作者計(jì)算機(jī)畢業(yè)設(shè)計(jì)小途個(gè)人簡(jiǎn)介曾長(zhǎng)期從事計(jì)算機(jī)專業(yè)培訓(xùn)教學(xué)本人也熱愛(ài)上課教學(xué)語(yǔ)言擅長(zhǎng)Java、微信小程序、Python、Golang、安卓Android等開(kāi)發(fā)項(xiàng)目包括大數(shù)據(jù)、深度學(xué)習(xí)、網(wǎng)站、小程序、安卓、算法。平常會(huì)做一些項(xiàng)目定制化開(kāi)發(fā)、代碼講解、答辯教學(xué)、文檔編寫(xiě)、也懂一些降重方面的技巧。平常喜歡分享一些自己開(kāi)發(fā)中遇到的問(wèn)題的解決辦法也喜歡交流技術(shù)大家有技術(shù)代碼這一塊的問(wèn)題可以問(wèn)我想說(shuō)的話感謝大家的關(guān)注與支持網(wǎng)站實(shí)戰(zhàn)項(xiàng)目安卓/小程序?qū)崙?zhàn)項(xiàng)目大數(shù)據(jù)實(shí)戰(zhàn)項(xiàng)目深度學(xué)習(xí)實(shí)戰(zhàn)項(xiàng)目目錄動(dòng)漫評(píng)分和人氣數(shù)據(jù)可視化與分析系統(tǒng)介紹動(dòng)漫評(píng)分和人氣數(shù)據(jù)可視化與分析系統(tǒng)演示視頻動(dòng)漫評(píng)分和人氣數(shù)據(jù)可視化與分析系統(tǒng)演示圖片動(dòng)漫評(píng)分和人氣數(shù)據(jù)可視化與分析系統(tǒng)代碼展示動(dòng)漫評(píng)分和人氣數(shù)據(jù)可視化與分析系統(tǒng)文檔展示動(dòng)漫評(píng)分和人氣數(shù)據(jù)可視化與分析系統(tǒng)介紹本系統(tǒng)《基于大數(shù)據(jù)的動(dòng)漫評(píng)分和人氣數(shù)據(jù)可視化與分析》面向動(dòng)漫評(píng)分、人氣等數(shù)據(jù)做集中整理、統(tǒng)計(jì)和可視化展示后端采用PythonDjango版本大數(shù)據(jù)部分用Hadoop與Spark借助HDFS存放原始數(shù)據(jù)用Spark、Spark SQL完成數(shù)據(jù)清洗、聚合和指標(biāo)計(jì)算Pandas、NumPy輔助做數(shù)值處理MySQL保存用戶、動(dòng)漫信息與部分分析結(jié)果前端用Vue、ElementUI、Echarts、HTML、CSS、JavaScript和jQuery搭建頁(yè)面與圖表。功能上包含系統(tǒng)首頁(yè)、大屏可視化、用戶、動(dòng)漫信息、評(píng)分分布分析、人氣熱度分析、類型對(duì)比分析、年代趨勢(shì)分析、體量結(jié)構(gòu)分析、價(jià)值分群分析、個(gè)人信息和修改密碼。用戶登錄后可以查看動(dòng)漫基礎(chǔ)信息也能在大屏上看到評(píng)分分布、熱度排行、類型差異、年代變化、體量結(jié)構(gòu)和價(jià)值分群等圖表后臺(tái)可維護(hù)動(dòng)漫數(shù)據(jù)與用戶數(shù)據(jù)。系統(tǒng)把原本分散的評(píng)分、人氣、類型、年代等字段按分析主題組織起來(lái)用Spark做批量統(tǒng)計(jì)再由前端圖表呈現(xiàn)幫助使用者更直觀地觀察動(dòng)漫評(píng)分和人氣之間的關(guān)系。整體實(shí)現(xiàn)以畢業(yè)設(shè)計(jì)可落地為目標(biāo)不追求復(fù)雜架構(gòu)重點(diǎn)把大數(shù)據(jù)處理流程和可視化分析功能串起來(lái)。動(dòng)漫評(píng)分和人氣數(shù)據(jù)可視化與分析系統(tǒng)演示視頻項(xiàng)目演示視頻動(dòng)漫評(píng)分和人氣數(shù)據(jù)可視化與分析系統(tǒng)演示圖片動(dòng)漫評(píng)分和人氣數(shù)據(jù)可視化與分析系統(tǒng)代碼展示sparkSparkSession.builder.appName(AnimeRatingPopularityAnalysis).master(local[*]).config(spark.sql.shuffle.partitions,4).getOrCreate()defrating_distribution(request):dfspark.read.format(jdbc).option(url,jdbc:mysql://localhost:3306/anime_db).option(dbtable,anime_info).option(user,root).option(password,123456).option(driver,com.mysql.cj.jdbc.Driver).load()df.createOrReplaceTempView(anime_rating)resultspark.sql(SELECT CAST(FLOOR(rating) AS INT) AS score_floor, COUNT(*) AS anime_count, ROUND(COUNT(*) * 100.0 / SUM(COUNT(*)) OVER(), 2) AS ratio FROM anime_rating WHERE rating IS NOT NULL GROUP BY CAST(FLOOR(rating) AS INT) ORDER BY score_floor)rowsresult.collect()labels[]counts[]ratios[]forrowinrows:startrow[score_floor]labels.append(str(start)-str(start1))counts.append(row[anime_count])ratios.append(row[ratio])totalsum(counts)max_countmax(counts)ifcountselse0max_rangelabels[counts.index(max_count)]ifcountselseavg_ratingdf.selectExpr(AVG(rating)).first()[0]returnJsonResponse({labels:labels,counts:counts,ratios:ratios,total:total,maxRange:max_range,avgRating:round(avg_rating,2)ifavg_ratingelse0,msg:評(píng)分分布分析完成})defpopularity_heat(request):dfspark.read.format(jdbc).option(url,jdbc:mysql://localhost:3306/anime_db).option(dbtable,anime_info).option(user,root).option(password,123456).option(driver,com.mysql.cj.jdbc.Driver).load()df.createOrReplaceTempView(anime_popularity)resultspark.sql(SELECT