week-02/orbital-mechanics-and-exoplanets/nasa-exoplanet-archive.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# NASA Exoplanet Archive\n",
    "\n",
    "-1. Going through [NASA Exoplanet Archive](https://exoplanetarchive.ipac.caltech.edu/)\n",
    "\n",
    "Learning Aspects:\n",
    "\n",
    "0. See an example of an exoplanet mass-radius diagram using data from the Exoplanet Archive\n",
    "\n",
    "1. Learn how to **download** data from the Exoplanet Archive ourselves\n",
    "\n",
    "2. **Visualize** the radius distribution of transiting exoplanets discovered by the *Kepler* space mission\n",
    "\n",
    "#### Tasks:\n",
    "\n",
    "Create an **orbital period vs radius** diagram for the transiting exoplanets from *Kepler*. Comment on any features that you see.\n",
    "\n",
    "For your plots make sure you **label your axes with units** and **choose useful axis scales**!\n",
    "\n",
    "## Note: \n",
    "None of the data files have been shared because you are expected to download the required data yourself from the website give above\n",
    "\n",
    "#### Updated June 2020, Joey Murphy(Intro to Astro) and Modified July 2021, Hrishabh Srivastava"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# It's always nice to have a cell at the top of your jupyter notebook for housing all of your import statements\n",
    "# and \"magic commands\" (lines that start with %), if any.\n",
    "\n",
    "# For bonus points: add a comment to your future self on why you're importing each module\n",
    "\n",
    "# File/directory handling\n",
    "import os \n",
    "\n",
    "# Data handling\n",
    "import pandas as pd\n",
    "pd.set_option('display.max_columns', None) # Display all of the columns of a DataFrame\n",
    "\n",
    "# For math\n",
    "import numpy as np\n",
    "\n",
    "# Plotting\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# \"Magic command\" to make the plots appear *inline* in the notebook\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Mass-radius diagram example"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Data will be loaded from: data/confirmed_example.csv\n"
     ]
    }
   ],
   "source": [
    "# Create a variable for the path to the file containing our example's data\n",
    "data_dir = 'data'\n",
    "data_fname = 'confirmed_example.csv'\n",
    "data_path = os.path.join(data_dir, data_fname) # os.path.join creates a valid path out of the directory and filename\n",
    "print(f'Data will be loaded from: {data_path}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load the data that's stored in the .csv file from the cell above (csv == comma separated values).\n",
    "# Load this data into a Pandas DataFrame object using the Pandas function read_csv().\n",
    "\n",
    "example_data = pd.read_csv(data_path, comment='#')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
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       "      <th>st_optmagerr</th>\n",
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       "      <th>gaia_gmaglim</th>\n",
       "      <th>st_teff</th>\n",
       "      <th>st_tefferr1</th>\n",
       "      <th>st_tefferr2</th>\n",
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       "      <th>st_mass</th>\n",
       "      <th>st_masserr1</th>\n",
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       "      <th>st_rad</th>\n",
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       "      <th>pl_facility</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2MASS J02192210-3925225</td>\n",
       "      <td>b</td>\n",
       "      <td>2MASS J02192210-3925225 b</td>\n",
       "      <td>Imaging</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>156.00000</td>\n",
       "      <td>10.00000</td>\n",
       "      <td>-10.00000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13.90000</td>\n",
       "      <td>1.10000</td>\n",
       "      <td>-1.10000</td>\n",
       "      <td>0</td>\n",
       "      <td>Mass</td>\n",
       "      <td>1.44</td>\n",
       "      <td>0.030</td>\n",
       "      <td>-0.030</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>02h19m22.11s</td>\n",
       "      <td>34.842106</td>\n",
       "      <td>-39d25m22.5s</td>\n",
       "      <td>-39.422928</td>\n",
       "      <td>39.40</td>\n",
       "      <td>2.60</td>\n",
       "      <td>-2.60</td>\n",
       "      <td>0</td>\n",
       "      <td>40.09</td>\n",
       "      <td>0.19</td>\n",
