IG-Scraping-BigData33.ipynb

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      "https://www.instagram.com/explore/tags/kabinetindonesiamaju/?__a=1\n",
      "200\n",
      "\"kabinetindonesiamaju\"\n",
      "false\n",
      "\"https://instagram.fbdo4-1.fna.fbcdn.net/vp/1a885a1db0a883b68f112dc75cf9cee9/5E4AF121/t51.2885-15/e35/s150x150/72898284_152681689274980_3840659124078273825_n.jpg?_nc_ht=instagram.fbdo4-1.fna.fbcdn.net&_nc_cat=104\"\n",
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      "text/plain": [
       "\"\\nfor post in edge_hashtag_to_media:\\n    for key in keys:\\n#      print(key.upper(), ':', post.get(key))\\n      print(key, ':', post.get(key))  \\nelse:\\n    print('Oops something went wrong!')    \\n\\n\""
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   "source": [
    "# parsing a graphql instagram\n",
    "\n",
    "import json\n",
    "import requests\n",
    "\n",
    "tag = 'kabinetindonesiamaju'\n",
    "url = 'https://www.instagram.com/explore/tags/' + tag + '/?__a=1'\n",
    "'''\n",
    "keys = ['id', 'owner', 'taken_at_timestamp', 'text', 'count',\n",
    "        'video_view_count',\n",
    "        'edge_media_to_comment',\n",
    "        'edge_media_to_caption',\n",
    "        'edge_liked_by',\n",
    "        'edge_media_preview_like']\n",
    "'''\n",
    "\n",
    "keys = ['text']\n",
    "\n",
    "\n",
    "def jprint(data_dict):\n",
    "  print(json.dumps(data_dict, indent = 4))\n",
    "\n",
    "#Grab the data\n",
    "def get_ig_page(url, session=None):\n",
    "  print(url)\n",
    "  session = session or requests.Session()\n",
    "\n",
    "  r = session.get(url)\n",
    "  r_code = r.status_code\n",
    "  print(r_code)\n",
    "\n",
    "  if r_code == requests.codes.ok:\n",
    "    return r\n",
    "  else:\n",
    "    return None\n",
    "\n",
    "ig_data_dict = get_ig_page(url)\n",
    "\n",
    "\n",
    "if ig_data_dict is not None:\n",
    "  ig_data_dict = ig_data_dict.json()     #complete data crawled with graphql keyword\n",
    "#  jprint(ig_data_dict)\n",
    "\n",
    "\n",
    "  graphql = ig_data_dict.get('graphql', None) #removing graphql keyword\n",
    "#  jprint(graphql)\n",
    "\n",
    "  hashtag = graphql.get('hashtag', None) #removing hashtag keyword\n",
    "#  jprint(hashtag)\n",
    "\n",
    "  #get name\n",
    "  name = hashtag.get('name', None) \n",
    "  jprint(name)\n",
    " \n",
    "  #get is_top_media_only \n",
    "  is_top_media_only = hashtag.get('is_top_media_only', None)\n",
    "  jprint(is_top_media_only)\n",
    "\n",
    "  #get profile_pic_url\n",
    "  profile_pic_url = hashtag.get('profile_pic_url', None)\n",
    "  jprint(profile_pic_url)\n",
    "\n",
    "  #removing edge_hashtag_to_media keyword\n",
    "  edge_hashtag_to_media = hashtag.get('edge_hashtag_to_media', None)\n",
    "#  jprint(edge_hashtag_to_media)\n",
    "\n",
    "  #get count\n",
    "  count = edge_hashtag_to_media.get('count', None)\n",
    "  jprint(count)\n",
    "\n",
    "  #get page info\n",
    "  page_info = edge_hashtag_to_media.get('page_info', None)\n",
    "  jprint(page_info)\n",
    "\n",
    "  #remove edges keyword\n",
    "#  edges = edge_hashtag_to_media.dumps('edges', None)\n",
    "#  jprint(edges)\n",
    "\n",
    "  #get node\n",
    "  node = edge_hashtag_to_media.get('edges', None)\n",
    "#  jprint(node)\n",
    "\n",
    "  print (len(node))\n",
    "\n",
    "#  a = json.dumps(node)\n",
    "#  print(a)\n",
    "\n",
    "'''\n",
    "for team in json_dict['teams']:\n",
    "    print team['_links']['fixtures']['href']\n",
    "'''\n",
    "\n",
    "for post in edge_hashtag_to_media['edges']:\n",
    "    print(post['node']['id'])\n",
    "    \n",
    "'''\n",
    "for post in edge_hashtag_to_media:\n",
    "    for key in keys:\n",
    "#      print(key.upper(), ':', post.get(key))\n",
    "      print(key, ':', post.get(key))  \n",
    "else:\n",
    "    print('Oops something went wrong!')    \n",
    "\n",
    "'''"
   ]
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     "text": [
      "https://www.instagram.com/explore/tags/kabinetindonesiamaju/?__a=1\n",
      "200\n",
      "\"kabinetindonesiamaju\"\n",
      "false\n",
      "\"https://instagram.fcgk8-1.fna.fbcdn.net/vp/f8b8a578b3847e8968123b91597ad64b/5E656FE2/t51.2885-15/e35/c65.0.949.949a/s150x150/75266929_693658614460091_2699463765027552938_n.jpg?_nc_ht=instagram.fcgk8-1.fna.fbcdn.net&_nc_cat=1\"\n",
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      "}\n",
      "55\n",
      "Keluarga besar Satpol PP dan Damkar Kota Mojokerto mengucapkan selamat dan sukses kepada Jenderal Polisi (Purn.) Prof. Drs. H. Muhammad Tito Karnavian, M.A., Ph.D. sebagai Menteri Dalam Negeri  periode 2019-2024\n",
      ".\n",
      "#kabinetindonesiamaju #pelantikanmenteri #pelantikan 1\n",
      "Keluarga Besar Geotour Indonesia mengucapkan selamat dan sukses kepada Bapak Wishnutama Kusubandio, atas dilantiknya sebagai Menteri Pariwisata dan Industri Kreatif pada kabinet Indonesia Maju periode 2019-2024\n",
      "\n",
      "Jaya terus Pariwisata Indonesia! \n",
      "#geopark \n",
      "#geowisataindonesia \n",
      "#kabinetindonesiamaju 2\n",
      "“Semoga” adalah sebuah harapan, yang jika diwujudkan akan membuahkan syukur. Jika tidak terwujudkan.. ya kita lihat saja nanti.\n",
      "Paling doa lagi.\n",
      ".\n",
      ".\n",
      ".\n",
      "#energiterbarukan #energibersih #enternusantara  #renewableenergy #climatecrisis #eyesonclimate #eyeonclimate #climateemergency #climateemergencydeclaration #dampaklingkungan #greenpeace #bersihkanindonesia #reformasidikorupsi #kabinetindonesiamaju #jokowi #jokowiamin2019 3\n",
      "Gista Putri menjadi satu sosok yang menarik perhatian dalam pelantikan menteri hari ini. Mendampingi sang Suami @wishnutama yang dilantik menjadi Menteri Pariwisata, Gista Putri pun tengah hamil 8 bulan.\n",
      "---\n",
      "Pesonanya membuat namanya jadi trending topic di Twitter dan mengundang komentar lucu dari netizen. Bagaimana menurut Mama penampilan ibu menteri yang satu ini? 😍\n",
      "---\n",
      "Selamat atas pelantikan Wishnu Tama sebagai Menteri Pariwisata dan sehat selalu Gista Putri, semoga lancar kehamilannya sampai persalinan 💜\n",
      "---\n",
      "Foto: @marlenehariman \n",
      "#Popmama #millennialmama #popmamanews #GistaPutri #WishnuTama #KabinetIndonesiaMaju 4\n",
      "🇮🇩🇮🇩🙏🤝🙏🇮🇩🇮🇩\n",
      "Selamat bertugas pak Jend. (Purn) Fachrul Razi.  @kemenag_ri\n",
      "#CongratsJokowiMarufAmin \n",
      "#KabinetJokowiAmin \n",
      "#KabinetIndonesiaMaju 5\n",
      "Selamat bekerja Kabinet Indonesia Maju⁣ periode 2019-2024⁣\n",
      "⁣⁣\n",
      "Semangat bekerja mengabdi untuk Tanah Air Indonesia 🇲🇨⁣⁣\n",
      "⁣⁣\n",
      "Btw, siapa nih menteri favorit kamu insan muda?⁣⁣\n",
      "⁣⁣\n",
      "#CumaDiArdan\n",
      "#kabinetindonesiamaju 6\n",
      "Selamat bertugas Pak Letjen TNI (Purn) Dr. dr. Terawan Agus Putranto, Sp. Rad (K) RI sebagai Menteri Kesehatan RI ( Periode 2019-2024 )\n",
      ".\n",
      "Kolose 2:7 \n",
      "Hendaklah kamu berakar di dalam Dia\n",
      "dan dibangun di atas Dia, hendaklah\n",
      "kamu bertambah teguh dalam iman yang\n",
      "telah diajarkan kepadamu, dan hendaklah\n",
      "hatimu melimpah dengan syukur.\n",
      ".\n",
