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#author("2023-02-27T05:48:06+00:00","","") #author("2023-02-27T05:48:34+00:00","","") #norelated #setlinebreak(on) #ref(url.zip,,url) https://dic515s2.pu-toyama.ac.jp/teaching-learning_system/ |>|>|>|>|>|CENTER:COLOR(white):BGCOLOR(blue):|c ||&size(13){月曜日};|&size(13){火曜日};|&size(13){水曜日};|&size(13){木曜日};|&size(13){金曜日};| |BGCOLOR(#5c5c5c):COLOR(white):|>|>|>|>|COLOR(white):BGCOLOR(white):CENTER:60|c |BGCOLOR(#999999):COLOR(white):|>|>|>|>|COLOR(white):BGCOLOR(white):CENTER:60|c |CENTER:&size(20){1-2};|||||| |CENTER:&size(20){3-4};||BGCOLOR(blue):&size(13){電波工学特論};||BGCOLOR(blue):&size(13){人間情報工学};|| |CENTER:&size(20){昼休み};|||||| |CENTER:&size(20){5-6};|||||BGCOLOR(blue):&size(13){科学技術論};| |CENTER:&size(20){7-8};|||||| |CENTER:&size(20){9-10};|||||| |CENTER:&size(20){11-12};|||||| [[トップページ>FrontPage]] ***[[研究会>研究会 清水]] [#h3a17cec] ***[[専門ゼミ>専門ゼミ 清水]][#h3a17cec] ***[[卒業論文テーマ>卒業論文 清水]][#h3a17cec] ***[[論文候補>論文候補]] [#h3a17cec] ***[[中間発表>中間発表用の]] [#h3a17cec] ***[[修士論文まとめる用>清水さん修論]] [#gdd91341] #memo(read_files = glob.glob("Tameshi/*.csv")\n dir_path = 'kyouzai'\n\n cols = ["HPtitle", "HPurl", "Hpnumber", "student", "evaluation", "text", "date"]\n dd =pd.DataFrame(columns = cols)\n\n colls = ["HPtitle", "HPurl", "Hpnumber", "student", "evaluation", "text", "date", "Credibility_score", " Score_average"]\n ddd =pd.DataFrame(columns = cols)\n\n for i in range(len(read_files)):\n os.makedirs("Tameshi/"+dir_path+str(i), exist_ok = True)\n read_file = read_files[i]\n df = pd.read_csv(read_file, encoding='utf-8')\n length = len(df)\n list=[]\n for j in range(len(df)):\n list.append(j)\n\n df['Hpnumber'] = list\n df['Credibility_score'] = ''\n df.to_csv("Tameshi/kyouzai"+str(i)+"/kyouzaiDB.csv", index=None, encoding="cp932",errors='ignore')\n dd.to_csv("Tameshi/kyouzai"+str(i)+"/review_prac.csv", index=None, encoding="cp932",errors='ignore')\n ddd.to_csv("Tameshi/kyouzai"+str(i)+"/review_score.csv", index=None, encoding="cp932",errors='ignore')) #memo(# スクレイピングのところ\n # os.makedirs("Tameshi", exist_ok=True)\n\n # sub_title = pd.read_csv("csv_save/"+kamoku_name+".csv", encoding='cp932', header=None)\n # sub_list =sub_title.iloc[:,0]\n # # print(sub_list)\n\n # hp_title = [[] for _ in range(len(sub_list))]\n # hp_url = [[] for _ in range(len(sub_list))]\n\n # for j in range(len(sub_list)):\n # search_word = sub_list[j]\n # pages_num = 15+1\n\n # url = f'https://www.google.co.jp/search?hl=ja&num={pages_num}&q={search_word}'\n # request =requests.get(url)\n\n # soup = BeautifulSoup(request.text, 'html.parser')\n # search_Results = soup.select('.kCrYT > a')\n # search_title = soup.select('.BNeawe.vvjwJb.AP7Wnd')\n\n # for i in range(len(sub_list)):\n # #なんか変な文字が入るので除く \n # site_url = str(search_Results[i].get('href').split('&sa=U&')[0].replace('/url?q=', ''))\n # #URLに日本語が含まれている場合、エンコードされているのでデコードする\n # site_url = urllib.parse.unquote(urllib.parse.unquote(site_url))\n \n # #いらない文字を削除\n # site_title = str(search_title[i]).strip('<div class="BNeawe vvjwJb AP7Wnd">').strip('</')\n # #URLに日本語が含まれている場合、エンコードされているのでデコードする\n # site_title = urllib.parse.unquote(urllib.parse.unquote(site_title))\n \n # #print(site_title)\n # hp_title[j].append(site_title)\n # hp_url[j].append(site_url)\n \n # for i in range(len(sub_list)):\n # df = pd.DataFrame({'HPtitle':hp_title[i],'HPurl':hp_url[i]})\n # df.to_csv(f'Tameshi/kyouzai_'+str(i)+'.csv',index=None,encoding='utf-8-sig')\n\n \n\n # ここではスクレイピングしてきたものをhtmlに表示させるためにいじる部分\n # read_files = glob.glob("Tameshi/*.csv")\n # dir_path = 'kyouzai'\n\n # cols = ["HPtitle", "HPurl", "Hpnumber", "student", "evaluation", "text", "date"]\n # dd =pd.DataFrame(columns = cols)\n\n # colls = ["HPtitle", "HPurl", "Hpnumber", "student", "evaluation", "text", "date", "Credibility_score", " Score_average"]\n # ddd =pd.DataFrame(columns = cols)\n\n # for i in