       "      <td>-0.19</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15.012</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3064.0</td>\n",
       "      <td>76.0</td>\n",
       "      <td>-76.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.11</td>\n",
       "      <td>0.01</td>\n",
       "      <td>-0.01</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.28</td>\n",
       "      <td>0.01</td>\n",
       "      <td>-0.01</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2015-05-14</td>\n",
       "      <td>Cerro Tololo Inter-American Observatory</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2MASS J21402931+1625183 A</td>\n",
       "      <td>b</td>\n",
       "      <td>2MASS J21402931+1625183 A b</td>\n",
       "      <td>Imaging</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>7336.500000</td>\n",
       "      <td>1934.500000</td>\n",
       "      <td>-584.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.26</td>\n",
       "      <td>0.06</td>\n",
       "      <td>-0.06</td>\n",
       "      <td>0.0</td>\n",
       "      <td>46.20</td>\n",
       "      <td>2.50</td>\n",
       "      <td>-8.70</td>\n",
       "      <td>0.0</td>\n",
       "      <td>20.95000</td>\n",
       "      <td>83.79000</td>\n",
       "      <td>-20.95000</td>\n",
       "      <td>0</td>\n",
       "      <td>Mass</td>\n",
       "      <td>0.92</td>\n",
       "      <td>0.390</td>\n",
       "      <td>-0.360</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>21h40m29.32s</td>\n",
       "      <td>325.122159</td>\n",
       "      <td>+16d25m18.3s</td>\n",
       "      <td>16.421759</td>\n",
       "      <td>25.00</td>\n",
       "      <td>10.00</td>\n",
       "      <td>-10.00</td>\n",
       "      <td>0</td>\n",
       "      <td>33.12</td>\n",
       "      <td>0.48</td>\n",
       "      <td>-0.48</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>17.396</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2300.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>-80.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.08</td>\n",
       "      <td>0.06</td>\n",
       "      <td>-0.06</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.12</td>\n",
       "      <td>0.05</td>\n",
       "      <td>-0.04</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2014-05-14</td>\n",
       "      <td>W. M. Keck Observatory</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>55 Cnc</td>\n",
       "      <td>e</td>\n",
       "      <td>55 Cnc e</td>\n",
       "      <td>Radial Velocity</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>0.736539</td>\n",
       "      <td>0.000007</td>\n",
       "      <td>-0.000007</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.01544</td>\n",
       "      <td>0.00009</td>\n",
       "      <td>-0.00009</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>83.30</td>\n",
       "      <td>0.90</td>\n",
       "      <td>-0.80</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.02542</td>\n",
       "      <td>0.00098</td>\n",
       "      <td>-0.00098</td>\n",
       "      <td>0</td>\n",
       "      <td>Mass</td>\n",
       "      <td>0.17</td>\n",
       "      <td>0.007</td>\n",
       "      <td>-0.007</td>\n",
       "      <td>0</td>\n",
       "      <td>6.4</td>\n",
       "      <td>0.8</td>\n",
       "      <td>-0.7</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>08h52m35.81s</td>\n",
       "      <td>133.149216</td>\n",
       "      <td>+28d19m50.9s</td>\n",
       "      <td>28.330818</td>\n",
       "      <td>12.59</td>\n",
       "      <td>0.01</td>\n",
       "      <td>-0.01</td>\n",
       "      <td>0</td>\n",
       "      <td>12.59</td>\n",
       "      <td>0.01</td>\n",
       "      <td>-0.01</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.960</td>\n",
       "      <td>0.010</td>\n",
       "      <td>0.0</td>\n",
       "      <td>V (Johnson)</td>\n",
       "      <td>5.714</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5196.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>-24.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.91</td>\n",
       "      <td>0.01</td>\n",
       "      <td>-0.01</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.94</td>\n",
       "      <td>0.01</td>\n",
       "      <td>-0.01</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2019-01-31</td>\n",
       "      <td>McDonald Observatory</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>BD+20 594</td>\n",