      "#selamatbertugas #bertugas #letjen #TNI #terawanagusputranto #menteri #menterikesehatan #RI #indonesia @jokowi @kemenkes_ri #kabinetindonesiamaju 7\n",
      "Buat kamu yang main slot, IBOBET kini menyediakan promo terbaru \"BONUS JACKPOT SLOT UP TO 100 IDR\" untuk kamu yang mendapatkan kemenangan Big Win atau Jackpot !! Kunjungi situs kami di WWW . IBOPASTI . COM\n",
      "\n",
      "#IBOPASTI #BonusSlot #JackpotSlot #BonusJackpot #KabinetIndonesiaMaju 8\n",
      "Terima Kasih Jenderal telah memimpin kami, sehingga Polri semakin PROMOTER (Profesional, Modern dan Terpercaya),\n",
      ".\n",
      "Dan kami ucapkan Selamat dan Sukses selalu dalam mengemban amanah jabatan baru sebagai Menteri Dalam Negeri Republik Indonesia dalam Kabinet Indonesia Maju\n",
      ".\n",
      "#titokarnavian \n",
      "#kabinetindonesiamaju \n",
      "#selamatbertugaspaktito\n",
      "#kemendagri \n",
      "#polresmadiunhebat \n",
      "#madiunkampungpesilat \n",
      "#sdmunggulindonesiamaju🇲🇨 9\n",
      "Lurah dan staff/perangkat beserta warga Kelurahan Sugihwaras mengucapkan\n",
      "SELAMAT DAN SUKSES ATAS PELANTIKAN\n",
      "Menteri Kabinet Indonesia Maju 2019 - 2024\n",
      "\n",
      "#kelurahansugihwaras #sugihwaraspemalang #kecamatanpemalang #pemkabpemalang #pelantikanmenteri #kabinetindonesiamaju 10\n",
      "Apakah tipikal masyarakat +62,\n",
      "Yg selalu menganggap dirinya hebat, \n",
      "Hingga akhirnya selalu meremehkan orang2 baru\n",
      "Yg dianggapnya di bawah dirinya? -------------------------------------- 5tahun lalu, \n",
      "Kehadiran Ibu Susi Pudjiastuti, \n",
      "Ditanggapi banyak orang dg pandangan mata tak percaya, \n",
      "Yg seakan meremehkan. \n",
      "Namun, \n",
      "Seiring waktu berjalan, \n",
      "Orang mulai menghargai kerja keras dan usahanya, \n",
      "Dan pada akhirnya mengakui kemampuannya. \n",
      "Bahkan, \n",
      "Merasa kehilangan saat sosoknya lenyap dari jajaran Kabinet Indonesia Maju, \n",
      "Yg siang tadi diumumkan oleh Presiden Ir. Joko Widodo. \n",
      "Kalimat \"Tenggelamkan\",\n",
      "Yg menjadi salah satu ciri khas nya, \n",
      "Akan tinggal kenangan di hati masyarakat Indonesia... Dan hari ini pula, \n",
      "Kita terperangah dg sederet nama2 baru, \n",
      "Sosok muda yg akan membawa angin segar bagi perubahan di Indonesia. \n",
      "Salah satunya adalah sosok Nadiem Makarim,\n",
      "Sang CEO GoJek.. Dia yg memulai bisnis dari bawah, \n",
      "Dan akhirnya menjadi salah satu unicorn besar di dunia. \n",
      "Semua seakan meragukan kemampuan nya, \n",
      "Ramai2 membuat MEME yg memperlihatkan ketidak yakinan pada sosok sederhananya. \n",
      "Dia belum bekerja, \n",
      "Dan mereka di luar sana sudah sibuk mem \"bully\" ... Andai seiring waktu ternyata dia mampu menunjukkan kinerja nya, \n",
      "Masihkah mereka akan tetap mem\"bully\"nya?\n",
      "Atau bahkan berbalik memuja nya?? ... \"Jangan pernah meremehkan kemampuan orang lain, \n",
      "Belum tentu kita bisa lebih baik ketimbang mereka yg telah terpilih itu\"\n",
      "\n",
      "Tetaplah bekerja dg tulus dan ikhlas, \n",
      "Dan biarkan semesta yg akan menyelesaikannya utkmu... Terima kasih,  Ibu Susi Pudjiastuti, \n",
      "Yg telah mengajak kita utk tidak menyerah pada nasib. \n",
      "Selamat bekerja abang Nadiem Makarim, \n",
      "Semoga bisa membawa angin segar bagi pendidikan di negeri ini. \n",
      "Salam cerdas Indonesia, \n",
      "Salam Indonesia Raya 🇮🇩🇮🇩🇮🇩 #koalisisabahatpancasila\n",
      "#KiSP #PAUDSieraPertiwi #PAUD #DinasPendidikandanKebudayaan #DinasPendidikandanKebudayaanDepok #BPIP #PancasilaCeria #Pancasila #KabinetIndonesiaMaju #nadiemmakarim #GoJek #Unicorn #Indonesia #NKRI #NKRIHargaMati # 11\n",
      "Jangan lupo, Ramaikan SCTV Karnaval di tanggal 26 - 27 Oktober atau di Hari sabtu dan minggu, Live di Lapangan Taman Olahraga Silampari (TOS). #kabarlinggau\n",
      "#lubuklinggau\n",
      "@official_st12 \n",
      "@geishaindonesia \n",
      "@ilir7band \n",
      "@limbadindonesia \n",
      "@biangindasband \n",
      "@hijaudaunmusik \n",
      "@ruben_onsu \n",
      "@yukikt \n",
      "@fero_walandouw \n",
      "@sctv \n",
      "@cintakarenacinta_official \n",
      "#kabinetindonesiamaju\n",
      "#jokowimaruf \n",
      "#prabowo \n",
      "#mentri \n",
      "#cebong \n",
      "#kampret 12\n",
      ".\n",
      "Selamat Mengabdi untuk Negeri \n",
      "Tetap Semangat dan Selamat Bekerja 💪\n",
      ".\n",
      "#kabinetindonesiamaju \n",
      "#bumnhadiruntuknegeri\n",
      "#bumn \n",
      "#perkebunannusantaragroup \n",
      "#ptpnviii \n",
      "#sahabatptpn8\n",
      "#workingclasshero 13\n",
      "Reposted from @sdppi_kominfo -  Selamat malam #SahabatFrekuensi , Seperti yg kita ketahui bersama, Menteri Kominfo periode 2019-2024 baru saja diumumkan yaitu Bapak Johnny G. Plate 🥳🥳🥳\n",
      ".\n",
      "Kami ucapkan terima kasih kepada Bapak Rudiantara yg siang tadi sudah melakukan serah terima jabatan kepada Menteri Kominfo yg baru.\n",
      ".\n",
      "#KabinetIndonesiaMaju\n",
      "#BijakPakaiFrekuensi 14\n",
      "Dalam formasi 4-4-2, inilah nama-nama yang layak dipilih untuk mengisi daftar kesebelasan Kabinet Indonesia Maju di bawah asuhan Jokowi. Oke gak, sob?\n",
      "\n",
      "Klik link di bio untuk alasan-alasannya.\n",
      "\n",
      "#KabinetIndonesiaMaju #indonesiamaju #jokowi #indosport 15\n",
      "Alhamdulillah... Selamat dan sukses @halimiskandarnu \n",
      "Mugi Mugi tansah pinaringan sehat... Anak desa ngemong desa.. #pakhalimholopiskuntulbaris #kabinetindonesiamaju 16\n",
      "Reposted from @kemenkominfo -  Selamat siang #SobatKom! Berikut ini adalah wajah-wajah Menteri Negara dalam Kabinet Indonesia Maju periode 2019-2024.\n",
      ".\n",
      "Saat mengumumkan nama-nama Menteri Negara, pagi tadi (23/10) Presiden @jokowi perintahkan 7 hal ini untuk para menteri:\n",
      "\n",
      "1. Jangan korupsi, ciptakan sistem yang menutup celah terjadinya korupsi.  2. Tidak ada visi misi Menteri, yang ada visi misi Presiden-Wakil Presiden. #KabinetIndonesiaMaju\n",
      "\n",
      "3. Kerja keras, kerja cepat, kerja produktif.\n",
      "\n",
      "4. Jangan terjebak rutinitas yang monoton.\n",
      "\n",
      "5. Kerja berorientasi hasil nyata, tugas kita tidak hanya menjamin sent, tapi delivered. #KabinetIndonesiaMaju\n",
      "\n",
      "6. Selalu cek masalah di lapangan dan temukan solusinya.\n",
      "\n",
      "7.Serius dalam bekerja. Yang tidak bersungguh-sungguh, dipastikan dicopot. #KabinetIndonesiaMaju\n",
      "\n",
      "Untuk itu, seluruh keluarga besar Kementerian Kominfo mengucapkan selamat kepada Menteri Negara #KabinetIndonesiaMaju. Semoga sukses dalam mengemban tugas barunya 🙏 - # 17\n",
      "Foto bersama #KabinetIndonesiaMaju yang diumumkan Presiden @jokowi bersama @wapres_ri KH. Ma'ruf Amin di Istana pagi ini, Rabu (23/10). Jenderal pol Tito Karnavian akan mengemban jabatan sebagai Mendagri #mendagri\n",
      "#TitoKarnavian #kapolri\n",
      "#polripromoter\n",
      "#polrihumanis\n",
      "@polisiindonesia_promoter\n",
      "@polisiindonesia\n",
      "@polantasindonesia\n",
      "@multimedia.humaspolri\n",
      "@divisihumaspolri\n",
      "@humas_poldajateng\n",
      "@ryckoad\n",
      "@je_we_98\n",
      "@bagsumda_polrespati\n",
      "@satlantaspolrespati\n",
      "@satpolair_polrespati\n",
      "@satnarkoba_respati\n",
      "@reskrimpati\n",