range(len(read_files)):\n # os.makedirs("Tameshi/"+dir_path+str(i), exist_ok = True)\n # read_file = read_files[i]\n # df = pd.read_csv(read_file, encoding='utf-8')\n # length = len(df)\n # list=[]\n # for j in range(len(df)):\n # list.append(j)\n\n # df['Hpnumber'] = list\n # df['Credibility_score'] = ''\n # df.to_csv("Tameshi/kyouzai"+str(i)+"/kyouzaiDB.csv", index=None, encoding="cp932",errors='ignore')\n # dd.to_csv("Tameshi/kyouzai"+str(i)+"/review_prac.csv", index=None, encoding="cp932",errors='ignore')\n # ddd.to_csv("Tameshi/kyouzai"+str(i)+"/review_score.csv", index=None, encoding="cp932",errors='ignore')) #memo(<!DOCTYPE html>\n<html lang="ja">\n\n<head>\n <meta charset="UTF-8">\n <meta http-equiv="X-UA-Compatible" content="IE=edge">\n <meta name="viewport" content="width=device-width, initial-scale=1.0">\n <title>Document</title>\n</head>\n\n<style>\n h1 {\n padding: 0.4em 0.5em;\n /*文字の上下 左右の余白*/\n color: #494949;\n /*文字色*/\n background: #f4f4f4;\n /*背景色*/\n border-left: solid 5px #7db4e6;\n /*左線*/\n border-bottom: solid 3px #d7d7d7;\n /*下線*/\n }\n\n /* ▼テーブル全体の装飾 */\n table.sample {\n border-collapse: collapse;\n /* テーブルの罫線を重ねて1本に見せる */\n border: 2px solid green;\n /* テーブルの外側の枠線(2pxで緑色の実線) */\n }\n\n /* ▼セル共通の装飾 */\n table.sample th,\n table.sample td {\n border: 1px solid green;\n /* テーブルの内側の罫線(1pxで緑色の実線) */\n padding: 0.3em;\n }\n\n /* ▼見出しセルの装飾 */\n table.sample th {\n background-color: #ccffcc;\n /* 背景色(淡い緑色) */\n padding: 0.3em;\n /* 内側の余白(0.3文字分) */\n }\n\n /* ▼リンクの上にマウスが載った際の装飾(背景色だけ指定) */\n a:hover {\n background-color: #fcfcaa;\n }\n\n .evaluation {\n display: flex;\n flex-direction: row-reverse;\n justify-content: center;\n }\n\n .evaluation input[type='radio'] {\n display: none;\n }\n\n .evaluation label {\n position: relative;\n padding: 10px 10px 0;\n color: gray;\n cursor: pointer;\n font-size: 30px;\n }\n\n .evaluation label .text {\n position: absolute;\n left: 0;\n top: 0;\n right: 0;\n text-align: center;\n font-size: 12px;\n color: gray;\n }\n\n .evaluation label:hover,\n .evaluation label:hover~label,\n .evaluation input[type='radio']:checked~label {\n color: #ffcc00;\n }\n\n dt {\n margin-top: 1em;\n }\n\n #test1 {\n width: 240px;\n height: 50px;\n background: white url(メモリ画像.gif) no-repeat 0 .6em;\n }\n\n #test1 label {\n display: block;\n width: 48px;\n float: left;\n }\n\n /* 上記↑評価１のCSS 下記↓評価２のCSS */\n #test2 {\n width: 240px;\n }\n\n #test2 label,\n #test2 input {\n display: block;\n }\n\n #test2 label {\n width: 48px;\n float: left;\n text-indent: 6px;\n }\n</style>\n\n\n<body>\n <a href="/math1_">キーワード選択画面に戻る<br></a>\n <h1>{{title}}</h1>\n <p>ホームページ教材</p>\n <table class="sample">\n <tr>\n <th>No.</th>\n <th>HPname</th>\n <th>評価スコア</th>\n <th>レビュー本文</th>\n <th>評価ボタン</th>\n <th>評価</th>\n </tr>\n <tr>\n <th>1</th>\n <td><a href='{{kyouzai_url1}}'>{{kyouzai_title1}}</a></td>\n <form action="/math1_1_Review" method="post">\n <input type="hidden" name="number" value="0">\n <td>\n <select name="evaluation">\n <option hidden>評価してね</option>\n <option value="1">非常に悪い</option>\n <option value="2">悪い</option>\n <option value="3">普通</option>\n <option value="4">良い</option>\n <option value="5">非常に良い</option>\n </select>\n </td>\n <td>\n <input type="text" name="text" placeholder="text" maxlength="500"\n style="width: 200px; height: 50px;">\n </td>\n <td>\n <p><input type="submit" value="評価する"></p>\n </td>\n </form>\n <td>\n {{score1}}\n </td>\n\n\n </tr>\n <tr>\n <th>2</th>\n <td><a href='{{kyouzai_url2}}'>{{kyouzai_title2}}</a></td>\n <form action="/math1_1_Review" method="post">\n <input type="hidden" name="number" value="1">\n <td>\n <select name="evaluation">\n <option hidden>評価してね</option>\n <option value="1">非常に悪い</option>\n <option value="2">悪い</option>\n <option value="3">普通</option>\n <option value="4">良い</option>\n <option value="5">非常に良い</option>\n </select>\n </td>\n <td>\n <input