       "      <td>b</td>\n",
       "      <td>BD+20 594 b</td>\n",
       "      <td>Transit</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>41.685500</td>\n",
       "      <td>0.003000</td>\n",
       "      <td>-0.003000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>89.55</td>\n",
       "      <td>0.16</td>\n",
       "      <td>-0.16</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.07000</td>\n",
       "      <td>0.03000</td>\n",
       "      <td>-0.03000</td>\n",
       "      <td>0</td>\n",
       "      <td>Mass</td>\n",
       "      <td>0.23</td>\n",
       "      <td>0.010</td>\n",
       "      <td>-0.010</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>03h34m36.23s</td>\n",
       "      <td>53.650967</td>\n",
       "      <td>+20d35m57.2s</td>\n",
       "      <td>20.599232</td>\n",
       "      <td>180.39</td>\n",
       "      <td>1.25</td>\n",
       "      <td>-1.25</td>\n",
       "      <td>0</td>\n",
       "      <td>180.39</td>\n",
       "      <td>1.25</td>\n",
       "      <td>-1.25</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.038</td>\n",
       "      <td>0.047</td>\n",
       "      <td>0.0</td>\n",
       "      <td>V (Johnson)</td>\n",
       "      <td>10.864</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5766.0</td>\n",
       "      <td>99.0</td>\n",
       "      <td>-99.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.67</td>\n",
       "      <td>0.40</td>\n",
       "      <td>-0.40</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.08</td>\n",
       "      <td>0.06</td>\n",
       "      <td>-0.06</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2018-04-26</td>\n",
       "      <td>K2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>CT Cha</td>\n",
       "      <td>b</td>\n",
       "      <td>CT Cha b</td>\n",
       "      <td>Imaging</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>440.00000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>17.00000</td>\n",
       "      <td>6.00000</td>\n",
       "      <td>-6.00000</td>\n",
       "      <td>0</td>\n",
       "      <td>Mass</td>\n",
       "      <td>2.20</td>\n",
       "      <td>0.810</td>\n",
       "      <td>-0.600</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>11h04m09.09s</td>\n",
       "      <td>166.037877</td>\n",
       "      <td>-76d27m19.4s</td>\n",
       "      <td>-76.455383</td>\n",
       "      <td>165.00</td>\n",
       "      <td>30.00</td>\n",
       "      <td>-30.00</td>\n",
       "      <td>0</td>\n",
       "      <td>191.78</td>\n",
       "      <td>0.78</td>\n",
       "      <td>-0.78</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11.773</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2014-05-14</td>\n",
       "      <td>Paranal Observatory</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 pl_hostname pl_letter                      pl_name  \\\n",
       "0    2MASS J02192210-3925225         b    2MASS J02192210-3925225 b   \n",
       "1  2MASS J21402931+1625183 A         b  2MASS J21402931+1625183 A b   \n",
       "2                     55 Cnc         e                     55 Cnc e   \n",
       "3                  BD+20 594         b                  BD+20 594 b   \n",
       "4                     CT Cha         b                     CT Cha b   \n",
       "\n",
       "     pl_discmethod  pl_controvflag  pl_pnum    pl_orbper  pl_orbpererr1  \\\n",
       "0          Imaging               0        1          NaN            NaN   \n",
       "1          Imaging               0        1  7336.500000    1934.500000   \n",
       "2  Radial Velocity               0        5     0.736539       0.000007   \n",
       "3          Transit               0        1    41.685500       0.003000   \n",
       "4          Imaging               0        1          NaN            NaN   \n",
       "\n",
       "   pl_orbpererr2  pl_orbperlim  pl_orbsmax  pl_orbsmaxerr1  pl_orbsmaxerr2  \\\n",
       "0            NaN           NaN   156.00000        10.00000       -10.00000   \n",
       "1    -584.000000           0.0         NaN             NaN             NaN   \n",
       "2      -0.000007           0.0     0.01544         0.00009        -0.00009   \n",
       "3      -0.003000           0.0         NaN             NaN             NaN   \n",
       "4            NaN           NaN   440.00000             NaN             NaN   \n",
       "\n",
