mars_data_challenge_part_2.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "67178699",
   "metadata": {},
   "source": [
    "# Deliverable 2: web scraping the Mars Weather Data\n",
    "- The HTML table was extracted into a Pandas DataFrame. Either Pandas or Splinter and Beautiful Soup were used to scrape the data. The columns have the correct headings and data types.\n",
    "- The data was analyzed to answer the following questions, and a data visualization was created to support each answer:\n",
    "    - How many months exist on Mars?\n",
    "    - Which month, on average, has the lowest temperature? The highest?\n",
    "    - Which month, on average, has the lowest atmospheric pressure? The highest?\n",
    "    - How many terrestrial days exist in a Martian year? A visual estimate within 25% was made.\n",
    "    - The DataFrame was exported into a CSV file."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "bb657996",
   "metadata": {},
   "outputs": [],
   "source": [
    "# import dependencies\n",
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib import style\n",
    "from matplotlib.ticker import AutoMinorLocator\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "from splinter import Browser\n",
    "from selenium import webdriver\n",
    "from selenium.webdriver.common.by import By\n",
    "from selenium.webdriver.common.keys import Keys\n",
    "from bs4 import BeautifulSoup as soup\n",
    "# import below when using Chrome browser\n",
    "from selenium.webdriver.chrome.service import Service\n",
    "from webdriver_manager.chrome import ChromeDriverManager"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "0dbf4940",
   "metadata": {},
   "outputs": [],
   "source": [
    "from datetime import datetime as dt\n",
    "import os\n",
    "# set local chromedriver\n",
    "chromedrv = os.path.expanduser('~/ucbDA/chromedriver_win32/chromedriver')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f1fb4fab",
   "metadata": {},
   "source": [
    "## Method 1: Pandas's `read_html`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "9f845e1e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# target url\n",
    "url = 'https://data-class-mars-challenge.s3.amazonaws.com/Mars/index.html'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "480ab6b1",
   "metadata": {},
   "outputs": [],
   "source": [
    "# read table(s) from the website as a pd.DataFrame\n",
    "pd_mars_df = pd.read_html(url)[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "f3105991",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1867 entries, 0 to 1866\n",
      "Data columns (total 7 columns):\n",
      " #   Column            Non-Null Count  Dtype         \n",
      "---  ------            --------------  -----         \n",
      " 0   id                1867 non-null   int64         \n",
      " 1   terrestrial_date  1867 non-null   datetime64[ns]\n",
      " 2   sol               1867 non-null   int64         \n",
      " 3   ls                1867 non-null   int64         \n",
      " 4   month             1867 non-null   int64         \n",
      " 5   min_temp          1867 non-null   float64       \n",
      " 6   pressure          1867 non-null   float64       \n",
      "dtypes: datetime64[ns](1), float64(2), int64(4)\n",
      "memory usage: 102.2 KB\n"
     ]
    }
   ],
   "source": [
    "# convert data to the appropriate data type\n",
    "pd_mars_df['terrestrial_date'] = pd.to_datetime(pd_mars_df['terrestrial_date'])\n",
    "pd_mars_df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "798c01d4",
   "metadata": {},
   "source": [
    "## Method 2: selenium's webdriver and bs4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "a009e9b5",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Visit a site defined in the url (default webdriver = selenium)\n",
    "def geturl(url, webdrv='selenium'):\n",
    "    driver.get(url) if webdrv == 'selenium' else browser.visit(url)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "d3e54dad",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Set some default options for chrome browser\n",
    "options = webdriver.ChromeOptions()\n",
    "options.add_argument(\"--lang=en\")\n",
    "options.add_argument(\"--start-maximized\")\n",
    "options.add_argument(\"--disable-notifications\")\n",
    "# Set up splinter (selenium 4)\n",
    "driver = webdriver.Chrome(service=Service(chromedrv), options=options)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "b16c5301",
   "metadata": {},