      "@binmas_respati\n",
      "@propam_respati42 18\n",
      "#Report@kemenperin_ri ............ Segenap keluarga besar Kementerian Perindustrian mengucapkan terima kasih atas pengabdian dan kontribusi Menteri Perindustrian periode 2016 - 2019 Bapak @airlanggahartarto4.0 untuk kemajuan industri Tanah Air dan menghantarkan Indonesia memasuki era #industri4.0. \n",
      "Selamat mengemban tugas baru sebagai Menteri Koordinator Bidang Perekonomian RI #KabinetIndonesiaMaju.\n",
      "\n",
      "Sukses selalu dimanapun Bapak bertugas. 19\n",
      "Reposted from @bps_statistics \n",
      "Pada #RabuSP kali ini, segenap keluarga BPS beserta #statmin turut mengucapkan selamat kepada para menteri yang baru dilantik dalam Kabinet Indonesia Maju. Semoga jabatan yang diemban dapat dijalani dengan profesional, integritas, dan amanah. \n",
      "Tahu gak sih #SahabatData kalau ternyata rata-rata usia menteri di kabinet ini yaitu 58 tahun. Dengan sebaran terbanyak di rentang usia 55-59 dan 60-64 tahun.\n",
      "\n",
      "Lantas bagaimana dengan karakteristik usia penduduk Indonesia? \n",
      "Dengan adanya Sensus Penduduk yang nantinya dilaksanakan tahun 2020, kita akan mengetahui karakteristik usia penduduk Indonesia. \n",
      "#RabuSP\n",
      "#SP2020\n",
      "#KabinetIndonesiaMaju\n",
      "#MencatatIndonesia 20\n",
      "Repost @kotaku.nasional \n",
      "Basuki Hadimuljono kembali dipercaya untuk mengemban amanah sebagai Menteri Pekerjaan Umum dan Perumahan Rakyat pada Kabinet Indonesia Maju 2019-2024.\n",
      "\n",
      "Keluarga besar Program Kota Tanpa Kumuh (Kotaku) mengucapkan, selamat bertugas, Pak Basuki! Tetap semangat, jaga kesehatan, dan jangan lupa bahagia. 😊🙏💕\n",
      ".\n",
      "#KotakuNasional #infokotakunasional #kotakupugoid #KabinetIndonesiaMaju #KemenPUPR\n",
      "@kemenpupr\n",
      "\n",
      "http://kotaku.pu.go.id 21\n",
      "Selamat Bekerja kepada Bapak Bambang P. S. Brodjonegoro sebagai Menteri Riset dan Teknologi/Kepala Badan Riset dan Inovasi Nasional Periode 2019 - 2024 yang baru saja dilantik... Bersama kita mampu... bersama kita menuju Indonesia Maju... #akuntansiukipaulus #ukipaulusmakassar #kabinetindonesiamaju #bersamaindonesiamaju #indonesia 22\n",
      "Let go of the past and go for the future.\n",
      "\n",
      "Saya harus bersabar dan bersyukur walaupun hari ini saya tidak dilantik menjadi menteri. Mungkin belum dibutuhkan 😁\n",
      "\n",
      "#menteripermusikan #bapakmenteri #menteri #kabinet #nkri #kabinetindonesiamaju #indonesiamaju #menterifender #menterigibson #jokowi #jokowidodo #maarufamin 23\n",
      "#Repost @kemenkominfo (@get_repost)\n",
      "・・・\n",
      "Selamat sore #SobatKom! Seperti yg kita ketahui bersama, Menteri Kominfo periode 2019-2024 baru saja diumumkan yaitu Bapak Johnny G. Plate 🥳🥳🥳\n",
      ".\n",
      "Kami ucapkan terima kasih kepada Bapak Rudiantara yg siang tadi sudah melakukan serah terima jabatan kepada Menteri Kominfo yg baru.\n",
      ".\n",
      "Menurut #SobatKom, program dan cita-cita apa yg perlu diteruskan dari Bapak Rudiantara ke Menkominfo Johnny?\n",
      ".\n",
      "#KabinetIndonesiaMaju 24\n",
      "Kren ada pak @prabowo dan @mohmahfudmd nya , tapi knapa gak ada bu @susipudjiastuti115 nya 😢😭\n",
      ".\n",
      "\n",
      "#kabinetindonesiamaju #kabinetjokowi #prabowosubianto #jokowidodo #mahfudmd 25\n",
      "Selamat atas pelantikan para menteri #kabinetIndonesiaMaju. \n",
      "Semoga 5 tahun ke depan ekonomi makin akseleratif dan situasi sosial politik makin damai kondusif. \n",
      "Kabinet rekonsiliasi yang penuh optimisme. \n",
      "Selamat bekerja.‬ From: @ridwankamil 26\n",
      "#kabinetindonesiamaju \n",
      "#kabinetjokowi \n",
      "#jokowimaruf \n",
      "#prabowosubianto \n",
      "#cebong \n",
      "#kampret 27\n",
      "Ucapan selamat kepada para MENTERI INDONESIA MAJU\n",
      "==========\n",
      "#karanganbungamentri #bungapapanmentri #menkomaritim  #menkes #kabinetindonesiamaju #pelantikanmenteri 28\n",
      "Selamat bertugas kepada seluruh menteri, semoga Amanah dalam menjalankan tugas wujudkan Indonesia Maju..!!! #KabinetIndonesiaMaju 29\n",
      "CERITA SOAL KABINET BARU! \n",
      "Serahterima Jabatan di Kementerian PUPR \"Saya serahkan seluruh tugas dan tanggungjawab pegiat senam infrastruktur kepada bapak Menteri yang baru yaitu saya\"\n",
      "\n",
      "#kementerianpupr #basukihadimuljono #infrastrukturkeren #membangundaripinggiran #perumahanrakyat #infrastructures #jalantoltranssumatera #jalantoltransjawa #jalantoltranskalimantan #toltranspapua #indonesiamaju #kabinetindonesiamaju #kabinetjokowi 30\n",
      ".\n",
      "Dengan resminya terbentuk #KabinetIndonesiaMaju segenap keluarga #BrightonRealEstate mengucapkan Selamat bekerja untuk Presiden Joko Widodo @jokowi dan Wapres Ma'ruf Amin\n",
      ".\n",
      "Berikut 7 Pesan Presiden yang dapat kita pelajari untuk kita turut mensukseskan 5 tahun kedepan ini\n",
      ".\n",
      "1. Jangan korupsi. Menciptakan sistem yang menutup celah terjadinya korupsi\n",
      ". \n",
      "2. Tidak ada visi-misi menteri, yang ada visi-misi presiden-wakil presiden\n",
      ".\n",
      "3. Semua harus kerja cepat, kerja keras, dan bekerja yang produktif\n",
      ".\n",
      "4. Jangan terjebak pada rutinitas yang monoton\n",
      ".\n",
      "5. Kerja yang berorientasi pada hasil nyata\n",
      ".\n",
      "6. Selalu mengecek masalah di lapangan dan temukan solusi\n",
      ".\n",
      "7. Semua harus serius dalam bekerja\n",
      ".\n",
      "Mari ciptakan #MimpiJadiNyata bersama!😊 31\n",
      "Pada #RabuSP kali ini, segenap keluarga BPS beserta #statmin turut mengucapkan selamat kepada para menteri yang baru dilantik dalam Kabinet Indonesia Maju. Semoga jabatan yang diemban dapat dijalani dengan profesional, integritas, dan amanah. \n",
      "Tahu gak sih #SahabatData kalau ternyata rata-rata usia menteri di kabinet ini yaitu 58 tahun. Dengan sebaran terbanyak di rentang usia 55-59 dan 60-64 tahun.\n",
      "\n",
      "Lantas bagaimana dengan karakteristik usia penduduk Indonesia? \n",
      "Dengan adanya Sensus Penduduk yang nantinya dilaksanakan tahun 2020, kita akan mengetahui karakteristik usia penduduk Indonesia. \n",
      "#SP2020\n",
      "#KabinetIndonesiaMaju\n",
      "#MencatatIndonesia 32\n",
      "Apa yang sedang kau cari, nak? Untuk apa? Adakah yang menyuruh mu? Atau hanya inisiatif mu? Jika ini kau lakukan atas kehendak mu sendiri, demi keinginan mu, sungguh aku merasa malu.\n",
      "\n",
      "Kau tak pantas berada di aspal di antara lalu lalang kendaraan pada jam-jam segini. Seharusnya kau di rumah. Isi PR atau les matematika, dan mengulang kaji tadi siang.\n",
      "\n",
      "Seragam mu semakin membuat hatiku sedih. Anak siapa kau sebenarnya? Kemana orang tua mu? Kenapa mereka membiarkan mu? Pasti kau letih, kan?\n",
      "\n",
      "Aku semakin malu pada diriku. Sungguh!\n",
      "\n",
      "Aspal Jalan Sudirman, Medan ini bukan tempat bermain, bukan tempat mencari nafkah mu. Becak saja tidak boleh lewat di kawasan  ini. Kawasan tertib lalu lintas.\n",
      "\n",
      "Di pinggir jalan itu, banyak rumah pejabat, pemangku kebijakan. Ada rumah gubernur, rumah walikota, rumah kapolda dan rumah pangdam. Nanti mereka malu, marah, jika kau terlihat di situ.\n",
      "\n",
      "Mungkin memang sengaja kau berada di perempatan itu, nak? Biar apa, coba?\n",
