Lese data fra SSB - ekstra eksempel.ipynb

{
  "cells": [
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "https://www.ssb.no/befolkning/statistikker/flytting\n\nhttps://www.ssb.no/eksport/tabell.csv?key=343890",
      "execution_count": null,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "data = !curl https://www.ssb.no/eksport/tabell.csv?key=343890",
      "execution_count": 1,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "print(data)",
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "text": "['  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current', '                                 Dload  Upload   Total   Spent    Left  Speed', '', '  0     0    0     0    0     0      0      0 --:--:-- --:--:-- --:--:--     0', '  0     0    0     0    0     0      0      0 --:--:-- --:--:-- --:--:--     0', '100  1470    0  1470    0     0   1870      0 --:--:-- --:--:-- --:--:--  1872', '\\ufeff;2017;2017;2017;2017;2017;2017;2017;2017;2017;', 'Innflyttinger;Innflyttinger;Innflyttinger;Utflyttinger;Utflyttinger;Utflyttinger;Nettoinnflytting;Nettoinnflytting;Nettoinnflytting;', 'Alle flyttinger;Fra utlandet;Innenlandske;Alle flyttinger;Til utlandet;Innenlandske;Alle flyttinger;Fra utlandet;Innenlandske;', 'Hele landet;208882;58192;150690;187533;36843;150690;21349;21349;0;', 'Østfold;10508;2075;8433;8232;1467;6765;2276;608;1668;', 'Akershus;33739;5993;27746;26287;4485;21802;7452;1508;5944;', 'Oslo;43866;12983;30883;42762;9503;33259;1104;3480;-2376;', 'Hedmark;7023;1485;5538;5853;811;5042;1170;674;496;', 'Oppland;6822;1448;5374;6078;656;5422;744;792;-48;', 'Buskerud;11787;2898;8889;10144;1954;8190;1643;944;699;', 'Vestfold;9581;2318;7263;7727;1516;6211;1854;802;1052;', 'Telemark;5394;1581;3813;5099;751;4348;295;830;-535;', 'Aust-Agder;4071;882;3189;3674;563;3111;397;319;78;', 'Vest-Agder;7504;1928;5576;5685;987;4698;1819;941;878;', 'Rogaland;10741;4796;5945;12163;4020;8143;-1422;776;-2198;', 'Hordaland;13742;4982;8760;13444;3608;9836;298;1374;-1076;', 'Sogn og Fjordane;3428;1337;2091;3599;595;3004;-171;742;-913;', 'Møre og Romsdal;6737;2532;4205;6625;1341;5284;112;1191;-1079;', 'Sør-Trøndelag (-2017);12666;3700;8966;10281;1923;8358;2385;1777;608;', 'Nord-Trøndelag (-2017);4627;1382;3245;4160;412;3748;467;970;-503;', 'Nordland;7336;2720;4616;6896;919;5977;440;1801;-1361;', 'Troms - Romsa;6339;2125;4214;5811;875;4936;528;1250;-722;', 'Finnmark - Finnmárku;2971;1027;1944;3013;457;2556;-42;570;-612;']\n",
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "for line in data:\n    print(line)",
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "text": "  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current\n                                 Dload  Upload   Total   Spent    Left  Speed\n\n  0     0    0     0    0     0      0      0 --:--:-- --:--:-- --:--:--     0\n  0     0    0     0    0     0      0      0 --:--:-- --:--:-- --:--:--     0\n100  1470    0  1470    0     0   1870      0 --:--:-- --:--:-- --:--:--  1872\n﻿;2017;2017;2017;2017;2017;2017;2017;2017;2017;\nInnflyttinger;Innflyttinger;Innflyttinger;Utflyttinger;Utflyttinger;Utflyttinger;Nettoinnflytting;Nettoinnflytting;Nettoinnflytting;\nAlle flyttinger;Fra utlandet;Innenlandske;Alle flyttinger;Til utlandet;Innenlandske;Alle flyttinger;Fra utlandet;Innenlandske;\nHele