   "outputs": [],
   "source": [
    "webdrv = 'selenium'\n",
    "geturl(url, webdrv)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "8a56f54b",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Use the tbody tag to extract a table\n",
    "def get_summary(webdrv='selenium'):\n",
    "    # Parse the HTML\n",
    "    if webdrv == 'selenium':\n",
    "        html = driver.page_source\n",
    "    else:\n",
    "        html = browser.html\n",
    "    html_soup = soup(html, 'html.parser')\n",
    "    mars_data = html_soup.find('tbody')\n",
    "    # extract table headers\n",
    "    theaders.append([th.text for th in mars_data.find_all('th')])\n",
    "    # extract table data\n",
    "    for tr in mars_data.find_all('tr', class_='data-row'):\n",
    "        row = [td.text for td in tr.find_all('td')]\n",
    "        tdata.append(row)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "594b90b5",
   "metadata": {},
   "outputs": [],
   "source": [
    "# list/dict to contain scraped data\n",
    "theaders = []\n",
    "tdata = []\n",
    "get_summary(webdrv)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "513a55cd",
   "metadata": {},
   "outputs": [],
   "source": [
    "if webdrv == 'selenium':\n",
    "    driver.quit()\n",
    "else:\n",
    "    browser.quit()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fef2e35c",
   "metadata": {},
   "source": [
    "## Method 3: splinter's executable_path and bs4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "c5650d98",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Set some default options for chrome browser\n",
    "options = webdriver.ChromeOptions()\n",
    "options.add_argument(\"--lang=en\")\n",
    "options.add_argument(\"--start-maximized\")\n",
    "options.add_argument(\"--disable-notifications\")\n",
    "# Set up splinter (PS: executable_path has deprecated)\n",
    "executable_path = {'executable_path': ChromeDriverManager().install()}\n",
    "browser = Browser('chrome', **executable_path, headless=False, options=options)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "f5e2a82c",
   "metadata": {},
   "outputs": [],
   "source": [
    "webdrv = 'splinter'\n",
    "geturl(url, webdrv)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "a13d6a23",
   "metadata": {},
   "outputs": [],
   "source": [
    "# list/dict to contain scraped data\n",
    "theaders = []\n",
    "tdata = []\n",
    "get_summary(webdrv)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "5d69885f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1867 entries, 0 to 1866\n",
      "Data columns (total 7 columns):\n",
      " #   Column            Non-Null Count  Dtype \n",
      "---  ------            --------------  ----- \n",
      " 0   id                1867 non-null   object\n",
      " 1   terrestrial_date  1867 non-null   object\n",
      " 2   sol               1867 non-null   object\n",
      " 3   ls                1867 non-null   object\n",
      " 4   month             1867 non-null   object\n",
      " 5   min_temp          1867 non-null   object\n",
      " 6   pressure          1867 non-null   object\n",
      "dtypes: object(7)\n",
      "memory usage: 102.2+ KB\n"
     ]
    }
   ],
   "source": [
    "# create pd.DataFrame\n",
    "mars_df = pd.DataFrame(tdata, columns=np.ravel(theaders))\n",
    "mars_df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "8dcbcc6a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mars_df.duplicated().any()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "5fcef6be",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1867 entries, 0 to 1866\n",
      "Data columns (total 7 columns):\n",
      " #   Column            Non-Null Count  Dtype         \n",
      "---  ------            --------------  -----         \n",
      " 0   id                1867 non-null   int64         \n",
      " 1   terrestrial_date  1867 non-null   datetime64[ns]\n",
      " 2   sol               1867 non-null   int64         \n",
      " 3   ls                1867 non-null   int64         \n",
      " 4   month             1867 non-null   int64         \n",
      " 5   min_temp          1867 non-null   float64       \n",
      " 6   pressure          1867 non-null   float64       \n",
      "dtypes: datetime64[ns](1), float64(2), int64(4)\n",
      "memory usage: 102.2 KB\n"
     ]
    }
   ],
   "source": [
    "# convert data to the appropriate data type\n",
    "mars_df.iloc[:, 0] = mars_df.iloc[:, 0].astype(np.int64)\n",
