데이터분석 시각화 문제 (최종).ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# -*- incoding: utf-8 -*-\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import time as t"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'date': '04/25', 'people': 10},\n",
       " {'date': '04/26', 'people': 10},\n",
       " {'date': '04/27', 'people': 10},\n",
       " {'date': '04/28', 'people': 14},\n",
       " {'date': '04/29', 'people': 9},\n",
       " {'date': '04/30', 'people': 4},\n",
       " {'date': '05/01', 'people': 4}]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "covid19 = []\n",
    "date = []\n",
    "xl=pd.ExcelFile(\"covid.xls\")\n",
    "df=xl.parse('Sheet1')\n",
    "for day in df['날짜']:\n",
    "    date.append((str(day)[5:7] + '/' + str(day)[8:10]))\n",
    "for i, d in enumerate(date):\n",
    "    covid19.append({'date': d, 'people': df['일별확진자수'][i]})\n",
    "covid19\n",
    "# covid19 = [\n",
    "#     {'date': '04/25', 'people': 10},\n",
    "#     {'date': '04/26', 'people': 10},\n",
    "#     {'date': '04/27', 'people': 10},\n",
    "#     {'date': '04/28', 'people': 14},\n",
    "#     {'date': '04/29', 'people': 9},\n",
    "#     {'date': '04/30', 'people': 4},\n",
    "#     {'date': '05/01', 'people': 4},\n",
    "# ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x161f0765808>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.rc('font', family='Malgun Gothic')\n",
    "\n",
    "date = []\n",
    "people = []\n",
    "for day in covid19:\n",
    "    date.append(day['date'])\n",
    "    people.append(day['people'])\n",
    "    \n",
    "plt.figure(figsize = (12, 6))\n",
    "plt.plot(date, people, color='hotpink', label='확진자 수')\n",
    "plt.grid(True, color='gray', alpha=0.5)\n",
    "plt.xlabel('날짜',fontsize=14)\n",
    "plt.ylabel('확진자 수',fontsize=14)\n",
    "plt.title('코로나19 일별 확진자 수',fontsize='18')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## [문제2] 누적 확진자 수와 누적 격리해제에 대한 시각화하기"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'04/25': {'확진': 10718, '격리해제': 8635},\n",
       " '04/26': {'확진': 10728, '격리해제': 8717},\n",
       " '04/27': {'확진': 10738, '격리해제': 8764},\n",
       " '04/28': {'확진': 10752, '격리해제': 8854},\n",
       " '04/29': {'확진': 10761, '격리해제': 8922},\n",
       " '04/30': {'확진': 10765, '격리해제': 9059},\n",
       " '05/01': {'확진': 10744, '격리해제': 9072}}"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "covid19 = {}\n",
    "date = []\n",
    "xl=pd.ExcelFile(\"covid.xls\")\n",
    "df=xl.parse('Sheet1')\n",
    "for day in df['날짜']:\n",
    "    date.append((str(day)[5:7] + '/' + str(day)[8:10]))\n",
    "for i, d in enumerate(date):\n",
    "    covid19.update({d: {'확진': df['누적환자수'][i], '격리해제': df['누적격리해제'][i]}})\n",
    "covid19\n",
    "# covid19 = {\n",
    "#     '04/25': {\"확진\": 10718, '격리해제': 8635},\n",
    "#     '04/26': {\"확진\": 10728, '격리해제': 8717},\n",
    "#     '04/27': {\"확진\": 10738, '격리해제': 8764},\n",
    "#     '04/28': {\"확진\": 10752, '격리해제': 8854},\n",
    "#     '04/29': {\"확진\": 10761, '격리해제': 8922},\n",
    "#     '04/30': {\"확진\": 10765, '격리해제': 9059},\n",
    "#     '05/01': {\"확진\": 10774, '격리해제': 9072},\n",
    "# }"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, '코로나19 확진, 격리해제 추세')"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "date = []\n",
    "hak = []\n",
    "kyeok = []\n",
    "for day in covid19.items():\n",
    "    date.append(day[0])\n",
    "    hak.append(day[1]['확진'])\n",
    "    kyeok.append(day[1]['격리해제'])\n",
    "\n",
    "plt.figure(figsize = (12, 6))\n",
    "plt.plot(date, hak, label='누적 확진자 수', color='red')\n",
