{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>.container { width:100% !important; }</style>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from IPython.core.display import display, HTML\n",
    "display(HTML(\"<style>.container { width:100% !important; }</style>\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "from selenium import webdriver\n",
    "from selenium.webdriver.chrome.options import Options\n",
    "from selenium.common.exceptions import NoSuchElementException\n",
    "\n",
    "options = Options()\n",
    "#options.headless = True\n",
    "b = webdriver.Chrome(options=options)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "import time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "still waiting\n",
      "still waiting\n",
      "still waiting\n",
      "still waiting\n"
     ]
    }
   ],
   "source": [
    "b.get(\"https://tyler.caraza-harter.com/cs320/s20/materials/lec-19/page1.html\")\n",
    "\n",
    "# poll (check) until we have the data\n",
    "for i in range(40):\n",
    "    try:\n",
    "        b.find_element_by_id(\"coords\")\n",
    "        break\n",
    "    except NoSuchElementException:\n",
    "        print(\"still waiting\")\n",
    "        time.sleep(0.25)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "from bs4 import BeautifulSoup\n",
    "page = BeautifulSoup(b.page_source)\n",
    "tbls = page.find_all(\"table\")\n",
    "assert len(tbls) == 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[['x', 'y'],\n",
       " ['0', '1'],\n",
       " ['2', '3'],\n",
       " ['4', '5'],\n",
       " ['6', '7'],\n",
       " ['8', '9'],\n",
       " ['10', '11'],\n",
       " ['12', '13'],\n",
       " ['14', '15'],\n",
       " ['16', '17'],\n",
       " ['18', '19']]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rows = []\n",
    "for tr in tbls[1].find_all(\"tr\"):\n",
    "    rows.append([td.get_text() for td in tr.find_all(\"td\")])\n",
    "rows"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "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>x</th>\n",
       "      <th>y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>6</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>8</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>10</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>12</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>14</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>16</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>18</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    x   y\n",
       "0   0   1\n",
       "1   2   3\n",
       "2   4   5\n",
       "3   6   7\n",
       "4   8   9\n",
       "5  10  11\n",
       "6  12  13\n",
       "7  14  15\n",
       "8  16  17\n",
       "9  18  19"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "pd.DataFrame(rows[1:], columns=rows[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "b.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "options = Options()\n",
    "#options.headless = True\n",
    "b = webdriver.Chrome(options=options)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "# page2.html\n",
    "b.get(\"https://tyler.caraza-harter.com/cs320/s20/materials/lec-19/page2.html\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "while True:\n",
    "    try:\n",
    "        btn = b.find_element_by_id(\"more\")\n",
    "    except NoSuchElementException:\n",
    "        break\n",
    "    btn.click()\n",
    "    time.sleep(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "from bs4 import BeautifulSoup\n",
    "page = BeautifulSoup(b.page_source)\n",
    "tbls = page.find_all(\"table\")\n",
    "assert len(tbls) == 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "b.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "options = Options()\n",
    "#options.headless = True\n",
    "b = webdriver.Chrome(options=options)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "# page3.html\n",
    "b.get(\"https://tyler.caraza-harter.com/cs320/s20/materials/lec-19/page3.html\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<selenium.webdriver.remote.webelement.WebElement (session=\"4fdc27c540f3c1e6504e37e3f774e54d\", element=\"0.2842643579606472-1\")>"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "btn = b.find_element_by_id(\"login_btn\")\n",
    "btn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<selenium.webdriver.remote.webelement.WebElement (session=\"4fdc27c540f3c1e6504e37e3f774e54d\", element=\"0.2842643579606472-2\")>"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pw = b.find_element_by_id(\"password\")\n",
    "pw"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "pw.clear()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "pw.send_keys(\"fido\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "btn.click()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "b.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "options = Options()\n",
    "#options.headless = True\n",
    "b = webdriver.Chrome(options=options)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "# page4.html\n",
    "b.get(\"https://tyler.caraza-harter.com/cs320/s20/materials/lec-19/page4.html\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<selenium.webdriver.remote.webelement.WebElement (session=\"7841b63d5390db596bb759a7fdd61c78\", element=\"0.24516250497320424-1\")>"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "year_box = b.find_element_by_id(\"year\")\n",
    "year_box"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<selenium.webdriver.remote.webelement.WebElement (session=\"7841b63d5390db596bb759a7fdd61c78\", element=\"0.24516250497320424-2\")>"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "search_btn = b.find_element_by_id(\"search_btn\")\n",
    "search_btn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def hurricane_count(year):\n",
    "    year_box.clear()\n",
    "    year_box.send_keys(str(year))\n",
    "    search_btn.click()\n",
    "    \n",
    "    trs = b.find_elements_by_tag_name(\"tr\")\n",
    "    return len(trs) - 1\n",
    "\n",
    "hurricane_count(1950)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "s = pd.Series()\n",
    "for year in range(1950, 2020):\n",
    "    s.loc[year] = hurricane_count(year)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib\n",
    "matplotlib.rcParams[\"font.size\"] = 16"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = s.plot.line(color=\"r\")\n",
    "ax.set_xlabel(\"Year\")\n",
    "ax.set_ylabel(\"Hurricane Count\")\n",
    "ax.spines[\"right\"].set_visible(False)\n",
    "ax.spines[\"top\"].set_visible(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.7.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}