    "mars_df['terrestrial_date'] = pd.to_datetime(mars_df['terrestrial_date'])\n",
    "mars_df.iloc[:, 2:5] = mars_df.iloc[:, 2:5].astype(np.int64)\n",
    "mars_df.iloc[:, -2:] = mars_df.iloc[:, -2:].astype(float)\n",
    "mars_df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "d917ccf0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Both pd.read_html vs splinter/selenium+bs4 methods matched perfectly.'"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "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>id</th>\n",
       "      <th>terrestrial_date</th>\n",
       "      <th>sol</th>\n",
       "      <th>ls</th>\n",
       "      <th>month</th>\n",
       "      <th>min_temp</th>\n",
       "      <th>pressure</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2</td>\n",
       "      <td>2012-08-16</td>\n",
       "      <td>10</td>\n",
       "      <td>155</td>\n",
       "      <td>6</td>\n",
       "      <td>-75.0</td>\n",
       "      <td>739.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>13</td>\n",
       "      <td>2012-08-17</td>\n",
       "      <td>11</td>\n",
       "      <td>156</td>\n",
       "      <td>6</td>\n",
       "      <td>-76.0</td>\n",
       "      <td>740.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>24</td>\n",
       "      <td>2012-08-18</td>\n",
       "      <td>12</td>\n",
       "      <td>156</td>\n",
       "      <td>6</td>\n",
       "      <td>-76.0</td>\n",
       "      <td>741.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>35</td>\n",
       "      <td>2012-08-19</td>\n",
       "      <td>13</td>\n",
       "      <td>157</td>\n",
       "      <td>6</td>\n",
       "      <td>-74.0</td>\n",
       "      <td>732.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>46</td>\n",
       "      <td>2012-08-20</td>\n",
       "      <td>14</td>\n",
       "      <td>157</td>\n",
       "      <td>6</td>\n",
       "      <td>-74.0</td>\n",
       "      <td>740.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   id terrestrial_date  sol   ls  month  min_temp  pressure\n",
       "0   2       2012-08-16   10  155      6     -75.0     739.0\n",
       "1  13       2012-08-17   11  156      6     -76.0     740.0\n",
       "2  24       2012-08-18   12  156      6     -76.0     741.0\n",
       "3  35       2012-08-19   13  157      6     -74.0     732.0\n",
       "4  46       2012-08-20   14  157      6     -74.0     740.0"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Compare dataframes created by pd.read_html vs splinter/selenium+bs4 methods\n",
    "if pd_mars_df.equals(mars_df):\n",
    "    display(\"Both pd.read_html vs splinter/selenium+bs4 methods matched perfectly.\", mars_df.head())\n",
    "else:\n",
    "    display(pd_mars_df.dtypes, mars_df.dtypes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "adef5988",
   "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>id</th>\n",
       "      <th>terrestrial_date</th>\n",
       "      <th>sol</th>\n",
       "      <th>ls</th>\n",
       "      <th>month</th>\n",
       "      <th>min_temp</th>\n",
       "      <th>pressure</th>\n",
       "      <th>ls_rad</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2</td>\n",
       "      <td>2012-08-16</td>\n",
       "      <td>10</td>\n",
       "      <td>155</td>\n",
       "      <td>6</td>\n",
       "      <td>-75.0</td>\n",
       "      <td>739.0</td>\n",
       "      <td>2.705260</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>13</td>\n",
       "      <td>2012-08-17</td>\n",
       "      <td>11</td>\n",
       "      <td>156</td>\n",
       "      <td>6</td>\n",
       "      <td>-76.0</td>\n",
       "      <td>740.0</td>\n",
       "      <td>2.722714</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>24</td>\n",
       "      <td>2012-08-18</td>\n",
       "      <td>12</td>\n",
       "      <td>156</td>\n",
       "      <td>6</td>\n",
       "      <td>-76.0</td>\n",
       "      <td>741.0</td>\n",
       "      <td>2.722714</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>35</td>\n",
       "      <td>2012-08-19</td>\n",
       "      <td>13</td>\n",
       "      <td>157</td>\n",
       "      <td>6</td>\n",
       "      <td>-74.0</td>\n",
       "      <td>732.0</td>\n",
       "      <td>2.740167</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>46</td>\n",
       "      <td>2012-08-20</td>\n",
       "      <td>14</td>\n",
       "      <td>157</td>\n",
       "      <td>6</td>\n",
       "      <td>-74.0</td>\n",
