(shè)計五、論文參考六、系統(tǒng)視頻結(jié)語一、前言基于大數(shù)據(jù)的公交站點出行信息數(shù)據(jù)可視化分析系統(tǒng)是一套面向城市公交出行場景的數(shù)據(jù)分析與可視化平臺整體采用Hadoop與Spark構(gòu)建大數(shù)據(jù)處理鏈路借助HDFS完成原始出行數(shù)據(jù)的分布式存儲通過Spark SQL與Pandas、NumPy對公交站點出行數(shù)據(jù)進行清洗、聚合與統(tǒng)計計算后端基于Django或Spring Boot提供數(shù)據(jù)接口服務(wù)前端使用Vue、ElementUI與Echarts完成圖表渲染與交互展示數(shù)據(jù)庫采用MySQL存儲用戶信息與業(yè)務(wù)配置數(shù)據(jù)。系統(tǒng)功能涵蓋系統(tǒng)首頁、大屏可視化、用戶管理、公交站點出行數(shù)據(jù)、線路結(jié)構(gòu)分析、站點覆蓋分析、方向?qū)Ρ确治觥⑿蛱柼卣鞣治?、換乘樞紐分析、出行畫像分析、個人信息與修改密碼等模塊能夠從線路、站點、方向、換乘、人群畫像等多個維度對公交出行信息進行可視化呈現(xiàn)幫助使用者直觀了解公交站點的出行規(guī)律與線路運行特征也為計算機專業(yè)畢業(yè)設(shè)計提供了一個完整的大數(shù)據(jù)技術(shù)實踐案例。二、開發(fā)環(huán)境大數(shù)據(jù)框架HadoopSpark本次沒用Hive支持定制開發(fā)語言PythonJava兩個版本都支持后端框架DjangoSpring Boot(SpringSpringMVCMybatis)兩個版本都支持前端VueElementUIEchartsHTMLCSSJavaScriptjQuery詳細技術(shù)點Hadoop、HDFS、Spark、Spark SQL、Pandas、NumPy數(shù)據(jù)庫MySQL三、系統(tǒng)界面展示基于大數(shù)據(jù)的公交站點出行信息數(shù)據(jù)可視化分析系統(tǒng)界面展示四、部分代碼設(shè)計項目實戰(zhàn)-代碼參考frompyspark.sqlimportSparkSessionfrompyspark.sql.functionsimportcol,count,countDistinct,desc,when,sumasspark_sum,avg,roundasspark_roundfromdjango.httpimportJsonResponsefromdjango.views.decorators.httpimportrequire_GETfrom.modelsimportBusStationTravel,BusLineInfo,BusStationInfo sparkSparkSession.builder.appName(BusStationTravelAnalysis).master(local[*]).config(spark.sql.shuffle.partitions,4).getOrCreate()defget_station_travel_data(request):travel_dfspark.read.format(jdbc).option(url,jdbc:mysql://localhost:3306/bus_bigdata).option(dbtable,bus_station_travel).option(user,root).option(password,123456).load()travel_df.createOrReplaceTempView(bus_station_travel)result_dfspark.sql(SELECT station_id, station_name, COUNT(*) AS travel_count, COUNT(DISTINCT line_id) AS line_count, SUM(passenger_count) AS total_passenger FROM bus_station_travel GROUP BY station_id, station_name ORDER BY total_passenger DESC)result_listresult_df.collect()data[]forrowinresult_list:data.append({stationId:row[station_id],stationName:row[station_name],travelCount:row[travel_count],lineCount:row[line_count],totalPassenger:row[total_passenger]})returnJsonResponse({code:200,msg:公交站點出行數(shù)據(jù)查詢成功,data:data})defget_line_structure_analysis(request):line_dfspark.read.format(jdbc).option(url,jdbc:mysql://localhost:3306/bus_bigdata).option(dbtable,bus_line_info).option(user,root).option(password,123456).load()line_df.createOrReplaceTempView(bus_line_info)structure_dfspark.sql(SELECT line_id, line_name, COUNT(station_id) AS station_total, SUM(CASE WHEN direction 上行 THEN 1 ELSE 0 END) AS up_station_count, SUM(CASE WHEN direction 下行 THEN 1 ELSE 0 END) AS down_station_count, AVG(station_distance) AS avg_distance FROM bus_line_info GROUP BY line_id, line_name ORDER BY station_total DESC)structure_liststructure_df.collect()data[]forrowinstructure_list:data.append({lineId:row[line_id],lineName:row[line_name],stationTotal:row[station_total],upStationCount:row[up_station_count],downStationCount:row[down_station_count],avgDistance:round(row[avg_distance],2)ifrow[avg_distance]else0})returnJsonResponse({code:200,msg:線路結(jié)構(gòu)分析成功,data:data})defget_transfer_hub_analysis(request):transfer_dfspark.read.format(jdbc).option(url,jdbc:mysql://localhost:3306/bus_bigdata).option(dbtable,bus_station_travel).option(user,root).option(password,123456).load()transfer_df.createOrReplaceTempView(bus_station_travel)hub_dfspark.sql(SELECT station_id, station_name, COUNT(DISTINCT line_id) AS transfer_line_count, SUM(passenger_count) AS total_passenger, COUNT(*) AS record_count FROM bus_station_travel GROUP BY station_id, station_name HAVING COUNT(DISTINCT line_id) 3 ORDER BY transfer_line_count DESC, total_passenger DESC)hub_listhub_df.collect()data[]forrowinhub_list:data.append({stationId:row[station_id],stationName:row[station_name],transferLineCount:row[transfer_line_count],totalPassenger:row[total_passenger],recordCount:row[record_count]})returnJsonResponse({code:200,msg:換乘樞紐分析成功,data:data})五、論文參考計算機畢業(yè)設(shè)計選題推薦-基于大數(shù)據(jù)的公交站點出行信息數(shù)據(jù)可視化分析系統(tǒng)-論文參考六、系統(tǒng)視頻基于大數(shù)據(jù)的公交站點出行信息數(shù)據(jù)可視化分析系統(tǒng)-項目視頻項目演示視頻結(jié)語計算機畢業(yè)設(shè)計選題推薦:基于大數(shù)據(jù)的公交站點出行信息數(shù)據(jù)可視化分析|畢業(yè)設(shè)計選題|計算機畢設(shè)|選題推薦|畢設(shè)指導(dǎo)|項目定制|源碼|高質(zhì)量項目大家可以幫忙點贊、收藏、關(guān)注、評論啦源碼獲取???精彩專欄推薦???Java項目Python項目安卓項目微信小程序項目