       "   pl_orbsmaxlim  pl_orbeccen  pl_orbeccenerr1  pl_orbeccenerr2  \\\n",
       "0            0.0          NaN              NaN              NaN   \n",
       "1            NaN         0.26             0.06            -0.06   \n",
       "2            0.0          NaN              NaN              NaN   \n",
       "3            NaN         0.00              NaN              NaN   \n",
       "4            0.0          NaN              NaN              NaN   \n",
       "\n",
       "   pl_orbeccenlim  pl_orbincl  pl_orbinclerr1  pl_orbinclerr2  pl_orbincllim  \\\n",
       "0             NaN         NaN             NaN             NaN            NaN   \n",
       "1             0.0       46.20            2.50           -8.70            0.0   \n",
       "2             NaN       83.30            0.90           -0.80            0.0   \n",
       "3             0.0       89.55            0.16           -0.16            0.0   \n",
       "4             NaN         NaN             NaN             NaN            NaN   \n",
       "\n",
       "   pl_bmassj  pl_bmassjerr1  pl_bmassjerr2  pl_bmassjlim pl_bmassprov  \\\n",
       "0   13.90000        1.10000       -1.10000             0         Mass   \n",
       "1   20.95000       83.79000      -20.95000             0         Mass   \n",
       "2    0.02542        0.00098       -0.00098             0         Mass   \n",
       "3    0.07000        0.03000       -0.03000             0         Mass   \n",
       "4   17.00000        6.00000       -6.00000             0         Mass   \n",
       "\n",
       "   pl_radj  pl_radjerr1  pl_radjerr2  pl_radjlim  pl_dens  pl_denserr1  \\\n",
       "0     1.44        0.030       -0.030           0      NaN          NaN   \n",
       "1     0.92        0.390       -0.360           0      NaN          NaN   \n",
       "2     0.17        0.007       -0.007           0      6.4          0.8   \n",
       "3     0.23        0.010       -0.010           0      NaN          NaN   \n",
       "4     2.20        0.810       -0.600           0      NaN          NaN   \n",
       "\n",
       "   pl_denserr2  pl_denslim  pl_ttvflag  pl_kepflag  pl_k2flag  pl_nnotes  \\\n",
       "0          NaN         NaN           0           0          0          0   \n",
       "1          NaN         NaN           0           0          0          0   \n",
       "2         -0.7         0.0           0           0          0          1   \n",
       "3          NaN         NaN           0           0          1          1   \n",
       "4          NaN         NaN           0           0          0          0   \n",
       "\n",
       "         ra_str          ra       dec_str        dec  st_dist  st_disterr1  \\\n",
       "0  02h19m22.11s   34.842106  -39d25m22.5s -39.422928    39.40         2.60   \n",
       "1  21h40m29.32s  325.122159  +16d25m18.3s  16.421759    25.00        10.00   \n",
       "2  08h52m35.81s  133.149216  +28d19m50.9s  28.330818    12.59         0.01   \n",
       "3  03h34m36.23s   53.650967  +20d35m57.2s  20.599232   180.39         1.25   \n",
       "4  11h04m09.09s  166.037877  -76d27m19.4s -76.455383   165.00        30.00   \n",
       "\n",
       "   st_disterr2  st_distlim  gaia_dist  gaia_disterr1  gaia_disterr2  \\\n",
       "0        -2.60           0      40.09           0.19          -0.19   \n",
       "1       -10.00           0      33.12           0.48          -0.48   \n",
       "2        -0.01           0      12.59           0.01          -0.01   \n",
       "3        -1.25           0     180.39           1.25          -1.25   \n",
       "4       -30.00           0     191.78           0.78          -0.78   \n",
       "\n",
       "   gaia_distlim  st_optmag  st_optmagerr  st_optmaglim   st_optband  \\\n",
       "0           0.0        NaN           NaN           NaN          NaN   \n",
       "1           0.0        NaN           NaN           NaN          NaN   \n",
       "2           0.0      5.960         0.010           0.0  V (Johnson)   \n",
       "3           0.0     11.038         0.047           0.0  V (Johnson)   \n",
       "4           0.0        NaN           NaN           NaN          NaN   \n",
       "\n",
       "   gaia_gmag  gaia_gmagerr  gaia_gmaglim  st_teff  st_tefferr1  st_tefferr2  \\\n",
       "0     15.012           NaN           0.0   3064.0         76.0        -76.0   \n",
       "1     17.396           NaN           0.0   2300.0         80.0        -80.0   \n",