       "      <td>740.0</td>\n",
       "      <td>2.740167</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   id terrestrial_date  sol   ls  month  min_temp  pressure    ls_rad\n",
       "0   2       2012-08-16   10  155      6     -75.0     739.0  2.705260\n",
       "1  13       2012-08-17   11  156      6     -76.0     740.0  2.722714\n",
       "2  24       2012-08-18   12  156      6     -76.0     741.0  2.722714\n",
       "3  35       2012-08-19   13  157      6     -74.0     732.0  2.740167\n",
       "4  46       2012-08-20   14  157      6     -74.0     740.0  2.740167"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# convert ls data to radians\n",
    "mars_df['ls_rad'] = mars_df['ls'] * np.pi / 180\n",
    "mars_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "17bf9ae7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12], dtype=int64)"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# number of Martian months exists on Mars (sorted)\n",
    "mars_months = np.unique(mars_df['month'])\n",
    "mars_months"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "4a258585",
   "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>month</th>\n",
       "      <th>sol</th>\n",
       "      <th>ls</th>\n",
       "      <th>min_temp</th>\n",
       "      <th>pressure</th>\n",
       "      <th>ls_rad</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>1204.406250</td>\n",
       "      <td>75.010417</td>\n",
       "      <td>-83.307292</td>\n",
       "      <td>877.322917</td>\n",
       "      <td>1.309179</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>1244.500000</td>\n",
       "      <td>104.365979</td>\n",
       "      <td>-82.747423</td>\n",
       "      <td>806.329897</td>\n",
       "      <td>1.821530</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>1175.853933</td>\n",
       "      <td>44.258427</td>\n",
       "      <td>-79.932584</td>\n",
       "      <td>889.455056</td>\n",
       "      <td>0.772455</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>1182.691275</td>\n",
       "      <td>132.885906</td>\n",
       "      <td>-79.308725</td>\n",
       "      <td>748.557047</td>\n",
       "      <td>2.319297</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>1077.574713</td>\n",
       "      <td>15.281609</td>\n",
       "      <td>-77.160920</td>\n",
       "      <td>862.488506</td>\n",
       "      <td>0.266714</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>750.829932</td>\n",
       "      <td>164.897959</td>\n",
       "      <td>-75.299320</td>\n",
       "      <td>745.054422</td>\n",
       "      <td>2.878012</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>12</td>\n",
       "      <td>990.951807</td>\n",
       "      <td>344.692771</td>\n",
       "      <td>-74.451807</td>\n",
       "      <td>842.156627</td>\n",
       "      <td>6.016024</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>715.105634</td>\n",
       "      <td>194.894366</td>\n",
       "      <td>-72.281690</td>\n",
       "      <td>795.105634</td>\n",
       "      <td>3.401548</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>11</td>\n",
       "      <td>947.224638</td>\n",
       "      <td>314.536232</td>\n",
       "      <td>-71.985507</td>\n",
       "      <td>857.014493</td>\n",
       "      <td>5.489693</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>1034.669643</td>\n",
       "      <td>286.330357</td>\n",
       "      <td>-71.982143</td>\n",
       "      <td>887.312500</td>\n",
       "      <td>4.997407</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>861.186567</td>\n",
       "      <td>254.052239</td>\n",
       "      <td>-69.171642</td>\n",
       "      <td>913.305970</td>\n",
       "      <td>4.434048</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>795.333333</td>\n",
       "      <td>224.347518</td>\n",
       "      <td>-68.382979</td>\n",
       "      <td>873.829787</td>\n",
       "      <td>3.915603</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    month          sol          ls   min_temp    pressure    ls_rad\n",
       "2       3  1204.406250   75.010417 -83.307292  877.322917  1.309179\n",
       "3       4  1244.500000  104.365979 -82.747423  806.329897  1.821530\n",
       "1       2  1175.853933   44.258427 -79.932584  889.455056  0.772455\n",
       "4       5  1182.691275  132.885906 -79.308725  748.557047  2.319297\n",
       "0       1  1077.574713   15.281609 -77.160920  862.488506  0.266714\n",