type="text" name="text" placeholder="text" maxlength="500"\n style="width: 200px; height: 50px;">\n </td>\n <td>\n <p><input type="submit" value="評価する"></p>\n </td>\n </form>\n <td>\n {{score2}}\n </td>\n\n\n </tr>\n <tr>\n <th>3</th>\n <td><a href='{{kyouzai_url3}}'>{{kyouzai_title3}}</a></td>\n <form action="/math1_1_Review" method="post">\n <input type="hidden" name="number" value="2">\n <td>\n <select name="evaluation">\n <option hidden>評価してね</option>\n <option value="1">非常に悪い</option>\n <option value="2">悪い</option>\n <option value="3">普通</option>\n <option value="4">良い</option>\n <option value="5">非常に良い</option>\n </select>\n </td>\n <td>\n <input type="text" name="text" placeholder="text" maxlength="500"\n style="width: 200px; height: 50px;">\n </td>\n <td>\n <p><input type="submit" value="評価する"></p>\n </td>\n </form>\n <td>\n {{score3}}\n </td>\n\n\n </tr>\n </table>\n\n <p>★未評価HP★</p>\n <table class="sample">\n <tr>\n <th>No.</th>\n <th>HPname</th>\n <th>評価スコア</th>\n <th>レビュー本文</th>\n <th>評価ボタン</th>\n </tr>\n <tr>\n <th>1</th>\n <td><a href='{{mihyouka_url1}}'>{{mihyouka_title1}}</a></td>\n <form action="/math1_1_mihyouka_Review" method="post">\n <input type="hidden" name="number" value="0">\n <td>\n <select name="evaluation">\n <option hidden>評価してね</option>\n <option value="1">非常に悪い</option>\n <option value="2">悪い</option>\n <option value="3">普通</option>\n <option value="4">良い</option>\n <option value="5">非常に良い</option>\n </select>\n </td>\n <td>\n <input type="text" name="text" placeholder="text" maxlength="500"\n style="width: 200px; height: 50px;">\n </td>\n <td>\n <p><input type="submit" value="評価する"></p>\n </td>\n </form>\n </tr>\n <tr>\n <th>2</th>\n <td><a href='{{mihyouka_url2}}'>{{mihyouka_title2}}</a></td>\n <form action="/math1_1_mihyouka_Review" method="post">\n <input type="hidden" name="number" value="1">\n <td>\n <select name="evaluation">\n <option hidden>評価してね</option>\n <option value="1">非常に悪い</option>\n <option value="2">悪い</option>\n <option value="3">普通</option>\n <option value="4">良い</option>\n <option value="5">非常に良い</option>\n </select>\n </td>\n <td>\n <input type="text" name="text" placeholder="text" maxlength="500"\n style="width: 200px; height: 50px;">\n </td>\n <td>\n <p><input type="submit" value="評価する"></p>\n </td>\n </form>\n </tr>\n <tr>\n <th>3</th>\n <td><a href='{{mihyouka_url3}}'>{{mihyouka_title3}}</a></td>\n <form action="/math1_1_mihyouka_Review" method="post">\n <input type="hidden" name="number" value="2">\n <td>\n <select name="evaluation">\n <option hidden>評価してね</option>\n <option value="1">非常に悪い</option>\n <option value="2">悪い</option>\n <option value="3">普通</option>\n <option value="4">良い</option>\n <option value="5">非常に良い</option>\n </select>\n </td>\n <td>\n <input type="text" name="text" placeholder="text" maxlength="500"\n style="width: 200px; height: 50px;">\n </td>\n <td>\n <p><input type="submit" value="評価する"></p>\n </td>\n </form>\n </tr>\n </table>\n\n\n\n</body>\n\n</html>) #memo(################################################################################################\n#############################################数学１############################\n################################################################################################\n@app.route("/aiueo", methods=['GET','POST'])\ndef aiueo():\n return render_template('/数学１/aiueo.html')\n\n\n@app.route("/math1_")\ndef math1_():\n # df_key = pd.read_csv("Kamoku/数学１/数学１.csv",encoding="cp932",names= ['key'])\n df_key = pd.read_csv("csv_save/オペレーションズ・リサーチ.csv", encoding="cp932", names = ['key'])\n keyword = []\n\n for i in range(len(df_key)):\n keyword.append(df_key.loc[i,'key'])\n\n return render_template('/数学１/math1__syr.html', \n key_word1 = keyword[0],\n key_word2 = keyword[1],\n key_word3 = keyword[2],\n key_word4 = keyword[3],\n key_word5 = keyword[4],\n key_word6 = keyword[5],\n key_word7 = keyword[6],\n key_word8 = keyword[7],\n key_word9 = keyword[8],\n key_word10 = keyword[9],\n key_word11 = keyword[10],\n key_word12 = keyword[11],\n key_word13 = keyword[12],\n key_word14 = keyword[13],\n key_word15 = keyword[14],\n )\n\n###########キーワード1つ目########################\n#################################################\n@app.route("/math1_1")\ndef math1_1():\n # df_key = pd.read_csv("Kamoku/数学１/数学１.csv",encoding="cp932",names= ['key'])\n df_key = pd.read_csv("csv_save/オペレーションズ・リサーチ.csv", encoding="cp932", names = ['key'])\n keyword = []\n for i in range(len(df_key)):\n keyword.append(df_key.loc[i,'key'])\n \n #HP\n # kyouzaiDB = pd.read_csv('Kamoku/数学１/Kyouzai/kyouzai0/kyouzaiDB.csv', encoding="cp932")\n kyouzaiDB = pd.read_csv('Tameshi/kyouzai0/kyouzaiDB.csv', encoding="cp932")\n # review_df = pd.read_csv("Kamoku/数学１/Kyouzai/kyouzai0/review_prac.csv",encoding="cp932")\n review_df = pd.read_csv("Tameshi/kyouzai0/review_prac.csv",encoding="cp932")\n\n kyouzai_title_list = []\n kyouzai_url_list = []\n mihyouka_kyouzai_title_list = []\n mihyouka_kyouzai_url_list = []\n length = []\n\n index = list(kyouzaiDB.query(f'Credibility_score.isnull()',engine='python').index)\n number = kyouzaiDB['Hpnumber']\n\n for i in range(3):\n kyouzai_title_list.append(kyouzaiDB.iloc[i,0])\n kyouzai_url_list.append(kyouzaiDB.iloc[i,1])\n mihyouka_kyouzai_title_list.append(kyouzaiDB.iloc[index[i],0])\n mihyouka_kyouzai_url_list.append(kyouzaiDB.iloc[index[i],1])\n length.append(len(list(review_df.query(f'Hpnumber == "{number[i]}"').index)))\n \n # update_df = pd.read_csv("Kamoku/数学１/Kyouzai/kyouzai0/kyouzaiDB.csv", encoding="cp932")\n update_df = pd.read_csv("Tameshi/kyouzai0/kyouzaiDB.csv", encoding="cp932")\n score_list=[]\n #Credibility_scoreをscore_listに追加する（上から３つ）\n for i in range(3):\n score_list.append(update_df.iat[i,3])\n \n\n #youtubeについて\n # youtubeDB = pd.read_csv('Kamoku/数学１/Kyouzai/kyouzai0/video_kyouzai.csv',encoding='cp932')\n # video_review_df = pd.read_csv('Kamoku/数学１/Kyouzai/kyouzai0/video_Review.csv',encoding='cp932')\n\n # video_title_list = []\n # video_url_list = []\n # video_id_list = []\n # mihyouka_video_title_list = []\n # mihyouka_video_url_list = []\n # mihyouka_video_id_list = []\n # video_length = []\n # video_index = list(youtubeDB.query(f'Credibility_score.isnull()',engine='python').index)\n # yo = youtubeDB['Youtubenumber']\n\n # for i in range(3):\n # video_title_list.append(youtubeDB.iat[i,0])\n # video_url_list.append(youtubeDB.iat[i,1])\n # video_id_list.append(youtubeDB.iat[i,3])\n # mihyouka_video_title_list.append(youtubeDB.iat[video_index[i],0])\n # mihyouka_video_url_list.append(youtubeDB.iat[video_index[i],1])\n # mihyouka_video_id_list.append(youtubeDB.iat[video_index[i],3])\n # video_length.append(len(list(video_review_df.query(f'Youtubenumber == "{yo[i]}"').index)))\n\n # video_update_df = pd.read_csv('Kamoku/数学１/Kyouzai/kyouzai0/video_kyouzai.csv',encoding='cp932')\n # video_score_list = []\n # for i in range(3):\n # video_score_list.append(video_update_df.iat[i,4])\n\n\n return render_template("/数学１/math1_1_1.html", title= keyword[0],\n kyouzai_title1 = kyouzai_title_list[0], kyouzai_url1 = kyouzai_url_list[0],\n kyouzai_title2 = kyouzai_title_list[1], kyouzai_url2 = kyouzai_url_list[1],\n kyouzai_title3 = kyouzai_title_list[2], kyouzai_url3 = kyouzai_url_list[2],\n mihyouka_title1 = mihyouka_kyouzai_title_list[0], mihyouka_url1 = mihyouka_kyouzai_url_list[0],\n mihyouka_title2 = mihyouka_kyouzai_title_list[1], mihyouka_url2 = mihyouka_kyouzai_url_list[1],\n mihyouka_title3 = mihyouka_kyouzai_title_list[2], mihyouka_url3 = mihyouka_kyouzai_url_list[2],\n length1 = length[0], length2=length[1], length3=length[2],\n # video_title1 = video_title_list[0],video_url1 = video_url_list[0],video_id1 = video_id_list[0],\n # video_title2 = video_title_list[1],video_url2 = video_url_list[1],video_id2 = video_id_list[1],\n # video_title3 = video_title_list[2],video_url3 = video_url_list[2],video_id3 = video_id_list[2],\n # mihyouka_video_title1 = mihyouka_video_title_list[0],mihyouka_video_url1 = mihyouka_video_url_list[0],\n # mihyouka_video_title2 = mihyouka_video_title_list[1],mihyouka_video_url2 = mihyouka_video_url_list[1],\n # mihyouka_video_title3 = mihyouka_video_title_list[2],mihyouka_video_url3 = mihyouka_video_url_list[2],\n # mihyouka_video_id1 = mihyouka_video_id_list[0],mihyouka_video_id2 = mihyouka_video_id_list[1],mihyouka_video_id3 = mihyouka_video_id_list[2],\n # video_length1 = video_length[0],video_length2=video_length[1],video_length3=video_length[2],\n score1 = score_list[0],score2 = score_list[1],score3 = score_list[2]\n # video_score1 = video_score_list[0],video_score2 = video_score_list[1],video_score3 = video_score_list[2]\n )\n\n@app.route('/math1_1_Review',methods = ["post"])\ndef math1_1_Review():\n # df_key = pd.read_csv("Kamoku/数学１/数学１.csv",encoding="cp932",names= ['key'])\n df_key = pd.read_csv("csv_save/オペレーションズ・リサーチ.csv", encoding="cp932", names = ['key'])\n keyword = []\n for i in range(len(df_key)):\n keyword.append(df_key.loc[i,'key'])\n\n # kyouzaiDB = pd.read_csv('Kamoku/数学１/Kyouzai/kyouzai0/kyouzaiDB.csv', encoding="cp932")\n kyouzaiDB = pd.read_csv('Tameshi/kyouzai0/kyouzaiDB.csv', encoding="cp932")\n number = int(request.form['number'])\n HPnumber = kyouzaiDB.iloc[number,2] \n HPtitle = kyouzaiDB.iloc[number,0]\n HPurl = kyouzaiDB.iloc[number,1]\n evaluation = int(request.form['evaluation'])\n text = request.form['text']\n\n #レビューした学籍番号を取得\n #studentnumber = session["user"]\n studentnumber = "2155016"\n\n #レビューした日付と時間を取得する\n dt = datetime.datetime.now()\n dtt = dt.replace(microsecond=0)\n date = dtt.strftime("%Y/%#m/%#d %H:%M") \n # date = dtt.strftime("%Y/%-m/%-d %H:%M")\n #上で取得したデータを review_list に保存する\n review_list = [HPtitle, HPurl, HPnumber, studentnumber, evaluation, text, date]\n\n # with open("Kamoku/数学１/Kyouzai/kyouzai0/review_prac.csv","a",encoding="cp932",newline='') as f:\n with open("Tameshi/kyouzai0/review_prac.csv","a",encoding="cp932",newline='') as f:\n writer = csv.writer(f,delimiter=',')\n writer.writerow(review_list)\n\n # df = pd.read_csv("Kamoku/数学１/Kyouzai/kyouzai0/review_prac.csv",encoding="cp932")\n df = pd.read_csv("Tameshi/kyouzai0/review_prac.csv",encoding="cp932")\n # saveDB = "Kamoku/数学１/Kyouzai/kyouzai0/kyouzaiDB.csv"\n saveDB = "Tameshi/kyouzai0/kyouzaiDB.csv"\n\n S_score_norm = Similarity(df)\n I_score_norm = Informative(df)\n C_score_norm = Concentration(df) \n Credibility_score, Ave_score = Credibility(S_score_norm, I_score_norm, C_score_norm, HPnumber, df)\n review_score = [HPtitle, HPurl, HPnumber, studentnumber, evaluation, text, date, Credibility_score, Ave_score]\n\n # with open("Kamoku/数学１/Kyouzai/kyouzai0/review_score.csv", "a", encoding="cp932",newline='') as f:\n with open("Tameshi/kyouzai0/review_score.csv", "a", encoding="cp932",newline='') as f:\n writer = csv.writer(f,delimiter=',')\n writer.writerow(review_score)\n\n #Youtube\n # youtubeDB = pd.read_csv('Kamoku/数学１/Kyouzai/kyouzai0/video_kyouzai.csv',encoding="cp932")\n # video_review_df = pd.read_csv('Kamoku/数学１/Kyouzai/kyouzai0/video_Review.csv',encoding='cp932')\n # video_title_list = []\n # video_url_list = []\n # video_id_list = []\n # mihyouka_video_title_list = []\n # mihyouka_video_url_list = []\n # mihyouka_video_id_list = []\n # video_length = []\n # video_index = list(youtubeDB.query(f'Credibility_score.isnull()',engine='python').index)\n # yo = youtubeDB['Youtubenumber']\n # for i in range(3):\n # video_title_list.append(youtubeDB.iat[i,0])\n # video_url_list.append(youtubeDB.iat[i,1])\n # video_id_list.append(youtubeDB.iat[i,3])\n # mihyouka_video_title_list.append(youtubeDB.iat[video_index[i],0])\n # mihyouka_video_url_list.append(youtubeDB.iat[video_index[i],1])\n # mihyouka_video_id_list.append(youtubeDB.iat[video_index[i],3])\n # video_length.append(len(list(video_review_df.query(f'Youtubenumber == "{yo[i]}"').index)))\n\n\n kyouzai_title_list, kyouzai_url_list, mihyouka_kyouzai_title_list, mihyouka_kyouzai_url_list, length =\\n kousinn01(kyouzaiDB, Credibility_score, HPnumber,df,saveDB)\n # kousinn_df = pd.read_csv("Kamoku/数学１/Kyouzai/kyouzai0/kyouzaiDB.csv",encoding="cp932")\n kousinn_df = pd.read_csv("Tameshi/kyouzai0/kyouzaiDB.csv",encoding="cp932")\n score_list = []\n for i in range(3):\n score_list.append(kousinn_df.iat[i,3])\n\n # video_kousinn_df = pd.read_csv('Kamoku/数学１/Kyouzai/kyouzai0/video_kyouzai.csv',encoding='cp932')\n # video_score_list = []\n # for i in range(3):\n # video_score_list.append(video_kousinn_df.iat[i,4])\n\n return render_template("/数学１/math1_1_1.html",title = keyword[0],\n kyouzai_title1 = kyouzai_title_list[0],kyouzai_url1 = kyouzai_url_list[0],\n kyouzai_title2 = kyouzai_title_list[1],kyouzai_url2 = kyouzai_url_list[1],\n kyouzai_title3 = kyouzai_title_list[2],kyouzai_url3 = kyouzai_url_list[2],\n mihyouka_title1 = mihyouka_kyouzai_title_list[0], mihyouka_url1 = mihyouka_kyouzai_url_list[0],\n mihyouka_title2 = mihyouka_kyouzai_title_list[1], mihyouka_url2 = mihyouka_kyouzai_url_list[1],\n mihyouka_title3 = mihyouka_kyouzai_title_list[2], mihyouka_url3 = mihyouka_kyouzai_url_list[2],\n length1 = length[0], length2=length[1], length3=length[2],\n # video_title1 = video_title_list[0],video_url1 = video_url_list[0],video_id1 = video_id_list[0],\n # video_title2 = video_title_list[1],video_url2 = video_url_list[1],video_id2 = video_id_list[1],\n # video_title3 = video_title_list[2],video_url3 = video_url_list[2],video_id3 = video_id_list[2],\n # mihyouka_video_title1 = mihyouka_video_title_list[0],mihyouka_video_url1 = mihyouka_video_url_list[0],\n # mihyouka_video_title2 = mihyouka_video_title_list[1],mihyouka_video_url2 = mihyouka_video_url_list[1],\n # mihyouka_video_title3 = mihyouka_video_title_list[2],mihyouka_video_url3 = mihyouka_video_url_list[2],\n # mihyouka_video_id1 = mihyouka_video_id_list[0],mihyouka_video_id2 = mihyouka_video_id_list[1],mihyouka_video_id3S = mihyouka_video_id_list[2],\n # video_length1 = video_length[0],video_length2=video_length[1],video_length3=video_length[2],\n score1 = score_list[0],score2 = score_list[1],score3 = score_list[2]\n # video_score1 = video_score_list[0],video_score2 = video_score_list[1],video_score3 = video_score_list[2]\n )\n\n@app.route("/math1_1_mihyouka_Review", methods=["POST"])\ndef math1_1_mihyouka_Review():\n ##キーワード取得のための部分##\n # df_key = pd.read_csv("Kamoku/数学１/数学１.csv",encoding="cp932",names= ['key'])\n df_key = pd.read_csv("csv_save/オペレーションズ・リサーチ.csv", encoding="cp932", names = ['key'])\n keyword = []\n for i in range(len(df_key)):\n keyword.append(df_key.loc[i,'key'])\n ############################\n\n # kyouzaiDB = pd.read_csv('Kamoku/数学１/Kyouzai/kyouzai0/kyouzaiDB.csv', encoding="cp932")\n kyouzaiDB = pd.read_csv('tameshi/kyouzai0/kyouzaiDB.csv', encoding="cp932")\n number = int(request.form['number'])\n #index = list(kyouzaiDB.reset_index().query(f'Credibility_score == "{np.nan}"').index)\n index = list(kyouzaiDB.reset_index().query(f'Credibility_score.isnull()').index)\n HPnumber = kyouzaiDB.iloc[index[number],2]\n HPtitle = kyouzaiDB.iloc[index[number],0]\n HPurl = kyouzaiDB.iloc[index[number],1]\n evaluation = int(request.form['evaluation'])\n text = request.form['text']\n\n #studentnumber = session["user"]\n studentnumber = "2155016"\n\n dt = datetime.datetime.now()\n dtt = dt.replace(microsecond=0)\n date = dtt.strftime("%Y/%-m/%-d %H:%M")\n review_list = [HPtitle,HPurl,HPnumber,studentnumber,evaluation,text,date]\n\n # with open("Kamoku/数学１/Kyouzai/kyouzai0/review_prac.csv","a",encoding="cp932",newline='') as f:\n with