type_name, COUNT(*) AS anime_count, ROUND(AVG(popularity), 2) AS avg_popularity, ROUND(AVG(rating), 2) AS avg_rating, SUM(popularity) AS total_heat FROM anime_popularity WHERE popularity IS NOT NULL GROUP BY type_name ORDER BY total_heat DESC)rowsresult.collect()top_list[]heat_values[row[total_heat]forrowinrows]min_heatmin(heat_values)ifheat_valueselse0max_heatmax(heat_values)ifheat_valueselse0forrowinrows[:10]:heatrow[total_heat]ifmax_heatmin_heat:score100.0else:scoreround((heat-min_heat)*100.0/(max_heat-min_heat),2)top_list.append({type:row[type_name],count:row[anime_count],avgPopularity:row[avg_popularity],avgRating:row[avg_rating],totalHeat:heat,heatScore:score})returnJsonResponse({top10:top_list,typeCount:len(rows),minHeat:min_heat,maxHeat:max_heat,msg:人氣熱度分析完成})deftype_compare(request):dfspark.read.format(jdbc).option(url,jdbc:mysql://localhost:3306/anime_db).option(dbtable,anime_info).option(user,root).option(password,123456).option(driver,com.mysql.cj.jdbc.Driver).load()df.createOrReplaceTempView(anime_type)resultspark.sql(SELECT type_name, COUNT(*) AS total, ROUND(AVG(rating), 2) AS avg_rating, ROUND(AVG(popularity), 2) AS avg_popularity, ROUND(SUM(CASE WHEN rating 8 THEN 1 ELSE 0 END) * 100.0 / COUNT(*), 2) AS high_rate_ratio FROM anime_type WHERE type_name IS NOT NULL GROUP BY type_name HAVING COUNT(*) 5 ORDER BY avg_rating DESC, avg_popularity DESC)rowsresult.collect()labels[]avg_ratings[]avg_popularities[]high_ratios[]totals[]forrowinrows:labels.append(row[type_name])avg_ratings.append(row[avg_rating])avg_popularities.append(row[avg_popularity])high_ratios.append(row[high_rate_ratio])totals.append(row[total])best_typelabels[0]iflabelselsebest_ratingavg_ratings[0]ifavg_ratingselse0returnJsonResponse({labels:labels,avgRatings:avg_ratings,avgPopularities:avg_popularities,highRatios:high_ratios,totals:totals,bestType:best_type,bestRating:best_rating,msg:類型對(duì)比分析完成})動(dòng)漫評(píng)分和人氣數(shù)據(jù)可視化與分析系統(tǒng)文檔展示作者計(jì)算機(jī)畢業(yè)設(shè)計(jì)小途個(gè)人簡(jiǎn)介曾長(zhǎng)期從事計(jì)算機(jī)專業(yè)培訓(xùn)教學(xué)本人也熱愛(ài)上課教學(xué)語(yǔ)言擅長(zhǎng)Java、微信小程序、Python、Golang、安卓Android等開(kāi)發(fā)項(xiàng)目包括大數(shù)據(jù)、深度學(xué)習(xí)、網(wǎng)站、小程序、安卓、算法。平常會(huì)做一些項(xiàng)目定制化開(kāi)發(fā)、代碼講解、答辯教學(xué)、文檔編寫(xiě)、也懂一些降重方面的技巧。平常喜歡分享一些自己開(kāi)發(fā)中遇到的問(wèn)題的解決辦法也喜歡交流技術(shù)大家有技術(shù)代碼這一塊的問(wèn)題可以問(wèn)我想說(shuō)的話感謝大家的關(guān)注與支持網(wǎng)站實(shí)戰(zhàn)項(xiàng)目安卓/小程序?qū)崙?zhàn)項(xiàng)目大數(shù)據(jù)實(shí)戰(zhàn)項(xiàng)目深度學(xué)習(xí)實(shí)戰(zhàn)項(xiàng)目