landet;208882;58192;150690;187533;36843;150690;21349;21349;0;\nØstfold;10508;2075;8433;8232;1467;6765;2276;608;1668;\nAkershus;33739;5993;27746;26287;4485;21802;7452;1508;5944;\nOslo;43866;12983;30883;42762;9503;33259;1104;3480;-2376;\nHedmark;7023;1485;5538;5853;811;5042;1170;674;496;\nOppland;6822;1448;5374;6078;656;5422;744;792;-48;\nBuskerud;11787;2898;8889;10144;1954;8190;1643;944;699;\nVestfold;9581;2318;7263;7727;1516;6211;1854;802;1052;\nTelemark;5394;1581;3813;5099;751;4348;295;830;-535;\nAust-Agder;4071;882;3189;3674;563;3111;397;319;78;\nVest-Agder;7504;1928;5576;5685;987;4698;1819;941;878;\nRogaland;10741;4796;5945;12163;4020;8143;-1422;776;-2198;\nHordaland;13742;4982;8760;13444;3608;9836;298;1374;-1076;\nSogn og Fjordane;3428;1337;2091;3599;595;3004;-171;742;-913;\nMøre og Romsdal;6737;2532;4205;6625;1341;5284;112;1191;-1079;\nSør-Trøndelag (-2017);12666;3700;8966;10281;1923;8358;2385;1777;608;\nNord-Trøndelag (-2017);4627;1382;3245;4160;412;3748;467;970;-503;\nNordland;7336;2720;4616;6896;919;5977;440;1801;-1361;\nTroms - Romsa;6339;2125;4214;5811;875;4936;528;1250;-722;\nFinnmark - Finnmárku;2971;1027;1944;3013;457;2556;-42;570;-612;\n",
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "linje = data[12]\nprint(linje)\nprint(linje.split(\";\"))\nprint(linje.rstrip(\";\"))\nprint(linje.rstrip(\";\").split(\";\"))",
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "text": "Oslo;43866;12983;30883;42762;9503;33259;1104;3480;-2376;\n['Oslo', '43866', '12983', '30883', '42762', '9503', '33259', '1104', '3480', '-2376', '']\nOslo;43866;12983;30883;42762;9503;33259;1104;3480;-2376\n['Oslo', '43866', '12983', '30883', '42762', '9503', '33259', '1104', '3480', '-2376']\n",
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "geografiskenhet = []\ninnflyttingtotalt = []\ninnflyttingfrautland = []\ninnflyttinginnenlandsk = []\nutflyttingtotalt = []\nutflyttingtilutland = []\nutflyttinginnenlandsk = []\nnettoinnflyttingtotalt = []\nnettoinnflyttingfrautland = []\nnettoinnflyttinginnenlandsk = []",
      "execution_count": 5,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "for line in data[11:]:\n    print(line)",
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "text": "Akershus;33739;5993;27746;26287;4485;21802;7452;1508;5944;\nOslo;43866;12983;30883;42762;9503;33259;1104;3480;-2376;\nHedmark;7023;1485;5538;5853;811;5042;1170;674;496;\nOppland;6822;1448;5374;6078;656;5422;744;792;-48;\nBuskerud;11787;2898;8889;10144;1954;8190;1643;944;699;\nVestfold;9581;2318;7263;7727;1516;6211;1854;802;1052;\nTelemark;5394;1581;3813;5099;751;4348;295;830;-535;\nAust-Agder;4071;882;3189;3674;563;3111;397;319;78;\nVest-Agder;7504;1928;5576;5685;987;4698;1819;941;878;\nRogaland;10741;4796;5945;12163;4020;8143;-1422;776;-2198;\nHordaland;13742;4982;8760;13444;3608;9836;298;1374;-1076;\nSogn og Fjordane;3428;1337;2091;3599;595;3004;-171;742;-913;\nMøre og Romsdal;6737;2532;4205;6625;1341;5284;112;1191;-1079;\nSør-Trøndelag (-2017);12666;3700;8966;10281;1923;8358;2385;1777;608;\nNord-Trøndelag (-2017);4627;1382;3245;4160;412;3748;467;970;-503;\nNordland;7336;2720;4616;6896;919;5977;440;1801;-1361;\nTroms - Romsa;6339;2125;4214;5811;875;4936;528;1250;-722;\nFinnmark - Finnmárku;2971;1027;1944;3013;457;2556;-42;570;-612;\n",