       "5       6   750.829932  164.897959 -75.299320  745.054422  2.878012\n",
       "11     12   990.951807  344.692771 -74.451807  842.156627  6.016024\n",
       "6       7   715.105634  194.894366 -72.281690  795.105634  3.401548\n",
       "10     11   947.224638  314.536232 -71.985507  857.014493  5.489693\n",
       "9      10  1034.669643  286.330357 -71.982143  887.312500  4.997407\n",
       "8       9   861.186567  254.052239 -69.171642  913.305970  4.434048\n",
       "7       8   795.333333  224.347518 -68.382979  873.829787  3.915603"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# get table headers\n",
    "headers = list(mars_df)\n",
    "# coldest and warmest months on Mars\n",
    "mintemp_df = mars_df[headers[2:]].groupby('month', as_index=False).mean().sort_values('min_temp')\n",
    "mintemp_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "cd137167",
   "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>terrestrial_date</th>\n",
       "      <th>sol</th>\n",
       "      <th>ls</th>\n",
       "      <th>month</th>\n",
       "      <th>min_temp</th>\n",
       "      <th>pressure</th>\n",
       "      <th>ls_rad</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1093</th>\n",
       "      <td>2015-12-09</td>\n",
       "      <td>1188</td>\n",
       "      <td>79</td>\n",
       "      <td>3</td>\n",
       "      <td>-90.0</td>\n",
       "      <td>881.0</td>\n",
       "      <td>1.378810</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1582</th>\n",
       "      <td>2017-05-10</td>\n",
       "      <td>1692</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>-62.0</td>\n",
       "      <td>820.0</td>\n",
       "      <td>0.034907</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     terrestrial_date   sol  ls  month  min_temp  pressure    ls_rad\n",
       "1093       2015-12-09  1188  79      3     -90.0     881.0  1.378810\n",
       "1582       2017-05-10  1692   2      1     -62.0     820.0  0.034907"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mars_df.loc[(mars_df['min_temp'] == mars_df['min_temp'].min()) | (mars_df['min_temp'] == mars_df['min_temp'].max()), headers[1:]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "1d6cd9ac",
   "metadata": {},
   "outputs": [],
   "source": [
    "# plot the average minimum daily temperature of all the months\n",
    "def barplot(x, y, title):\n",
    "    style.use('fivethirtyeight')\n",
    "    fig, ax = plt.subplots(figsize=(8, 5))\n",
    "    ax.bar(x, y)\n",
    "    ax.set_title(title)\n",
    "    ax.set_xlabel(f'{title.split()[-2]} {title.split()[-1]}')\n",
    "    ax.set_xticks(x)\n",
    "    if 'min temperature' in title.lower():\n",
    "        ax.set_ylabel('Min Temperature (\\N{DEGREE SIGN}F)')\n",
    "        ax.set_yticks(np.arange(0, -91, -10))\n",
    "        figname = './Data/mars_mintemp.png'\n",
    "    elif 'pressure' in title.lower():\n",
    "        ax.set_ylabel('Pressure')\n",
    "        ax.set_yticks(np.arange(0, 1001, 100))\n",
    "        figname = './Data/mars_pressure.png'\n",
    "    elif 'longitude' in title.lower():\n",
    "        ax.set_ylabel('Solar Longitude (rad)')\n",
    "        figname = './Data/mars_solarlongitude.png'\n",
    "    else:\n",
    "        ax.set_ylabel(f'{title.split()[1]} {title.split()[2]} (sols)')\n",
    "        figname = './Data/mars_elapsedsol.png'\n",
    "    # Save the figure.\n",
    "    fig.savefig(figname, bbox_inches='tight', facecolor='w')\n",
    "    # Show Figure\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "d8d2240d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "barplot(mintemp_df['month'], mintemp_df['min_temp'], 'Mars Min Temperature by Martian Month')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "e280fdfd",
   "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>month</th>\n",
       "      <th>sol</th>\n",
       "      <th>ls</th>\n",
       "      <th>min_temp</th>\n",
       "      <th>pressure</th>\n",
       "      <th>ls_rad</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>750.829932</td>\n",
       "      <td>164.897959</td>\n",
       "      <td>-75.299320</td>\n",
       "      <td>745.054422</td>\n",
       "      <td>2.878012</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>1182.691275</td>\n",
       "      <td>132.885906</td>\n",
       "      <td>-79.308725</td>\n",
       "      <td>748.557047</td>\n",
       "      <td>2.319297</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>715.105634</td>\n",