      "\n",
      "Nak, sengaja ku posting sekelumit derita cita mu ini di beranda ku. Aku juga harus pamerkan diri mu kepada orang - orang di jagad maya. Siapa tau ya, nak. Mungkin saja, bisa jadi ya, kan. Kau dipedulikan ya, kan.\n",
      "\n",
      "Karena kamu baru punya menteri yang baru. Menteri Pendidikan dan Kebudayaan, Nadiem Makarim. Menteri yang dipilih Presiden Joko Widodo, di jajaran Kabinet Indonesia Maju. Dipilih siang tadi, saat kau bersekolah.\n",
      "\n",
      "Setelah ini, semoga tak terlihatku lagi kau 'mengaspal' dan berharap belas kasih di tengah jalan. Di aspal cukup dilakukan abang-abang atau bapak driver online ya, nak.\n",
      "\n",
      "Sudah ya, nak. Aku mau melihat teman mu. Apakah dia belajar atau sudah tidur di rumah. Aku mau memeluk dan mencium mereka.\n",
      "\n",
      "Salam.\n",
      "\n",
      "@jokowi @nadiemmakarimofficial @edy_rahmayadi @musa_rajekshah @nasution.akhyar\n",
      ". . . \n",
      "#incekbudi #medan #indonesia #jokowi #kabinetindonesiamaju #kemendikbud #anakjalanan #nadiemmakarim #sumut #sumaterautara #sekolah #anaksekolahan 33\n",
      ".\n",
      "Selamat bertugas Pak Erick @erickthohir , Sukses !!! 🙏🙏\n",
      ".\n",
      "#kabinet #kabinetindonesiamaju #indonesiamaju #20192024 #kabinetindonesiamaju2019 #kabinetindonesiamaju20192024 34\n",
      "Selamat bekerja kembali Bapak Presiden Ir. H. Joko Widodo, Bapak Wakil Presiden K. H. Ma'ruf Amin, dan beserta jajaran Menteri kabinet, semoga Indonesia semakin maju dan semakin sukses untuk 5 tahun kedepan.\n",
      "Kabinet Indonesia Maju.\n",
      "\n",
      "#apartemen #investasisemarang #kabinetindonesiamaju #indonesia #investasi #indonesiamaju #property #propertysemarang 35\n",
      "Repost from @indonesiaunny using @RepostRegramApp - \n",
      "PTRI New York mengucapkan Selamat atas terpilihnya kembali Ibu Retno LP Marsudi sebagai Menteri Luar Negeri @Menlu_RI #KabinetIndonesiaMaju 2019-2024\n",
      ".\n",
      "Congratulations Minister Retno LP Marsudi on being re-appointed Minister for Foreign Affairs for #KabinetIndonesiaMaju 2019-2024 .\n",
      "\n",
      "#IniDiplomasi 36\n",
      "Etika jurnalis dalam menulis harus selalu berpedoman pada nilai2 Pancasila..... #SDMUnggul \n",
      "#IndonesiaMaju \n",
      "#74thIndonesia \n",
      "#KabinetIndonesiaMaju #jokowi #nawacita #PasukanRebahan #WINNER_SOSO #SAIK2019 #ShallWe2ndwin #bumn #media #viral #jurnalisme #indonesia 37\n",
      "#Repost @bps_statistics\n",
      "• • • • • •\n",
      "Pada #RabuSP kali ini, segenap keluarga BPS beserta #statmin turut mengucapkan selamat kepada para menteri yang baru dilantik dalam Kabinet Indonesia Maju. Semoga jabatan yang diemban dapat dijalani dengan profesional, integritas, dan amanah. \n",
      "Tahu gak sih #SahabatData kalau ternyata rata-rata usia menteri di kabinet ini yaitu 58 tahun. Dengan sebaran terbanyak di rentang usia 55-59 dan 60-64 tahun.\n",
      "\n",
      "Lantas bagaimana dengan karakteristik usia penduduk Indonesia? \n",
      "Dengan adanya Sensus Penduduk yang nantinya dilaksanakan tahun 2020, kita akan mengetahui karakteristik usia penduduk Indonesia. \n",
      "#RabuSP\n",
      "#SP2020\n",
      "#KabinetIndonesiaMaju\n",
      "#MencatatIndonesia 38\n",
      "Etika jurnalis dalam menulis harus selalu berpedoman pada nilai2 Pancasila..... #SDMUnggul \n",
      "#IndonesiaMaju \n",
      "#74thIndonesia \n",
      "#KabinetIndonesiaMaju #jokowi #nawacita #PasukanRebahan #WINNER_SOSO #SAIK2019 #ShallWe2ndwin #bumn #media #viral #jurnalisme #indonesia 39\n",
      "#Repost @kemenperin_ri\n",
      "• • • • • •\n",
      "Selamat menjalankan tugas sebagai Menteri Perindustrian RI kepada Bapak @agusgumiwangk .\n",
      "\n",
      "Semoga kepemimpinan Bapak @agusgumiwangk dapat melahirkan terobosan baru bagi industri nasional dan membawa Indonesia menjadi negara industri tangguh yang siap menuju era #industri4.0.\n",
      "\n",
      "#KabinetIndonesiaMaju 40\n",
      "Etika jurnalis dalam menulis harus selalu berpedoman pada nilai2 Pancasila..... #SDMUnggul \n",
      "#IndonesiaMaju \n",
      "#74thIndonesia \n",
      "#KabinetIndonesiaMaju #jokowi #nawacita #PasukanRebahan #WINNER_SOSO #SAIK2019 #ShallWe2ndwin #bumn #media #viral #jurnalisme #indonesia 41\n",
      "@jokowi @kyai_marufamin \n",
      "#kabinetindonesiamaju 42\n",
      "Ambil inti \"toleransi'a\" aja, agar menjadi pelajaran bagi kita kita yg masih menjadikan perbedaan agama sebagai penghambat hubungan antar manusia ciptaan Tuhan.. #nadiemmakarim \n",
      "#mentri\n",
      "#kabinetindonesiamaju \n",
      "#jokowi\n",
      "#gojek\n",
      "#titokarnavian 43\n",
      "Etika jurnalis dalam menulis harus selalu berpedoman pada nilai2 Pancasila..... #SDMUnggul \n",
      "#IndonesiaMaju \n",
      "#74thIndonesia \n",
      "#KabinetIndonesiaMaju #jokowi #nawacita #PasukanRebahan #WINNER_SOSO #SAIK2019 #ShallWe2ndwin #bumn #media #viral #jurnalisme #indonesia 44\n",
      "Pak Prabowo, the past competitions have left bitter taste in our mouths. Let’s prove the people wrong that bitterness is what remains.\n",
      "\n",
      "Semoga jurang pemisah antara makro dan realita keseharian berkurang dengan kerjasama DPR dan Menteri perekonomian.\n",
      "\n",
      "Melalui olahraga kita boleh belajar mentalitas siap menang dan siap kalah.\n",
      "\n",
      "Pak Wisnutama, kami tunggu dukungannya  untuk pariwisata Danau Toba dan Sumatera Utara.\n",
      "\n",
      "Selamat bekerja. Merdeka!!! #kabinetindonesiamaju #jokowi #prabowo #menteriindonesia #wishnutama #indonesiamaju #menpora #menhan 45\n",
      "#Repost @bpom_ri (@get_repost)\n",
      "・・・\n",
      "Selamat bekerja Kabinet Indonesia Maju. Semangat mengabdi untuk negeri. \n",
      "Mari rapatkan barisan untuk kerja bersama membangun tanah air tercinta.\n",
      "\n",
      "#Indonesia\n",
      "#KabinetIndonesiaMaju\n",
      "#KerjaBersama\n",
      "#MemimpinBangsa 46\n",
      "Etika jurnalis dalam menulis harus selalu berpedoman pada nilai2 Pancasila..... #SDMUnggul \n",
      "#IndonesiaMaju \n",
      "#74thIndonesia \n",
      "#KabinetIndonesiaMaju #jokowi #nawacita #PasukanRebahan #WINNER_SOSO #SAIK2019 #ShallWe2ndwin #bumn #media #viral #jurnalisme #indonesia 47\n",
      "#Repost @kemenperin_ri\n",
      "• • • • • •\n",
      "Segenap keluarga besar Kementerian Perindustrian mengucapkan terima kasih atas pengabdian dan kontribusi Menteri Perindustrian periode 2016 - 2019 Bapak @airlanggahartarto4.0 untuk kemajuan industri Tanah Air dan menghantarkan Indonesia memasuki era #industri4.0.\n",
      "\n",
      "Selamat mengemban tugas baru sebagai Menteri Koordinator Bidang Perekonomian RI #KabinetIndonesiaMaju.\n",
      "\n",
      "Sukses selalu dimanapun Bapak bertugas. 48\n",
      "Selamat & Sukses atas Dilantiknya Mentri Indonesia Maju.\n",
      "\n",
      "Mari Bersama Bersinergi Untuk KabinetMembangun Negeri.\n",
      "\n",
      "#KabinetIndonesiaMaju\n",
      "#JokowiAmin 49\n",
      "Selamat kepada Bapak, Ibu, Mas, Mbak yang telah terpilih dan menjadi bagian dari kabinet Jokowi-Ma'ruf\n",
      "Selamat bekerja keras demi membangun Indonesia menjadi negara maju\n",
      "Jaga integritas kalian \n",
      "Jaga semangatnya jangan sampai kendor di tengah jalan\n",
      "Karena ada rakyat yang telah membayar pajak dan menunggu perubahan negeri ini menuju lebih baik \n",