    "plt.plot(date, kyeok, label='누적 격리해제', color='orange')\n",
    "plt.legend(loc=\"center left\", title='범주')\n",
    "plt.grid(True, color='gray', alpha=0.5)\n",
    "plt.xlabel('날짜',fontsize=14)\n",
    "plt.ylabel('명',fontsize=14)\n",
    "plt.title('코로나19 확진, 격리해제 추세',fontsize='18')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## [문제3] 연령대별 확진자 수 시각화하기"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'80이상': 488,\n",
       " '70-79': 710,\n",
       " '60-69': 1351,\n",
       " '50-59': 1956,\n",
       " '40-49': 1432,\n",
       " '30-39': 1163,\n",
       " '20-29': 2962,\n",
       " '10-19': 591,\n",
       " '0-9': 140}"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "xl=pd.ExcelFile(\"covid.xls\")    \n",
    "df=xl.parse('Sheet2')\n",
    "covid19 = dict(zip(df['구분'], df['확진자(명)']))\n",
    "covid19\n",
    "# covid19 = {\n",
    "#     \"80이상\": 488,\n",
    "#     \"70~79\": 710,\n",
    "#     \"60~69\": 1351,\n",
    "#     \"50~59\": 1956,\n",
    "#     \"40~49\": 1432,\n",
    "#     \"30~39\": 1163,\n",
    "#     \"20~29\": 2962,\n",
    "#     \"10~19\": 591,\n",
    "#     \"0~9\": 140,\n",
    "# }"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, '코로나19 연령대별 확진자 수')"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "age = []\n",
    "people = []\n",
    "for day in covid19.items():\n",
    "    age.append(day[0])\n",
    "    people.append(day[1])\n",
    "\n",
    "plt.figure(figsize = (16,8))\n",
    "for i in range(len(age)):\n",
    "    plt.text(people[i], i-0.1, f\"{people[i]}명\", color='red', size='large')\n",
    "plt.barh(age, people, label='확진자 수')\n",
    "plt.legend(loc=\"best\")\n",
    "plt.grid(True, color='gray', alpha=0.5)\n",
    "plt.xlabel('연령대',fontsize=14)\n",
    "plt.ylabel('명',fontsize=14)\n",
    "plt.title('코로나19 연령대별 확진자 수',fontsize='18')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## [문제4] 연령대별 확진/사망자 수 시각화하기"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'80이상': {'확진': 488, '사망': 120},\n",
       " '70-79': {'확진': 710, '사망': 75},\n",
       " '60-69': {'확진': 1351, '사망': 35},\n",
       " '50-59': {'확진': 1956, '사망': 15},\n",
       " '40-49': {'확진': 1432, '사망': 3},\n",
       " '30-39': {'확진': 1163, '사망': 2},\n",
       " '20-29': {'확진': 2962, '사망': 0},\n",
       " '10-19': {'확진': 591, '사망': 0},\n",
       " '0-9': {'확진': 140, '사망': 0}}"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "date = []\n",
    "people = []\n",
    "covid19 = {}\n",
    "xl=pd.ExcelFile(\"covid.xls\")    \n",
    "df=xl.parse('Sheet2')\n",
    "for i in range(df['구분'].size):\n",
    "    covid19.update({df['구분'][i]: {'확진': df['확진자(명)'][i], '사망': df['사망자(명)'][i]}})\n",
    "covid19\n",
    "# covid19 = {\n",
    "#     \"80이상\": {\"확진\": 488, \"사망\": 120},\n",
    "#     \"70~79\": {\"확진\": 710, \"사망\": 75},\n",
    "#     \"60~69\": {\"확진\": 1351, \"사망\": 35},\n",
    "#     \"50~59\": {\"확진\": 1956, \"사망\": 15},\n",
    "#     \"40~49\": {\"확진\": 1432, \"사망\": 3},\n",
    "#     \"30~39\": {\"확진\": 1163, \"사망\": 2},\n",
    "#     \"20~29\": {\"확진\": 2962, \"사망\": 0},\n",
    "#     \"10~19\": {\"확진\": 591, \"사망\": 0},\n",
    "#     \"0~9\": {\"확진\": 140, \"사망\": 0},\n",
    "# }"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "([<matplotlib.axis.XTick at 0x161f0b16688>,\n",
       "  <matplotlib.axis.XTick at 0x161f0b10d48>,\n",
       "  <matplotlib.axis.XTick at 0x161f0b10948>,\n",
       "  <matplotlib.axis.XTick at 0x161f0917108>,\n",
       "  <matplotlib.axis.XTick at 0x161f09177c8>,\n",
       "  <matplotlib.axis.XTick at 0x161f0917348>,\n",