       "      <td>194.894366</td>\n",
       "      <td>-72.281690</td>\n",
       "      <td>795.105634</td>\n",
       "      <td>3.401548</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>1244.500000</td>\n",
       "      <td>104.365979</td>\n",
       "      <td>-82.747423</td>\n",
       "      <td>806.329897</td>\n",
       "      <td>1.821530</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>12</td>\n",
       "      <td>990.951807</td>\n",
       "      <td>344.692771</td>\n",
       "      <td>-74.451807</td>\n",
       "      <td>842.156627</td>\n",
       "      <td>6.016024</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>11</td>\n",
       "      <td>947.224638</td>\n",
       "      <td>314.536232</td>\n",
       "      <td>-71.985507</td>\n",
       "      <td>857.014493</td>\n",
       "      <td>5.489693</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>1077.574713</td>\n",
       "      <td>15.281609</td>\n",
       "      <td>-77.160920</td>\n",
       "      <td>862.488506</td>\n",
       "      <td>0.266714</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>795.333333</td>\n",
       "      <td>224.347518</td>\n",
       "      <td>-68.382979</td>\n",
       "      <td>873.829787</td>\n",
       "      <td>3.915603</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>1204.406250</td>\n",
       "      <td>75.010417</td>\n",
       "      <td>-83.307292</td>\n",
       "      <td>877.322917</td>\n",
       "      <td>1.309179</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>1034.669643</td>\n",
       "      <td>286.330357</td>\n",
       "      <td>-71.982143</td>\n",
       "      <td>887.312500</td>\n",
       "      <td>4.997407</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>1175.853933</td>\n",
       "      <td>44.258427</td>\n",
       "      <td>-79.932584</td>\n",
       "      <td>889.455056</td>\n",
       "      <td>0.772455</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>861.186567</td>\n",
       "      <td>254.052239</td>\n",
       "      <td>-69.171642</td>\n",
       "      <td>913.305970</td>\n",
       "      <td>4.434048</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    month          sol          ls   min_temp    pressure    ls_rad\n",
       "5       6   750.829932  164.897959 -75.299320  745.054422  2.878012\n",
       "4       5  1182.691275  132.885906 -79.308725  748.557047  2.319297\n",
       "6       7   715.105634  194.894366 -72.281690  795.105634  3.401548\n",
       "3       4  1244.500000  104.365979 -82.747423  806.329897  1.821530\n",
       "11     12   990.951807  344.692771 -74.451807  842.156627  6.016024\n",
       "10     11   947.224638  314.536232 -71.985507  857.014493  5.489693\n",
       "0       1  1077.574713   15.281609 -77.160920  862.488506  0.266714\n",
       "7       8   795.333333  224.347518 -68.382979  873.829787  3.915603\n",
       "2       3  1204.406250   75.010417 -83.307292  877.322917  1.309179\n",
       "9      10  1034.669643  286.330357 -71.982143  887.312500  4.997407\n",
       "1       2  1175.853933   44.258427 -79.932584  889.455056  0.772455\n",
       "8       9   861.186567  254.052239 -69.171642  913.305970  4.434048"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# months on Mars with lowest and highest atmospheric pressure\n",
    "pressure_df = mars_df[headers[2:]].groupby('month', as_index=False).mean().sort_values('pressure')\n",
    "pressure_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "34de406f",
   "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>terrestrial_date</th>\n",
       "      <th>sol</th>\n",
       "      <th>ls</th>\n",
       "      <th>month</th>\n",
       "      <th>min_temp</th>\n",
       "      <th>pressure</th>\n",
       "      <th>ls_rad</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>156</th>\n",
       "      <td>2013-01-27</td>\n",
       "      <td>170</td>\n",
       "      <td>252</td>\n",
       "      <td>9</td>\n",
       "      <td>-66.0</td>\n",
       "      <td>925.0</td>\n",
       "      <td>4.398230</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>157</th>\n",
       "      <td>2013-01-28</td>\n",
       "      <td>171</td>\n",
       "      <td>253</td>\n",
       "      <td>9</td>\n",
       "      <td>-67.0</td>\n",
       "      <td>925.0</td>\n",
       "      <td>4.415683</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>766</th>\n",
       "      <td>2014-12-23</td>\n",