open("Tameshi/kyouzai0/review_prac.csv","a",encoding="cp932",newline='') as f:\n writer = csv.writer(f,delimiter=',')\n writer.writerow(review_list)\n #評価によって並べ替える\n # df = pd.read_csv("Kamoku/数学１/Kyouzai/kyouzai0/review_prac.csv",encoding="cp932")\n df = pd.read_csv("Tameshi/kyouzai0/review_prac.csv",encoding="cp932")\n # saveDB = "Kamoku/数学１/Kyouzai/kyouzai0/kyouzaiDB.csv"\n saveDB = "Tameshi/kyouzai0/kyouzaiDB.csv"\n\n\n #Youtube\n # youtubeDB = pd.read_csv('Kamoku/数学１/Kyouzai/kyouzai0/video_kyouzai.csv', encoding="cp932")\n # video_review_df = pd.read_csv('Kamoku/数学１/Kyouzai/kyouzai0/video_Review.csv',encoding='cp932')\n\n # video_title_list = []\n # video_url_list = []\n # video_id_list = []\n # mihyouka_video_title_list = []\n # mihyouka_video_url_list = []\n # mihyouka_video_id_list = []\n # video_length = []\n # video_index = list(youtubeDB.query(f'Credibility_score.isnull()',engine='python').index)\n # yo = youtubeDB['Youtubenumber']\n\n # for i in range(3):\n # video_title_list.append(youtubeDB.iat[i,0])\n # video_url_list.append(youtubeDB.iat[i,1])\n # video_id_list.append(youtubeDB.iat[i,3])\n # mihyouka_video_title_list.append(youtubeDB.iat[video_index[i],0])\n # mihyouka_video_url_list.append(youtubeDB.iat[video_index[i],1])\n # mihyouka_video_id_list.append(youtubeDB.iat[video_index[i],3])\n # video_length.append(len(list(video_review_df.query(f'Youtubenumber == "{yo[i]}"').index)))\n\n\n S_score_norm = Similarity(df)\n I_score_norm = Informative(df)\n C_score_norm = Concentration(df)\n Credibility_score,Ave_score = Credibility(S_score_norm,I_score_norm,C_score_norm,HPnumber,df)\n review_score = [HPtitle,HPurl,HPnumber,studentnumber,evaluation,text,date,Credibility_score,Ave_score]\n\n # with open("Kamoku/数学１/Kyouzai/kyouzai0/review_score.csv", "a", encoding="cp932",newline='') as f:\n with open("Tameshi/kyouzai0/review_score.csv", "a", encoding="cp932",newline='') as f:\n writer = csv.writer(f,delimiter=',')\n writer.writerow(review_score)\n\n kyouzai_title_list,kyouzai_url_list,mihyouka_kyouzai_title_list,mihyouka_kyouzai_url_list,length =\\n kousinn01(kyouzaiDB,Credibility_score,HPnumber,df,saveDB)\n\n # kousinn_df = pd.read_csv("Kamoku/数学１/Kyouzai/kyouzai0/kyouzaiDB.csv",encoding="cp932")\n kousinn_df = pd.read_csv("Tameshi/kyouzai0/kyouzaiDB.csv",encoding="cp932")\n score_list = []\n for i in range(3):\n score_list.append(kousinn_df.iat[i,3])\n \n # video_kousinn_df = pd.read_csv('Kamoku/数学１/Kyouzai/kyouzai0/video_kyouzai.csv',encoding='cp932')\n # video_score_list = []\n # for i in range(3):\n # video_score_list.append(video_kousinn_df.iat[i,4])\n \n\n return render_template("/数学１/math1_1_1.html",title = keyword[0],\n kyouzai_title1 = kyouzai_title_list[0],kyouzai_url1 = kyouzai_url_list[0],\n kyouzai_title2 = kyouzai_title_list[1],kyouzai_url2 = kyouzai_url_list[1],\n kyouzai_title3 = kyouzai_title_list[2],kyouzai_url3 = kyouzai_url_list[2],\n mihyouka_title1 = mihyouka_kyouzai_title_list[0],mihyouka_url1 = mihyouka_kyouzai_url_list[0],\n mihyouka_title2 = mihyouka_kyouzai_title_list[1],mihyouka_url2 = mihyouka_kyouzai_url_list[1],\n mihyouka_title3 = mihyouka_kyouzai_title_list[2],mihyouka_url3 = mihyouka_kyouzai_url_list[2],\n length1 = length[0],length2=length[1],length3=length[2],\n # video_title1 = video_title_list[0],video_url1 = video_url_list[0],video_id1 = video_id_list[0],\n # video_title2 = video_title_list[1],video_url2 = video_url_list[1],video_id2 = video_id_list[1],\n # video_title3 = video_title_list[2],video_url3 = video_url_list[2],video_id3 = video_id_list[2],\n # mihyouka_video_title1 = mihyouka_video_title_list[0],mihyouka_video_url1 = mihyouka_video_url_list[0],\n # mihyouka_video_title2 = mihyouka_video_title_list[1],mihyouka_video_url2 = mihyouka_video_url_list[1],\n # mihyouka_video_title3 = mihyouka_video_title_list[2],mihyouka_video_url3 = mihyouka_video_url_list[2],\n # mihyouka_video_id1 = mihyouka_video_id_list[0],mihyouka_video_id2 = mihyouka_video_id_list[1],mihyouka_video_id3S = mihyouka_video_id_list[2],\n # video_length1 = video_length[0],video_length2=video_length[1],video_length3=video_length[2],\n score1 = score_list[0],score2 = score_list[1],score3 = score_list[2]\n # video_score1 = video_score_list[0],video_score2 = video_score_list[1],video_score3 = video_score_list[2]\n )) #memo(https://tanuhack.com/flask-client2server/#i-2\n\nhttps://qiita.com/kiyokiyo_kzsby/items/0184973e9de0ea9011ed#html%E3%81%AB%E3%83%95%E3%82%A9%E3%83%BC%E3%83%A0%E3%82%92%E8%BF%BD%E5%8A%A0%E3%81%99%E3%82%8B\n\nhttps://tech-diary.net/flask-introduction/#index_id12) #memo(<!DOCTYPE html>\n<html lang="ja">\n\n<head>\n <meta charset="UTF-8">\n <meta http-equiv="X-UA-Compatible" content="IE=edge">\n <meta name="viewport" content="width=device-width, initial-scale=1.0">\n <link rel="stylesheet" href="../static/syrabus.css">\n <title>Document</title>\n</head>\n\n\n\n<body>\n <a href="/top">科目選択画面に戻る<br></a>\n <div class="clearfix">\n <!-- シラバスのURLを貼る -->\n <!--\n <object\n data="https://tpuwswebsv.pu-toyama.ac.jp/public/web/Syllabus/WebSyllabusSansho/UI/WSL_SyllabusSansho.aspx?P1=1012111&P2=2022&P3=20221001"\n width="900" height="1000">\n </object>\n -->\n <iframe src="{{url_for('aiueo')}}" width="900" height="1000"></iframe>\n\n <br>\n\n <!-- キーワードの個数に応じて作る -->\n <table class="sample">\n <tr>\n <th>キーワード</th>\n </tr>\n <tr>\n <td><a href="{{ url_for('math1_1') }}">{{key_word1}}</a></td>\n </tr>\n <tr>\n <td><a href="{{ url_for('math1_2') }}">{{key_word2}}</a></td>\n </tr>\n <tr>\n <td><a href="{{ url_for('math1_3') }}">{{key_word3}}</a></td>\n </tr>\n <tr>\n <td><a href="{{ url_for('math1_4') }}">{{key_word4}}</a></td>\n </tr>\n \n <tr>\n <td><a href="{{ url_for('math1_1') }}">{{key_word5}}</a></td>\n </tr>\n <tr>\n <td><a href="{{ url_for('math1_1') }}">{{key_word6}}</a></td>\n </tr>\n <tr>\n <td><a href="{{ url_for('math1_1') }}">{{key_word7}}</a></td>\n </tr>\n <tr>\n <td><a href="{{ url_for('math1_1') }}">{{key_word8}}</a></td>\n </tr>\n <tr>\n <td><a href="{{ url_for('math1_1') }}">{{key_word9}}</a></td>\n </tr>\n <tr>\n <td><a href="{{ url_for('math1_1') }}">{{key_word10}}</a></td>\n </tr>\n <tr>\n <td><a href="{{ url_for('math1_1') }}">{{key_word11}}</a></td>\n </tr>\n <tr>\n <td><a href="{{ url_for('math1_1') }}">{{key_word12}}</a></td>\n </tr>\n <tr>\n <td><a href="{{ url_for('math1_1') }}">{{key_word13}}</a></td>\n </tr>\n <tr>\n <td><a href="{{ url_for('math1_1') }}">{{key_word14}}</a></td>\n </tr>\n <tr>\n <td><a href="{{ url_for('math1_1') }}">{{key_word15}}</a></td>\n </tr>\n\n\n </table>\n </div>\n\n</body>\n\n</html>) #memo(flask関連のやつ\n\nhttps://qiita.com/m3y/items/45c7be319e401b24fca8\n\nhttps://www.ravness.com/posts/apacheflask\n\nhttps://qiita.com/kiyokiyo_kzsby/items/0184973e9de0ea9011ed#%E6%9A%97%E5%8F%B7%E5%8C%96%E3%82%AD%E3%83%BC%E6%83%85%E5%A0%B1%E3%82%92%E6%89%B1%E3%81%86%E3%83%95%E3%82%A1%E3%82%A4%E3%83%ABkeypy%E3%81%AE%E4%BD%9C%E6%88%90) #memo(https://schoo.jp/biz/column/205\n\nhttps://gakkai.univcoop.or.jp/pcc/2018/papers/pdf/pcc097.pdf\n\nhttps://www.jstage.jst.go.jp/article/jjrm/64/5/64_877/_pdf\n\ne ラーニングを活用した基礎看護技術の学習支援の評価\n\n不登校児童生徒の学習支援における e ラーニングの活用に関する考察\n\n大学における e ラーニング導入教育についての考察\n\nhttps://learningbox.online/2022/11/30/blog-new-employee-training-e-learning/\n\nhttps://satt.jp/e-learning/e-learning.html\n\nhttps://www.digital-knowledge.co.jp/el-knowledge/e-learning/\n\nhttps://www.yano.co.jp/press-release/show/press_id/2970\n\n\nhttps://www.jstage.jst.go.jp/article/arepj/53/0/53_156/_pdf\n\nhttps://ipsj.ixsq.nii.ac.jp/ej/?action=pages_view_main&active_action=repository_view_main_item_detail&item_id=64176&item_no=1&page_id=13&block_id=8\n\n) #memo(協調フィルタリング 参考サイト\nhttps://takuti.me/ja/note/two-decades-of-amazon-recommender/\n\n甲南大学ＧＰＡ\n甲南大学マネジメント創造学部(CUBE生)のGPA及び\n能力向上感に影響を与える要因についての調査報告) ~