       "  <matplotlib.axis.XTick at 0x161f0ba00c8>,\n",
       "  <matplotlib.axis.XTick at 0x161f0ba0ac8>,\n",
       "  <matplotlib.axis.XTick at 0x161f0ba5408>],\n",
       " <a list of 9 Text xticklabel objects>)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "bar_width = 0.4\n",
    "age = []\n",
    "live = []\n",
    "dead = []\n",
    "for day in covid19.items():\n",
    "    age.append(day[0])\n",
    "    live.append(day[1]['확진'])\n",
    "    dead.append(day[1]['사망'])\n",
    "x = np.arange(0, len(age))   \n",
    "    \n",
    "plt.figure(figsize = (16, 8))\n",
    "for i in range(len(age)):\n",
    "    plt.text(i-0.2, live[i]+20, f'{live[i]}명', size='medium', ha='center', color='blue')\n",
    "    plt.text(i+0.2, dead[i]+20, f'{dead[i]}명', size='medium', ha='center', color='red')\n",
    "plt.bar(x-0.2, live, bar_width, label='확진')\n",
    "plt.bar(x+0.2, dead, bar_width, label='사망', color='red')\n",
    "plt.legend(loc=\"best\")\n",
    "plt.grid(True, color='gray', alpha=0.5)\n",
    "plt.xlabel('연령대',fontsize=14)\n",
    "plt.ylabel('명',fontsize=14)\n",
    "plt.title('연령대별 확진자/사망자 수',fontsize='18')\n",
    "plt.xticks(x, labels=age)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## [문제5] 연령대별 확진비율 시각화하기"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'80이상': {'확진': 488, '사망': 120},\n",
       " '70-79': {'확진': 710, '사망': 75},\n",
       " '60-69': {'확진': 1351, '사망': 35},\n",
       " '50-59': {'확진': 1956, '사망': 15},\n",
       " '40-49': {'확진': 1432, '사망': 3},\n",
       " '30-39': {'확진': 1163, '사망': 2},\n",
       " '20-29': {'확진': 2962, '사망': 0},\n",
       " '10-19': {'확진': 591, '사망': 0},\n",
       " '0-9': {'확진': 140, '사망': 0}}"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "covid19"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, '연령대별 확진 비율')"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "age = []\n",
    "live = []\n",
    "for day in covid19.items():\n",
    "    age.append(day[0])\n",
    "    live.append(day[1]['확진'])\n",
    "    \n",
    "plt.figure(figsize = (10, 10))\n",
    "plt.pie(live, labels=age, autopct='%1.2f%%')\n",
    "plt.title('연령대별 확진 비율',fontsize='18')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## [문제6] 교통 사고 통계 분석 시각화 하기\n",
    "\n",
    "#### 1) 데이터 가져오기"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>년도</th>\n",
       "      <th>월</th>\n",
       "      <th>발생건수</th>\n",
       "      <th>사망자수</th>\n",
       "      <th>부상자수</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2005</td>\n",
       "      <td>1</td>\n",
       "      <td>15494</td>\n",
       "      <td>504</td>\n",
       "      <td>25413</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2005</td>\n",
       "      <td>2</td>\n",
       "      <td>13244</td>\n",
       "      <td>431</td>\n",
       "      <td>21635</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2005</td>\n",
       "      <td>3</td>\n",
       "      <td>16580</td>\n",
       "      <td>477</td>\n",
       "      <td>25550</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2005</td>\n",
       "      <td>4</td>\n",
       "      <td>17817</td>\n",
       "      <td>507</td>\n",
       "      <td>28131</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2005</td>\n",
       "      <td>5</td>\n",
       "      <td>19085</td>\n",
       "      <td>571</td>\n",
       "      <td>29808</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>163</th>\n",
       "      <td>2018</td>\n",
       "      <td>8</td>\n",
       "      <td>18335</td>\n",
       "      <td>357</td>\n",