       "      <td>846</td>\n",
       "      <td>257</td>\n",
       "      <td>9</td>\n",
       "      <td>-74.0</td>\n",
       "      <td>925.0</td>\n",
       "      <td>4.485496</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1866</th>\n",
       "      <td>2018-02-27</td>\n",
       "      <td>1977</td>\n",
       "      <td>135</td>\n",
       "      <td>5</td>\n",
       "      <td>-77.0</td>\n",
       "      <td>727.0</td>\n",
       "      <td>2.356194</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     terrestrial_date   sol   ls  month  min_temp  pressure    ls_rad\n",
       "156        2013-01-27   170  252      9     -66.0     925.0  4.398230\n",
       "157        2013-01-28   171  253      9     -67.0     925.0  4.415683\n",
       "766        2014-12-23   846  257      9     -74.0     925.0  4.485496\n",
       "1866       2018-02-27  1977  135      5     -77.0     727.0  2.356194"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mars_df.loc[(mars_df['pressure'] == mars_df['pressure'].min()) | (mars_df['pressure'] == mars_df['pressure'].max()), headers[1:]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "c0f236a4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot the average atmospheric daily pressure of all the months\n",
    "barplot(pressure_df['month'], pressure_df['pressure'], 'Mars Atmospheric Pressure by Martian Month')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "4d4f2f90",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "barplot(mintemp_df['month'], mintemp_df['sol'], 'Mars Elapsed Sols by Martian Month')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "6b63fd33",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Reimport Matplotlib.\n",
    "import matplotlib\n",
    "# Reset the style from Matplotlib to default.\n",
    "matplotlib.rcParams.update(matplotlib.rcParamsDefault)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "dc0f40a8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# bar chart on polar axis to show how solar longitudes change phases\n",
    "theta = mintemp_df['ls_rad']\n",
    "radii = 20\n",
    "width = np.pi / len(mars_months)\n",
    "ax = plt.subplot(projection='polar')\n",
    "ax.bar(theta, radii, width=width, bottom=2.0, alpha=0.5)\n",
    "ax.set_title('Mars Solar Longitude Ls by Martian Month')\n",
    "ax.set_theta_zero_location('S')\n",
    "# sun emoji as the center of the polar projection\n",
    "ax.set_ylabel(u\"\\u2600\", fontsize=64, color='tab:orange')\n",
    "ax.yaxis.set_label_coords(np.pi/5, np.pi/6)\n",
    "# Save the figure.\n",
    "figname = './Data/mars_solarlongitude.png'\n",
    "plt.savefig(figname, bbox_inches='tight', facecolor='w')\n",
    "# Show Figure\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "fce157d2",
   "metadata": {},
   "outputs": [],
   "source": [
    "# # group the solar longitude Ls in the dataset\n",
    "# ls_ranges = np.arange(0, 360, 30)\n",
    "# mars_df['ls_range'] = pd.cut(mars_df['ls'], ls_ranges)\n",
    "# mars_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "8a2b15e4",
   "metadata": {},
   "outputs": [],
   "source": [
    "# plot the average minimum daily temperature of all the months\n",
    "def plot2D(x, y, title):\n",
    "    plt.rc('lines', linewidth=2, color='r')\n",
    "    fig, ax = plt.subplots(figsize=(10, 5))\n",
    "    ax.set_title(title, fontsize=18)\n",
    "    ax.set_xlabel(title.split()[-1], fontsize=14)\n",
    "    ax.set_ylabel('Min Temperature (\\N{DEGREE SIGN}F)', fontsize=14)\n",
    "    ax.set_xticks(np.arange(0, 2001, 200))\n",
    "    ax.xaxis.set_minor_locator(AutoMinorLocator(4))\n",
    "    ax.tick_params(axis='x', which='minor', bottom=False)\n",
    "    ax.set_yticks(np.arange(-60, -96, -5))\n",
    "    ax.grid(which='both')\n",
    "    ax.plot(x, y, '*')\n",
    "    # Save the figure.\n",
    "    figname = './Data/mars_mintemp_daily.png'\n",
    "    fig.savefig(figname, bbox_inches='tight', facecolor='w')\n",
    "    # Show Figure\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "9c4f0106",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot2D(mars_df['sol'], mars_df['min_temp'], 'Mars Daily Min Temperature by Mars Sol')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "d771a678",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "max    1977\n",
      "min      10\n",
      "Name: sol, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "# 1 earth day = 86164.0916s or 23.93 hours (https://phys.org/news/2015-11-day-earth.html)\n",