      "#lettering #letteringdesign #handlettering #handmadefont #kaligrafina #hurufraktur #jogjacreatype #jktyp #typography #tyxca #kanvastan #goodtype #strengthinletters #kabinetindonesiamaju 50\n",
      "Presiden Jokowi menunjuk mantan Kapolri Jenderal Tito Karnavian sebagai Menteri Dalam Negeri di Kabinet Indonesia Maju. Sosok pengganti Tito pun mulai mencuat, yaitu Kabareskrim Komjen Idham Azis.⁠\n",
      "-⁠\n",
      "Idham saat ini berusia 56 tahun, namun Januari 2020 Idham sudah berusia 57 tahun. Sesuai aturan, Idham hanya akan menjabat sebagai Kapolri selama satu tahun kecuali @jokowi memperpanjang masa jabatannya.⁠\n",
      "-⁠\n",
      "Simak selengkapnya dengan klik link di bio, ﻿atau download aplikasi kumparan di App Store dan Google Play.⁠\n",
      "-⁠\n",
      "#kumparanNEWS #kabinetindonesiamaju #pelantikanpresiden #jokowi #presidenterpilih #wapres #menteri #kabinetbarujokowi #pelantikanjokowiamin #jokowimaruf #presidenri #trendingtopic #info #videoviral #videooftheday #beritahariini #berita #beritaterkini #terbaru #indonesia #viral #news #like4like #instalike #repost #instadaily #instanews #instavideo #kumparan 51\n",
      "Repost @kemlu_ri \n",
      "Selamat dan sukses untuk Ibu Retno LP Marsudi sebagai Menteri Luar Negeri #KabinetIndonesiaMaju Periode 2019-2024\n",
      "\n",
      "#SahabatKemlu, ada harapan khusus untuk politik luar negeri Indonesia moving forward?\n",
      "\n",
      "#IniDiplomasi 52\n",
      "Menteri Badan Usaha Milik Negara [BUMN], Erick Thohir, B.A., M.B.A.\n",
      "\n",
      "Selamat bekerja untuk Indonesia.\n",
      "\n",
      "#KabinetIndonesiaMaju 53\n",
      "ㅤㅤㅤㅤㅤㅤ\n",
      "Halo Carya Budaya!\n",
      "\n",
      "Hari ini kita kenalan yuk dengan beberapa menteri yang baru di lantik hari ini. Mereka, akan memimpin kementerian-kementrian yang programnya sejalan dengan @agarya.id. Selamat menjalankan tugas bapak-bapak. Semoga amanah dalam menjalani program kerjanya. 😊\n",
      "\n",
      "ㅤㅤㅤㅤㅤㅤ\n",
      "Ikuti terus postingan kami di :\n",
      "• Line : @767csugi\n",
      "• Twitter : agaryaid_\n",
      "• Facebook : agaryaid\n",
      "• YouTube : agarya indonesia\n",
      "\n",
      "#agarya #agaryacreative #budaya #indonesia #culture#budayaindonesia #seni #tradisi #tradisional #sosial#pesonaindonesia #nusantara #budayasaya#warisanbudaya #art #traditionalmusic #kabinetindonesiamaju #kemendes2019 #kemensos #kemdikbud #sobatwisata #sobatdesa #kemenkopmk #kemenpar 54\n",
      "video by: @ekagustiwana .\n",
      "\n",
      "Dm/Tag ➡️ @wartabhineka \n",
      "#infowarta #beritaterkini #wartabhineka #viral #trending #trendingtopic #news #berita\n",
      "#pengumuman #menteri #jokowi #kabinetjokowi  #congratulations #kabinet #menterikabinet #jayalahnegeriku\n",
      "#kabinetindonesiamaju #kabinetindonesiamaju2019 55\n"
     ]
    }
   ],
   "source": [
    "# parsing a graphql instagram\n",
    "# CG - last updated 2 May 2018\n",
    "\n",
    "import json\n",
    "import requests\n",
    "\n",
    "tag = 'kabinetindonesiamaju'\n",
    "url = 'https://www.instagram.com/explore/tags/' + tag + '/?__a=1'\n",
    "'''\n",
    "keys = ['id', 'owner', 'taken_at_timestamp', 'text', 'count',\n",
    "        'video_view_count',\n",
    "        'edge_media_to_comment',\n",
    "        'edge_media_to_caption',\n",
    "        'edge_liked_by',\n",
    "        'edge_media_preview_like']\n",
    "'''\n",
    "\n",
    "keys = ['text']\n",
    "\n",
    "\n",
    "def jprint(data_dict):\n",
    "  print(json.dumps(data_dict, indent = 4))\n",
    "\n",
    "#Grab the data\n",
    "def get_ig_page(url, session=None):\n",
    "  print(url)\n",
    "  session = session or requests.Session()\n",
    "\n",
    "  r = session.get(url)\n",
    "  r_code = r.status_code\n",
    "  print(r_code)\n",
    "\n",
    "  if r_code == requests.codes.ok:\n",
    "    return r\n",
    "  else:\n",
    "    return None\n",
    "\n",
    "ig_data_dict = get_ig_page(url)\n",
    "\n",
    "\n",
    "if ig_data_dict is not None:\n",
    "  ig_data_dict = ig_data_dict.json()     #complete data crawled with graphql keyword\n",
    "#  jprint(ig_data_dict)\n",
    "\n",
    "\n",
    "  graphql = ig_data_dict.get('graphql', None) #removing graphql keyword\n",
    "#  jprint(graphql)\n",
    "\n",
    "  hashtag = graphql.get('hashtag', None) #removing hashtag keyword\n",
    "#  jprint(hashtag)\n",
    "\n",
    "  #get name\n",
    "  name = hashtag.get('name', None) \n",
    "  jprint(name)\n",
    " \n",
    "  #get is_top_media_only \n",
    "  is_top_media_only = hashtag.get('is_top_media_only', None)\n",
    "  jprint(is_top_media_only)\n",
    "\n",
    "  #get profile_pic_url\n",
    "  profile_pic_url = hashtag.get('profile_pic_url', None)\n",
    "  jprint(profile_pic_url)\n",
    "\n",
    "  #removing edge_hashtag_to_media keyword\n",
    "  edge_hashtag_to_media = hashtag.get('edge_hashtag_to_media', None)\n",
    "#  jprint(edge_hashtag_to_media)\n",
    "\n",
    "  #get count\n",
    "  count = edge_hashtag_to_media.get('count', None)\n",
    "  jprint(count)\n",
    "\n",
    "  #get page info\n",
    "  page_info = edge_hashtag_to_media.get('page_info', None)\n",
    "  jprint(page_info)\n",
    "\n",
    "  #remove edges keyword\n",
    "#  edges = edge_hashtag_to_media.dumps('edges', None)\n",
    "#  jprint(edges)\n",
    "\n",
    "  #get node\n",
    "  node = edge_hashtag_to_media.get('edges', None)\n",
    "#  jprint(node)\n",
    "\n",
    "  print (len(node))\n",
    "\n",
    "#  a = json.dumps(node)\n",
    "#  print(a)\n",
    "\n",
    "'''\n",
    "for team in json_dict['teams']:\n",
    "    print team['_links']['fixtures']['href']\n",
    "'''\n",
    "c = 0\n",
    "for post in edge_hashtag_to_media['edges']:\n",
    "    get_text = post['node']['edge_media_to_caption']['edges']\n",
    "#    print(post['node']['edge_media_to_caption']['edges'])\n",
    "#    print(get_text)\n",
    "    for post in get_text:\n",
    "        c = c + 1\n",
    "        print(post['node']['text'] , c)\n",
    "    \n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "https://www.instagram.com/explore/tags/kabinetindonesiamaju/?__a=1\n",
      "200\n",
      "\"kabinetindonesiamaju\"\n",
      "false\n",
      "\"https://instagram.fbdo4-1.fna.fbcdn.net/vp/1a885a1db0a883b68f112dc75cf9cee9/5E4AF121/t51.2885-15/e35/s150x150/72898284_152681689274980_3840659124078273825_n.jpg?_nc_ht=instagram.fbdo4-1.fna.fbcdn.net&_nc_cat=104\"\n",
      "7128\n",
      "{\n",
      "    \"has_next_page\": true,\n",
      "    \"end_cursor\": \"QVFBX2M4RmRWSkV0NXE4V2xFS2ZWczhyUGdsR1ZDZUpIR0NOT1BaaWZNS1NYSGxsVVZaOGhCakVyZ0F2TG5CQlUtR01VLW9JbUNJWXM0aUxOSjhUVVhBWQ==\"\n",
      "}\n",
      "51\n",
      "Penonton, mohon bersabar! Jangan iri!\n",
      "Hahaha\n",
      "\n",
      "https://www.google.com/amp/s/amp.suara.com/news/2019/10/14/161245/viral-video-tiktok-anggota-dpr-lora-fadil-dan-3-istrinya\n",
      "__________\n",
      "Follow 👉 @cakmid_bookstore\n",
      "Follow 👉 @cakmid_bookstore\n",
      "__________\n",
      "#entahapayangmerasukimu #menteri #kabinetindonesiamaju #dprri #lorafadil #jember #tiktok #legislatif #poligami #istri\n",
      "__________\n",
      "#aktivismahasiswa #hidupmahasiswa #maba #kampus #hmi #mahasiswa #mahasiswi #aktivis #indonesiamaju #islam #indonesia\n",
      "__________\n",