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "for line in data[11:]:\n    print(line)\n    line = line.rstrip(\";\").split(\";\")\n    print(line)\n    geografiskenhet.append(line[0])\n    innflyttingtotalt.append(int(line[1]))\n    innflyttingfrautland.append(int(line[2]))\n    innflyttinginnenlandsk.append(int(line[3]))\n    utflyttingtotalt.append(int(line[4]))\n    utflyttingtilutland.append(int(line[5]))\n    utflyttinginnenlandsk.append(int(line[6]))\n    nettoinnflyttingtotalt.append(int(line[7]))\n    nettoinnflyttingfrautland.append(int(line[8]))\n    nettoinnflyttinginnenlandsk.append(int(line[9]))",
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "stream",
          "text": "Akershus;33739;5993;27746;26287;4485;21802;7452;1508;5944;\n['Akershus', '33739', '5993', '27746', '26287', '4485', '21802', '7452', '1508', '5944']\nOslo;43866;12983;30883;42762;9503;33259;1104;3480;-2376;\n['Oslo', '43866', '12983', '30883', '42762', '9503', '33259', '1104', '3480', '-2376']\nHedmark;7023;1485;5538;5853;811;5042;1170;674;496;\n['Hedmark', '7023', '1485', '5538', '5853', '811', '5042', '1170', '674', '496']\nOppland;6822;1448;5374;6078;656;5422;744;792;-48;\n['Oppland', '6822', '1448', '5374', '6078', '656', '5422', '744', '792', '-48']\nBuskerud;11787;2898;8889;10144;1954;8190;1643;944;699;\n['Buskerud', '11787', '2898', '8889', '10144', '1954', '8190', '1643', '944', '699']\nVestfold;9581;2318;7263;7727;1516;6211;1854;802;1052;\n['Vestfold', '9581', '2318', '7263', '7727', '1516', '6211', '1854', '802', '1052']\nTelemark;5394;1581;3813;5099;751;4348;295;830;-535;\n['Telemark', '5394', '1581', '3813', '5099', '751', '4348', '295', '830', '-535']\nAust-Agder;4071;882;3189;3674;563;3111;397;319;78;\n['Aust-Agder', '4071', '882', '3189', '3674', '563', '3111', '397', '319', '78']\nVest-Agder;7504;1928;5576;5685;987;4698;1819;941;878;\n['Vest-Agder', '7504', '1928', '5576', '5685', '987', '4698', '1819', '941', '878']\nRogaland;10741;4796;5945;12163;4020;8143;-1422;776;-2198;\n['Rogaland', '10741', '4796', '5945', '12163', '4020', '8143', '-1422', '776', '-2198']\nHordaland;13742;4982;8760;13444;3608;9836;298;1374;-1076;\n['Hordaland', '13742', '4982', '8760', '13444', '3608', '9836', '298', '1374', '-1076']\nSogn og Fjordane;3428;1337;2091;3599;595;3004;-171;742;-913;\n['Sogn og Fjordane', '3428', '1337', '2091', '3599', '595', '3004', '-171', '742', '-913']\nMøre og Romsdal;6737;2532;4205;6625;1341;5284;112;1191;-1079;\n['Møre og Romsdal', '6737', '2532', '4205', '6625', '1341', '5284', '112', '1191', '-1079']\nSør-Trøndelag (-2017);12666;3700;8966;10281;1923;8358;2385;1777;608;\n['Sør-Trøndelag (-2017)', '12666', '3700', '8966', '10281', '1923', '8358', '2385', '1777', '608']\nNord-Trøndelag (-2017);4627;1382;3245;4160;412;3748;467;970;-503;\n['Nord-Trøndelag (-2017)', '4627', '1382', '3245', '4160', '412', '3748', '467', '970', '-503']\nNordland;7336;2720;4616;6896;919;5977;440;1801;-1361;\n['Nordland', '7336', '2720', '4616', '6896', '919', '5977', '440', '1801', '-1361']\nTroms - Romsa;6339;2125;4214;5811;875;4936;528;1250;-722;\n['Troms - Romsa', '6339', '2125', '4214', '5811', '875', '4936', '528', '1250', '-722']\nFinnmark - Finnmárku;2971;1027;1944;3013;457;2556;-42;570;-612;\n['Finnmark - Finnmárku', '2971', '1027', '1944', '3013', '457', '2556', '-42', '570', '-612']\n",
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "print(geografiskenhet)\nprint(innflyttingtotalt)",
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "stream",