    "# 1 martian day = 88775.245s or 24.66 hours (http://www-mars.lmd.jussieu.fr/mars/time/solar_longitude.html)\n",
    "# calculate how many sols exist in a Martian year based on monthly elapsed sols\n",
    "sols = 0\n",
    "for mm in mars_months:\n",
    "    sol_duration = mars_df.loc[mars_df['month'] == mm, 'sol'].max() - mars_df.loc[mars_df['month'] == mm, 'sol'].min()\n",
    "    sols += (sol_duration / 24.66)\n",
    "# number of Martian days included in the dataset\n",
    "print(mars_df['sol'].agg(['max', 'min']))\n",
    "sol_range = mars_df['sol'].max() - mars_df['sol'].min()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "f2310902",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mars sols in a Martian year (statistical estimate): 675.710\n",
      "Mars sols in a Martian year (visual estimate):      666.780\n",
      "Mars sols in a Martian year (average estimate):     669.730\n"
     ]
    }
   ],
   "source": [
    "# statistically calculate total orbital periods (= total Martian years)\n",
    "mars_year = sol_range/sols\n",
    "# Visually estimate the result from the daily minimum temperature plots\n",
    "visual_mars_year = [2.9, 3.0, mars_year]\n",
    "avg_visual_mars_year = np.mean(visual_mars_year[:2])\n",
    "avg_mars_year = np.mean(visual_mars_year)\n",
    "print(\n",
    "    f'Mars sols in a Martian year (statistical estimate): {sols:.3f}\\n'\n",
    "    f'Mars sols in a Martian year (visual estimate):      {sol_range/avg_visual_mars_year:.3f}\\n'\n",
    "    f'Mars sols in a Martian year (average estimate):     {sol_range/avg_mars_year:.3f}'\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "66123d75",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "max   2018-02-27\n",
      "min   2012-08-16\n",
      "Name: terrestrial_date, dtype: datetime64[ns]\n"
     ]
    }
   ],
   "source": [
    "# number of terrestrial days included in the dataset\n",
    "print(mars_df['terrestrial_date'].agg(['max', 'min']))\n",
    "tday_range = (mars_df['terrestrial_date'].max() - mars_df['terrestrial_date'].min()).days"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "c4744a70",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calculate total terrestrial years in the dataset (Mars orbits the Sun once = 1 Martian year) \n",
    "earth_year = tday_range / 365.25"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "429fd43c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# estimate how many Earth days exist in a Martian year \n",
    "visual_sols_to_earthdays = tday_range / avg_visual_mars_year\n",
    "avg_sols_to_earthdays = tday_range / avg_mars_year\n",
    "ref_period = 687\n",
    "pct_visual_period_diff = (visual_sols_to_earthdays / ref_period - 1)*100\n",
    "pct_avg_period_diff = (avg_sols_to_earthdays / ref_period - 1)*100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "5210df79",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "- Exact Earth years in the dataset:                  5.533\n",
      "- Martian years in the dataset (visual estimate):    2.950\n",
      "- Martian years in the dataset (average estimate):   2.937\n",
      "- Earth days in a Martian year (visual estimate):  685.085 (-0.279%)\n",
      "- Earth days in a Martian year (average estimate): 688.116 ( 0.162%)\n"
     ]
    }
   ],
   "source": [
    "# Calculate total years in the dataset and summary results for markdown report\n",
    "print(\n",
    "    f'- Exact Earth years in the dataset:                {earth_year:7.3f}\\n'\n",
    "    f'- Martian years in the dataset (visual estimate):  {avg_visual_mars_year:7.3f}\\n'\n",
    "    f'- Martian years in the dataset (average estimate): {avg_mars_year:7.3f}\\n'\n",
    "    f'- Earth days in a Martian year (visual estimate):  {visual_sols_to_earthdays:7.3f} ({pct_visual_period_diff:6.3f}%)\\n'\n",
    "    f'- Earth days in a Martian year (average estimate): {avg_sols_to_earthdays:7.3f} ({pct_avg_period_diff:6.3f}%)'\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "4a43b45a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Export the DataFrame as a CSV file (encoding='utf-8' by default on Python 3)\n",
    "file_name = './Data/mars_data.csv'\n",
    "mars_df.to_csv(file_name, index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "98652626",
   "metadata": {},
   "outputs": [],
   "source": [
    "if webdrv == 'selenium':\n",
    "    driver.quit()\n",
    "else:\n",
    "    browser.quit()"
   ]
  }
 ],
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