      "#cakmidbookstore #tokobuku #bukumurah #ayobaca #baca #buku #bacabuku #membacaituasyik\n"
     ]
    },
    {
     "ename": "UnicodeEncodeError",
     "evalue": "'charmap' codec can't encode character '\\U0001f449' in position 192: character maps to <undefined>",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mUnicodeEncodeError\u001b[0m                        Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-3-42f7ed77c18f>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m    103\u001b[0m     \u001b[1;32mfor\u001b[0m \u001b[0mpost\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mget_text\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    104\u001b[0m         \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mpost\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'node'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'text'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 105\u001b[1;33m         \u001b[0mdata\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mwrite\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mpost\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'node'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'text'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    106\u001b[0m         \u001b[0mcount\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mcount\u001b[0m \u001b[1;33m+\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    107\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mC:\\Anaconda\\lib\\encodings\\cp1252.py\u001b[0m in \u001b[0;36mencode\u001b[1;34m(self, input, final)\u001b[0m\n\u001b[0;32m     17\u001b[0m \u001b[1;32mclass\u001b[0m \u001b[0mIncrementalEncoder\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mcodecs\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mIncrementalEncoder\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     18\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0mencode\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0minput\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mfinal\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mFalse\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 19\u001b[1;33m         \u001b[1;32mreturn\u001b[0m \u001b[0mcodecs\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcharmap_encode\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0minput\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0merrors\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mencoding_table\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     20\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     21\u001b[0m \u001b[1;32mclass\u001b[0m \u001b[0mIncrementalDecoder\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mcodecs\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mIncrementalDecoder\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mUnicodeEncodeError\u001b[0m: 'charmap' codec can't encode character '\\U0001f449' in position 192: character maps to <undefined>"
     ]
    }
   ],
   "source": [
    "# parsing a graphql instagram\n",
    "\n",
    "import json\n",
    "import requests\n",
    "\n",
    "tag = 'kabinetindonesiamaju'\n",
    "url = 'https://www.instagram.com/explore/tags/' + tag + '/?__a=1'\n",
    "'''\n",
    "keys = ['id', 'owner', 'taken_at_timestamp', 'text', 'count',\n",
    "        'video_view_count',\n",
    "        'edge_media_to_comment',\n",
    "        'edge_media_to_caption',\n",
    "        'edge_liked_by',\n",
    "        'edge_media_preview_like']\n",
    "'''\n",
    "\n",
    "keys = ['text']\n",
    "\n",
    "\n",
    "def jprint(data_dict):\n",
    "  print(json.dumps(data_dict, indent = 4))\n",
    "\n",
    "#Grab the data\n",
    "def get_ig_page(url, session=None):\n",
    "  print(url)\n",
    "  session = session or requests.Session()\n",
    "\n",
    "  r = session.get(url)\n",
    "  r_code = r.status_code\n",
    "  print(r_code)\n",
    "\n",
    "  if r_code == requests.codes.ok:\n",
    "    return r\n",
    "  else:\n",
    "    return None\n",
    "\n",
    "ig_data_dict = get_ig_page(url)\n",
    "\n",
    "\n",
    "if ig_data_dict is not None:\n",
    "  ig_data_dict = ig_data_dict.json()     #complete data crawled with graphql keyword\n",
    "#  jprint(ig_data_dict)\n",
    "\n",
    "\n",
    "  graphql = ig_data_dict.get('graphql', None) #removing graphql keyword\n",
    "#  jprint(graphql)\n",
    "\n",
    "  hashtag = graphql.get('hashtag', None) #removing hashtag keyword\n",
    "#  jprint(hashtag)\n",
    "\n",
    "  #get name\n",
    "  name = hashtag.get('name', None) \n",
    "  jprint(name)\n",
    " \n",
    "  #get is_top_media_only \n",
    "  is_top_media_only = hashtag.get('is_top_media_only', None)\n",
    "  jprint(is_top_media_only)\n",
    "\n",
    "  #get profile_pic_url\n",
    "  profile_pic_url = hashtag.get('profile_pic_url', None)\n",
    "  jprint(profile_pic_url)\n",
    "\n",
    "  #removing edge_hashtag_to_media keyword\n",
    "  edge_hashtag_to_media = hashtag.get('edge_hashtag_to_media', None)\n",
    "#  jprint(edge_hashtag_to_media)\n",
    "\n",
    "  #get count\n",
    "  count = edge_hashtag_to_media.get('count', None)\n",
    "  jprint(count)\n",
    "\n",
    "  #get page info\n",
    "  page_info = edge_hashtag_to_media.get('page_info', None)\n",
    "  jprint(page_info)\n",
    "\n",
    "  #remove edges keyword\n",
    "#  edges = edge_hashtag_to_media.dumps('edges', None)\n",
    "#  jprint(edges)\n",
    "\n",
    "  #get node\n",
    "  node = edge_hashtag_to_media.get('edges', None)\n",
    "#  jprint(node)\n",
    "\n",
    "  print (len(node))\n",
    "\n",
    "#  a = json.dumps(node)\n",
    "#  print(a)\n",
    "\n",
    "'''\n",
    "for team in json_dict['teams']:\n",
    "    print team['_links']['fixtures']['href']\n",
    "'''\n",
    "data_file = \"data_file.txt\"\n",
    "data = open(data_file, \"w\")\n",
    "\n",
    "\n",
    "count = 0\n",
    "\n",
    "for post in edge_hashtag_to_media['edges']:\n",
    "    get_text = post['node']['edge_media_to_caption']['edges']\n",
    "#    print(post['node']['edge_media_to_caption']['edges'])\n",
    "#    print(get_text)\n",
    "   \n",
    "    for post in get_text:\n",
    "        print(post['node']['text'])\n",
    "        data.write(post['node']['text'])\n",
    "        count = count +1\n",
    "        \n",
    "print(\"Total nodes: \" + str(count))\n",
    "        \n",
    "        \n",
    "\n",
    "    \n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INI URL - https://www.instagram.com/explore/tags/kabinetindonesiamaju/?__a=1\n",
      "INI R_CODE - 200\n",
      "-------- <Response [200]>\n",
      "DISINI - \"kabinetindonesiamaju\"\n",
      "DISINI - false\n",
      "DISINI - \"https://instagram.fbdo4-1.fna.fbcdn.net/vp/1a885a1db0a883b68f112dc75cf9cee9/5E4AF121/t51.2885-15/e35/s150x150/72898284_152681689274980_3840659124078273825_n.jpg?_nc_ht=instagram.fbdo4-1.fna.fbcdn.net&_nc_cat=104\"\n",
      "DISINI - 7130\n",
      "DISINI - {\n",
      "    \"has_next_page\": true,\n",
      "    \"end_cursor\": \"QVFENzlkQmxaSVUydVJQN0JUdTloSDM2clBYVmpRdWVoazdTVkY0OXhfY3p1TXNCWGxKVFBsd2syOWt0eldJeEJfV3FKNC1uMFlpQnl2YVdKRFdkWjBETQ==\"\n",
      "}\n",
      "51\n",
      "jumlah node: 51\n",