       "      <td>27749</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>164</th>\n",
       "      <td>2018</td>\n",
       "      <td>9</td>\n",
       "      <td>18371</td>\n",
       "      <td>348</td>\n",
       "      <td>27751</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>165</th>\n",
       "      <td>2018</td>\n",
       "      <td>10</td>\n",
       "      <td>19738</td>\n",
       "      <td>373</td>\n",
       "      <td>28836</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>166</th>\n",
       "      <td>2018</td>\n",
       "      <td>11</td>\n",
       "      <td>19029</td>\n",
       "      <td>298</td>\n",
       "      <td>28000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167</th>\n",
       "      <td>2018</td>\n",
       "      <td>12</td>\n",
       "      <td>18010</td>\n",
       "      <td>323</td>\n",
       "      <td>26463</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>168 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       년도   월   발생건수  사망자수   부상자수\n",
       "0    2005   1  15494   504  25413\n",
       "1    2005   2  13244   431  21635\n",
       "2    2005   3  16580   477  25550\n",
       "3    2005   4  17817   507  28131\n",
       "4    2005   5  19085   571  29808\n",
       "..    ...  ..    ...   ...    ...\n",
       "163  2018   8  18335   357  27749\n",
       "164  2018   9  18371   348  27751\n",
       "165  2018  10  19738   373  28836\n",
       "166  2018  11  19029   298  28000\n",
       "167  2018  12  18010   323  26463\n",
       "\n",
       "[168 rows x 5 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy\n",
    "from pandas import DataFrame\n",
    "from pandas import read_csv\n",
    "from matplotlib import pyplot as plt\n",
    "\n",
    "data=read_csv('traffic.csv', encoding='cp949')\n",
    "data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 2) 데이터 전처리 하기"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>년도</th>\n",
       "      <th>발생건수</th>\n",
       "      <th>사망자수</th>\n",
       "      <th>부상자수</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2005</td>\n",
       "      <td>214171</td>\n",
       "      <td>6376</td>\n",
       "      <td>342233</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2006</td>\n",
       "      <td>213745</td>\n",
       "      <td>6327</td>\n",
       "      <td>340229</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2007</td>\n",
       "      <td>211662</td>\n",
       "      <td>6166</td>\n",
       "      <td>335906</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2008</td>\n",
       "      <td>215822</td>\n",
       "      <td>5870</td>\n",
       "      <td>338962</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2009</td>\n",
       "      <td>231990</td>\n",
       "      <td>5838</td>\n",
       "      <td>361875</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2010</td>\n",
       "      <td>226878</td>\n",
       "      <td>5505</td>\n",
       "      <td>352458</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2011</td>\n",
       "      <td>221711</td>\n",
       "      <td>5229</td>\n",
       "      <td>341391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2012</td>\n",
       "      <td>223656</td>\n",
       "      <td>5392</td>\n",
       "      <td>344565</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2013</td>\n",
       "      <td>215354</td>\n",
       "      <td>5092</td>\n",
       "      <td>328711</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2014</td>\n",
       "      <td>223552</td>\n",