          "text": "['Akershus', 'Oslo', 'Hedmark', 'Oppland', 'Buskerud', 'Vestfold', 'Telemark', 'Aust-Agder', 'Vest-Agder', 'Rogaland', 'Hordaland', 'Sogn og Fjordane', 'Møre og Romsdal', 'Sør-Trøndelag (-2017)', 'Nord-Trøndelag (-2017)', 'Nordland', 'Troms - Romsa', 'Finnmark - Finnmárku']\n[33739, 43866, 7023, 6822, 11787, 9581, 5394, 4071, 7504, 10741, 13742, 3428, 6737, 12666, 4627, 7336, 6339, 2971]\n",
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "import matplotlib.pyplot as plt\n\nplt.figure(num=None, figsize=(16, 12), dpi=80, facecolor='w', edgecolor='k')\n\nx = innflyttingtotalt\ny = utflyttingtotalt\n\nplt.scatter(x, y)\n\nplt.xlim(0, 1.1*max(max(x),max(y)))\nplt.ylim(0, 1.1*max(max(x),max(y)))\n    \nplt.plot([0, max(max(x),max(y))], [0, max(max(x),max(y))])\n\nplt.xlabel('Innflytting totalt')\nplt.ylabel('Utflytting totalt')\n\n#plt.legend(loc='best')\nplt.grid()\nplt.show()",
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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            "text/plain": "<matplotlib.figure.Figure at 0x7f694abef358>"
          },
          "metadata": {}
        }
      ]
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "import matplotlib.pyplot as plt\n\nplt.figure(num=None, figsize=(16, 12), dpi=80, facecolor='w', edgecolor='k')\n\nx = innflyttingtotalt[1:]\ny = utflyttingtotalt[1:]\n\nplt.scatter(x, y)\n\nplt.xlim(0, 1.1*max(max(x),max(y)))\nplt.ylim(0, 1.1*max(max(x),max(y)))\n    \nplt.plot([0, max(max(x),max(y))], [0, max(max(x),max(y))])\n\nplt.xlabel('Innflytting totalt')\nplt.ylabel('Utflytting totalt')\n\n#plt.legend(loc='best')\nplt.grid()\nplt.show()",
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": "<matplotlib.figure.Figure at 0x7f694ab196d8>"
          },
          "metadata": {}
        }
      ]
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "import matplotlib.pyplot as plt\n\nplt.figure(num=None, figsize=(16, 12), dpi=80, facecolor='w', edgecolor='k')\n\nx = [innflyttingtotalt[1]]\ny = [utflyttingtotalt[1]]\n\nx.extend(innflyttingtotalt[4:])\ny.extend(utflyttingtotalt[4:])\n\nplt.scatter(x, y)\n\nplt.xlim(0, 1.1*max(max(x),max(y)))\nplt.ylim(0, 1.1*max(max(x),max(y)))\n    \nplt.plot([0, max(max(x),max(y))], [0, max(max(x),max(y))])\n\nplt.xlabel('Innflytting totalt')\nplt.ylabel('Utflytting totalt')\n\n#plt.legend(loc='best')\nplt.grid()\nplt.show()",
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": "<matplotlib.figure.Figure at 0x7f694aa8c160>"
          },
          "metadata": {}
        }
      ]
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "for i in range(len(geografiskenhet)):\n    if utflyttingtotalt[i] > innflyttingtotalt[i]:\n        print(geografiskenhet[i])\n        print(utflyttingtotalt[i], innflyttingtotalt[i])",
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "stream",
          "text": "Rogaland\n12163 10741\nSogn og Fjordane\n3599 3428\nFinnmark - Finnmárku\n3013 2971\n",
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "",
      "execution_count": null,
      "outputs": []
    }
  ],
  "metadata": {
    "kernelspec": {
      "name": "python36",
      "display_name": "Python 3.6",
      "language": "python"
    },
    "language_info": {
      "mimetype": "text/x-python",
      "nbconvert_exporter": "python",
      "name": "python",
      "pygments_lexer": "ipython3",
      "version": "3.6.6",
      "file_extension": ".py",
      "codemirror_mode": {
        "version": 3,
        "name": "ipython"
      }
    }
  },
  "nbformat": 4,
  "nbformat_minor": 2
}