      "[('presiden', 34), ('menteri', 30), ('jokowi', 29), ('indonesia', 24), ('kabinet', 22), ('maju', 16), ('dalam', 16), ('negara', 15), ('rapat', 14), ('ada', 11), ('adalah', 11), ('kerja', 10), ('bisa', 9), ('wakil', 9), ('com', 9), ('lebih', 9), ('baru', 9), ('follow', 8), ('serikatnews', 8), ('hari', 8)]\n"
     ]
    }
   ],
   "source": [
    "# parsing a graphql instagram\n",
    "# CG - last updated 2 May 2018\n",
    "\n",
    "import json\n",
    "import requests\n",
    "import re\n",
    "from collections import Counter\n",
    "\n",
    "tag = 'kabinetindonesiamaju'\n",
    "url = 'https://www.instagram.com/explore/tags/' + tag + '/?__a=1'\n",
    "'''\n",
    "keys = ['id', 'owner', 'taken_at_timestamp', 'text', 'count',\n",
    "        'video_view_count',\n",
    "        'edge_media_to_comment',\n",
    "        'edge_media_to_caption',\n",
    "        'edge_liked_by',\n",
    "        'edge_media_preview_like']\n",
    "'''\n",
    "\n",
    "stop_words = ['is', 'that', 'and', 'this', 'or', 'these', 'those', 'https', 'graphql', 'hashtag', 'instagram', 'fna',\n",
    "             'fbcdn', 'net', 'jpg', 'src', 'the', 'yang', 'dan', 'untuk', 'dengan', 'pada', 'ini', 'akan', 'dari', \n",
    "              'kami', 'kalian', 'kita']\n",
    "\n",
    "keys = ['text']\n",
    "\n",
    "\n",
    "def jprint(data_dict):\n",
    "  print('DISINI - '+json.dumps(data_dict, indent = 4))\n",
    "\n",
    "#Grab the data\n",
    "def get_ig_page(url, session=None):\n",
    "  print('INI URL - '+url)\n",
    "  session = session or requests.Session()\n",
    "\n",
    "  r = session.get(url)\n",
    "  r_code = r.status_code\n",
    "  print('INI R_CODE - '+str(r_code))\n",
    "\n",
    "  if r_code == requests.codes.ok:\n",
    "    return r\n",
    "  else:\n",
    "    return None\n",
    "\n",
    "ig_data_dict = get_ig_page(url)\n",
    "print('-------- '+str(ig_data_dict))\n",
    "\n",
    "if ig_data_dict is not None:\n",
    "  ig_data_dict = ig_data_dict.json()     #complete data crawled with graphql keyword\n",
    "#  jprint(ig_data_dict)\n",
    "\n",
    "\n",
    "  graphql = ig_data_dict.get('graphql', None) #removing graphql keyword\n",
    "#  jprint(graphql)\n",
    "\n",
    "  hashtag = graphql.get('hashtag', None) #removing hashtag keyword\n",
    "#  jprint(hashtag)\n",
    "\n",
    "  #get name\n",
    "  name = hashtag.get('name', None) \n",
    "  jprint(name)\n",
    " \n",
    "  #get is_top_media_only \n",
    "  is_top_media_only = hashtag.get('is_top_media_only', None)\n",
    "  jprint(is_top_media_only)\n",
    "\n",
    "  #get profile_pic_url\n",
    "  profile_pic_url = hashtag.get('profile_pic_url', None)\n",
    "  jprint(profile_pic_url)\n",
    "\n",
    "  #removing edge_hashtag_to_media keyword\n",
    "  edge_hashtag_to_media = hashtag.get('edge_hashtag_to_media', None)\n",
    "#  jprint(edge_hashtag_to_media)\n",
    "\n",
    "  #get count\n",
    "  count = edge_hashtag_to_media.get('count', None)\n",
    "  jprint(count)\n",
    "\n",
    "  #get page info\n",
    "  page_info = edge_hashtag_to_media.get('page_info', None)\n",
    "  jprint(page_info)\n",
    "\n",
    "  #remove edges keyword\n",
    "#  edges = edge_hashtag_to_media.dumps('edges', None)\n",
    "#  jprint(edges)\n",
    "\n",
    "  #get node\n",
    "  node = edge_hashtag_to_media.get('edges', None)\n",
    "#  jprint(node)\n",
    "\n",
    "  print (len(node))\n",
    "\n",
    "#  a = json.dumps(node)\n",
    "#  print(a)\n",
    "\n",
    "'''\n",
    "for team in json_dict['teams']:\n",
    "    print team['_links']['fixtures']['href']\n",
    "'''\n",
    "\n",
    "counter = 0\n",
    "text = ''\n",
    "for post in edge_hashtag_to_media['edges']:\n",
    "    get_text = post['node']['edge_media_to_caption']['edges']\n",
    "#    print(post['node']['edge_media_to_caption']['edges'])\n",
    "#    print(get_text)\n",
    "    for post in get_text:\n",
    "        #print(post['node']['text'])\n",
    "        text += post['node']['text']\n",
    "        counter += 1\n",
    "\n",
    "text_string = text.lower() #convert input text to lower case\n",
    "match_pattern = re.findall(r'\\b[a-z]{3,15}\\b', text_string) #regex for removing symbols\n",
    "\n",
    "popularKeyword = []\n",
    "for word in match_pattern:\n",
    "    if word not in stop_words:\n",
    "        popularKeyword.append(word)\n",
    "        #count = frequency.get(word, 0)\n",
    "        #frequency[word] = count + 1\n",
    "    \n",
    "print('jumlah node: ' + str(counter))\n",
    "print(Counter(popularKeyword).most_common(20))\n",
    "#print(frequency)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['2160847888354179795', '2160972783109889884', '2160833606438847683', '2160877507976348521', '2160842773249519843', '2160931292667997885']\n",
      "[572, 504, 285, 265, 258, 153]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# parsing a graphql instagram\n",
    "# CG - last updated 2 May 2018\n",
    "\n",
    "import json\n",
    "import requests\n",
    "import re\n",
    "from collections import Counter\n",
    "\n",
    "tag = 'telkomuniversity'\n",
    "url = 'https://www.instagram.com/explore/tags/' + tag + '/?__a=1'\n",
    "'''\n",
    "keys = ['id', 'owner', 'taken_at_timestamp', 'text', 'count',\n",
    "        'video_view_count',\n",
    "        'edge_media_to_comment',\n",
    "        'edge_media_to_caption',\n",
    "        'edge_liked_by',\n",
    "        'edge_media_preview_like']\n",
    "'''\n",
    "\n",
    "stop_words = ['is', 'that', 'and', 'this', 'or', 'these', 'those', 'https', 'graphql', 'hashtag', 'instagram', 'fna',\n",
    "             'fbcdn', 'net', 'jpg', 'src', 'the', 'yang', 'dan', 'untuk', 'dengan', 'pada', 'ini', 'akan', 'dari', \n",
    "              'kami', 'kalian', 'kita']\n",
    "\n",
    "keys = ['text']\n",
    "\n",
    "\n",
    "def jprint(data_dict):\n",
    "  print('DISINI - '+json.dumps(data_dict, indent = 4))\n",
    "\n",
    "#Grab the data\n",
    "def get_ig_page(url, session=None):\n",
    "#  print('INI URL - '+url)\n",
    "  session = session or requests.Session()\n",
    "\n",
    "  r = session.get(url)\n",
    "  r_code = r.status_code\n",
    "#  print('INI R_CODE - '+str(r_code))\n",
    "\n",
    "  if r_code == requests.codes.ok:\n",
    "    return r\n",
    "  else:\n",
    "    return None\n",
    "\n",
    "ig_data_dict = get_ig_page(url)\n",
    "# print('-------- '+str(ig_data_dict))\n",
    "\n",
    "if ig_data_dict is not None:\n",
    "  ig_data_dict = ig_data_dict.json()     #complete data crawled with graphql keyword\n",
    "#  jprint(ig_data_dict)\n",
    "\n",
    "\n",
    "  graphql = ig_data_dict.get('graphql', None) #removing graphql keyword\n",
    "#  jprint(graphql)\n",
    "\n",
    "  hashtag = graphql.get('hashtag', None) #removing hashtag keyword\n",
    "#  jprint(hashtag)\n",
    "\n",
    "  #get name\n",
    "  name = hashtag.get('name', None) \n",
    "#  jprint(name)\n",
    " \n",
    "  #get is_top_media_only \n",
    "  is_top_media_only = hashtag.get('is_top_media_only', None)\n",
    "#  jprint(is_top_media_only)\n",
    "\n",
    "  #get profile_pic_url\n",
    "  profile_pic_url = hashtag.get('profile_pic_url', None)\n",
    "#  jprint(profile_pic_url)\n",
    "\n",
    "  #removing edge_hashtag_to_media keyword\n",
    "  edge_hashtag_to_media = hashtag.get('edge_hashtag_to_media', None)\n",
    "#  jprint(edge_hashtag_to_media)\n",
    "\n",
    "  #get count\n",
    "  count = edge_hashtag_to_media.get('count', None)\n",