       "      <td>4762</td>\n",
       "      <td>337497</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2015</td>\n",
       "      <td>232035</td>\n",
       "      <td>4621</td>\n",
       "      <td>350400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2016</td>\n",
       "      <td>220917</td>\n",
       "      <td>4292</td>\n",
       "      <td>331720</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2017</td>\n",
       "      <td>216335</td>\n",
       "      <td>4185</td>\n",
       "      <td>322829</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2018</td>\n",
       "      <td>217148</td>\n",
       "      <td>3781</td>\n",
       "      <td>323037</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      년도    발생건수  사망자수    부상자수\n",
       "0   2005  214171  6376  342233\n",
       "1   2006  213745  6327  340229\n",
       "2   2007  211662  6166  335906\n",
       "3   2008  215822  5870  338962\n",
       "4   2009  231990  5838  361875\n",
       "5   2010  226878  5505  352458\n",
       "6   2011  221711  5229  341391\n",
       "7   2012  223656  5392  344565\n",
       "8   2013  215354  5092  328711\n",
       "9   2014  223552  4762  337497\n",
       "10  2015  232035  4621  350400\n",
       "11  2016  220917  4292  331720\n",
       "12  2017  216335  4185  322829\n",
       "13  2018  217148  3781  323037"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_for_year = []\n",
    "for i in range(2005, 2018+1):\n",
    "    year = data[data[\"년도\"] == i]\n",
    "    data_for_year.append([i, sum(year['발생건수']), sum(year['사망자수']), sum(year['부상자수'])])\n",
    "df = DataFrame(data_for_year, columns=['년도','발생건수','사망자수', '부상자수'])\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 3) 년도별 교통사고 발생현황 시각화 하기"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x161f0c3ca48>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (14, 7))\n",
    "plt.plot(df['년도'], df['발생건수'], color='red', label='발생건수')\n",
    "plt.grid(True, color='gray', alpha=0.5)\n",
    "plt.xlabel('년도',fontsize=14)\n",
    "plt.ylabel('교통사고 수',fontsize=14)\n",
    "plt.title('년도별 교통사고 발생현황',fontsize='18')\n",
    "plt.xticks(df['년도'], labels=map(lambda x: f'{x}년', df['년도']))\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 4) 년도별 교통사고 발생현황 시각화 하기\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x161f0ffdf48>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (14, 7))\n",
    "plt.plot(df['년도'], df['발생건수'], color='RoyalBlue', label='발생건수')\n",
    "plt.plot(df['년도'], df['사망자수'], color='SandyBrown', label='사망자수')\n",
    "plt.plot(df['년도'], df['부상자수'], color='OliveDrab', label='부상자수')\n",
    "plt.grid(True, color='gray', alpha=0.5)\n",
    "plt.xlabel('년도',fontsize=14)\n",
    "plt.ylabel('교통사고 수',fontsize=14)\n",
    "plt.title('년도별 교통사고 발생현황',fontsize='18')\n",
    "plt.xticks(df['년도'], labels=map(lambda x: f'{x}년', df['년도']))\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 5) 추세선을 포함한 산점도 그래프 그리기"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib.pylab import plot\n",
    "\n",
    "plt.figure(figsize = (14, 7))\n",
    "plt.scatter(data['발생건수'], data['부상자수'], s=16, c='Tomato')\n",
    "plt.grid(True, color='gray', alpha=0.5)\n",
    "plt.xlabel('발생건수',fontsize=14)\n",
    "plt.ylabel('부상자수',fontsize=14)\n",
    "plt.title('교통사고 발생건수와 부상자수의 상관관계',fontsize='18')\n",
    "\n",
    "z = np.polyfit(data['발생건수'], data['부상자수'], 1) # (X, Y, 차원)\n",
    "p = np.poly1d(z) # 1차원 다항식에 대한 연산을 캡슐화\n",
    "plot(data['발생건수'] ,p(data['발생건수']), c='r')\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}