    "#  jprint(count)\n",
    "\n",
    "  #get page info\n",
    "  page_info = edge_hashtag_to_media.get('page_info', None)\n",
    "#  jprint(page_info)\n",
    "\n",
    "  #remove edges keyword\n",
    "#  edges = edge_hashtag_to_media.dumps('edges', None)\n",
    "#  jprint(edges)\n",
    "\n",
    "  #get node\n",
    "  node = edge_hashtag_to_media.get('edges', None)\n",
    "#  jprint(node)\n",
    "\n",
    "#  print (len(node))\n",
    "\n",
    "#  a = json.dumps(node)\n",
    "#  print(a)\n",
    "\n",
    "'''\n",
    "for team in json_dict['teams']:\n",
    "    print team['_links']['fixtures']['href']\n",
    "'''\n",
    "\n",
    "counter = 0\n",
    "text = 0\n",
    "list = []\n",
    "dict = {}\n",
    "\n",
    "for post in edge_hashtag_to_media['edges']:\n",
    "    get_id = post['node']['id']\n",
    "    get_like = post['node']['edge_liked_by']['count']\n",
    "#    print(get_id , get_like)\n",
    "    \n",
    "    dict[get_id] = get_like\n",
    "\n",
    "urut =sorted(dict.items(), key = lambda x : x[1],reverse=True)\n",
    "#print(urut)\n",
    "\n",
    "listurut = []\n",
    "listkey = []\n",
    "listvalue = []\n",
    "\n",
    "for i in range(6):\n",
    "#    print((urut[i]))\n",
    "#    print(type(urut[i]))\n",
    "#    print ((urut[i])[0])\n",
    "    listkey.append((urut[i])[0])\n",
    "#    listurut.append(urut[i])\n",
    "#    print ((urut[i])[1])\n",
    "    listvalue.append((urut[i])[1])\n",
    "print(listkey)\n",
    "print(listvalue)\n",
    "\n",
    "\n",
    "import matplotlib.pyplot as plt; plt.rcdefaults()\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "y_pos = np.arange(len(listkey))\n",
    "performance = listvalue\n",
    "\n",
    "plt.bar(y_pos, performance, align='center', alpha=0.5)\n",
    "plt.xticks(y_pos, listkey)\n",
    "plt.ylabel('jumlah like')\n",
    "plt.title('matilampu')\n",
    "\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['2161800899830655146', '2161799915261887478', '2161822276010803844', '2161783540513894877', '2161813911729186411', '2161803384605093184']\n",
      "[2259, 1460, 660, 411, 341, 71]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# parsing a graphql instagram\n",
    "\n",
    "\n",
    "import json\n",
    "import requests\n",
    "import re\n",
    "from collections import Counter\n",
    "\n",
    "tag = 'kabinetindonesiamaju'\n",
    "url = 'https://www.instagram.com/explore/tags/' + tag + '/?__a=1'\n",
    "'''\n",
    "keys = ['id', 'owner', 'taken_at_timestamp', 'text', 'count',\n",
    "        'video_view_count',\n",
    "        'edge_media_to_comment',\n",
    "        'edge_media_to_caption',\n",
    "        'edge_liked_by',\n",
    "        'edge_media_preview_like']\n",
    "'''\n",
    "\n",
    "stop_words = ['is', 'that', 'and', 'this', 'or', 'these', 'those', 'https', 'graphql', 'hashtag', 'instagram', 'fna',\n",
    "             'fbcdn', 'net', 'jpg', 'src', 'the', 'yang', 'dan', 'untuk', 'dengan', 'pada', 'ini', 'akan', 'dari', \n",
    "              'kami', 'kalian', 'kita']\n",
    "\n",
    "keys = ['text']\n",
    "\n",
    "\n",
    "def jprint(data_dict):\n",
    "  print('DISINI - '+json.dumps(data_dict, indent = 4))\n",
    "\n",
    "#Grab the data\n",
    "def get_ig_page(url, session=None):\n",
    "#  print('INI URL - '+url)\n",
    "  session = session or requests.Session()\n",
    "\n",
    "  r = session.get(url)\n",
    "  r_code = r.status_code\n",
    "#  print('INI R_CODE - '+str(r_code))\n",
    "\n",
    "  if r_code == requests.codes.ok:\n",
    "    return r\n",
    "  else:\n",
    "    return None\n",
    "\n",
    "ig_data_dict = get_ig_page(url)\n",
    "# print('-------- '+str(ig_data_dict))\n",
    "\n",
    "if ig_data_dict is not None:\n",
    "  ig_data_dict = ig_data_dict.json()     #complete data crawled with graphql keyword\n",
    "#  jprint(ig_data_dict)\n",
    "\n",
    "\n",
    "  graphql = ig_data_dict.get('graphql', None) #removing graphql keyword\n",
    "#  jprint(graphql)\n",
    "\n",
    "  hashtag = graphql.get('hashtag', None) #removing hashtag keyword\n",
    "#  jprint(hashtag)\n",
    "\n",
    "  #get name\n",
    "  name = hashtag.get('name', None) \n",
    "#  jprint(name)\n",
    " \n",
    "  #get is_top_media_only \n",
    "  is_top_media_only = hashtag.get('is_top_media_only', None)\n",
    "#  jprint(is_top_media_only)\n",
    "\n",
    "  #get profile_pic_url\n",
    "  profile_pic_url = hashtag.get('profile_pic_url', None)\n",
    "#  jprint(profile_pic_url)\n",
    "\n",
    "  #removing edge_hashtag_to_media keyword\n",
    "  edge_hashtag_to_media = hashtag.get('edge_hashtag_to_media', None)\n",
    "#  jprint(edge_hashtag_to_media)\n",
    "\n",
    "  #get count\n",
    "  count = edge_hashtag_to_media.get('count', None)\n",
    "#  jprint(count)\n",
    "\n",
    "  #get page info\n",
    "  page_info = edge_hashtag_to_media.get('page_info', None)\n",
    "#  jprint(page_info)\n",
    "\n",
    "  #remove edges keyword\n",
    "#  edges = edge_hashtag_to_media.dumps('edges', None)\n",
    "#  jprint(edges)\n",
    "\n",
    "  #get node\n",
    "  node = edge_hashtag_to_media.get('edges', None)\n",
    "#  jprint(node)\n",
    "\n",
    "#  print (len(node))\n",
    "\n",
    "#  a = json.dumps(node)\n",
    "#  print(a)\n",
    "\n",
    "'''\n",
    "for team in json_dict['teams']:\n",
    "    print team['_links']['fixtures']['href']\n",
    "'''\n",
    "\n",
    "counter = 0\n",
    "text = 0\n",
    "list = []\n",
    "dict = {}\n",
    "\n",
    "for post in edge_hashtag_to_media['edges']:\n",
    "    get_id = post['node']['id']\n",
    "    get_like = post['node']['edge_liked_by']['count']\n",
    "#    print(get_id , get_like)\n",
    "    \n",
    "    dict[get_id] = get_like\n",
    "\n",
    "urut =sorted(dict.items(), key = lambda x : x[1],reverse=True)\n",
    "#print(urut)\n",
    "\n",
    "listurut = []\n",
    "listkey = []\n",
    "listvalue = []\n",
    "\n",
    "for i in range(6):\n",
    "#    print((urut[i]))\n",
    "#    print(type(urut[i]))\n",
    "#    print ((urut[i])[0])\n",
    "    listkey.append((urut[i])[0])\n",
    "#    listurut.append(urut[i])\n",
    "#    print ((urut[i])[1])\n",
    "    listvalue.append((urut[i])[1])\n",
    "print(listkey)\n",
    "print(listvalue)\n",
    "\n",
    "\n",
    "import matplotlib.pyplot as plt; plt.rcdefaults()\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "y_pos = np.arange(len(listkey))\n",
    "performance = listvalue\n",
    "\n",
    "\n",
    "plt.bar(y_pos, performance, align='center', alpha=0.5)\n",
    "plt.xticks(y_pos, listkey)\n",
    "plt.xlabel('Status')\n",
    "plt.ylabel('jumlah like')\n",
    "plt.title('kabinet')\n",
    "\n",
    "plt.show()\n",
    "\n",
    "# Plotpie\n",
    "explode = (0.1, 0.1, 0.1, 0.5, 0, 0)  # explode 1st slice\n",
    "plt.pie(listvalue,labels=listkey,explode=explode,\n",
    "autopct='%.1f', shadow=True, startangle=140)\n",
    "\n",
    "plt.axis('equal')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "from selenium import webdriver\n",
    "from bs4 import BeautifulSoup as bs\n",
    "import time\n",
    "import re\n",
    "from urllib.request import urlopen\n",
    "import json\n",
    "from pandas.io.json import json_normalize\n",
    "import pandas as pd, numpy as np"
   ]
  },
  {
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