       "2      5.714           NaN           0.0   5196.0         24.0        -24.0   \n",
       "3     10.864           NaN           0.0   5766.0         99.0        -99.0   \n",
       "4     11.773           NaN           0.0      NaN          NaN          NaN   \n",
       "\n",
       "   st_tefflim  st_mass  st_masserr1  st_masserr2  st_masslim  st_rad  \\\n",
       "0         0.0     0.11         0.01        -0.01         0.0    0.28   \n",
       "1         0.0     0.08         0.06        -0.06         0.0    0.12   \n",
       "2         0.0     0.91         0.01        -0.01         0.0    0.94   \n",
       "3         0.0     1.67         0.40        -0.40         0.0    1.08   \n",
       "4         NaN      NaN          NaN          NaN         NaN     NaN   \n",
       "\n",
       "   st_raderr1  st_raderr2  st_radlim   rowupdate  \\\n",
       "0        0.01       -0.01        0.0  2015-05-14   \n",
       "1        0.05       -0.04        0.0  2014-05-14   \n",
       "2        0.01       -0.01        0.0  2019-01-31   \n",
       "3        0.06       -0.06        0.0  2018-04-26   \n",
       "4         NaN         NaN        NaN  2014-05-14   \n",
       "\n",
       "                               pl_facility  \n",
       "0  Cerro Tololo Inter-American Observatory  \n",
       "1                   W. M. Keck Observatory  \n",
       "2                     McDonald Observatory  \n",
       "3                                       K2  \n",
       "4                      Paranal Observatory  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "example_data.head() # What sort of data is contained in this pandas.DataFrame?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(762, 72)\n"
     ]
    }
   ],
   "source": [
    "# What are the dimensions of this DataFrame?\n",
    "print(example_data.shape) # prints (# of rows, # of columns)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "What do all of these columns mean? Let's checkout the .csv file itself for more information!\n",
    "\n",
    "...\n",
    "\n",
    "So we saw that this table was generated from the Exoplanet Archive, and whoever generated it enforced some constraints: the mass and radius (in units of Jupiter mass and radius) must **not** be *null* i.e. we only want to download planets that have both a radius **and** a mass measurement.\n",
    "\n",
    "We also saw that there were a **ton** of columns that we didn't really mention in that table, and some are a little more useful than others. That's okay, for now let's just load *all* of the data into a Pandas DataFrame and then we can choose which columns we actually want to use."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/hrishabh/.local/lib/python3.7/site-packages/matplotlib/cbook/__init__.py:1402: FutureWarning: Support for multi-dimensional indexing (e.g. `obj[:, None]`) is deprecated and will be removed in a future version.  Convert to a numpy array before indexing instead.\n",
      "  ndim = x[:, None].ndim\n",
      "/home/hrishabh/.local/lib/python3.7/site-packages/matplotlib/axes/_base.py:276: FutureWarning: Support for multi-dimensional indexing (e.g. `obj[:, None]`) is deprecated and will be removed in a future version.  Convert to a numpy array before indexing instead.\n",
      "  x = x[:, np.newaxis]\n",
      "/home/hrishabh/.local/lib/python3.7/site-packages/matplotlib/axes/_base.py:278: FutureWarning: Support for multi-dimensional indexing (e.g. `obj[:, None]`) is deprecated and will be removed in a future version.  Convert to a numpy array before indexing instead.\n",
      "  y = y[:, np.newaxis]\n"
     ]
    },
    {
     "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": [
    "# Make a quick mass-radius diagram!\n",
    "\n",
    "# Plot the data with mass (in units of Jupiter masses) on the x-axis and radius \n",
    "# (in units of Jupiter radii) on the y-axis.\n",
    "\n",
    "# '.'   --> use small unconnected dots to plot the data points\n",
    "# alpha --> governs the transparency of each datapoint: 0 = completely transparent, 1 = completely opaque.\n",
    "# (alpha = 0.3 will let us see the density of the data points more easily)\n",
    "plt.plot(example_data['pl_bmassj'], example_data['pl_radj'], '.', alpha=0.3)\n",
    "\n",
    "# At the end, show the plot\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The plot above is alright, but it seems like a lot of data is bunched up at low masses and the large range of the data makes it hard to see the finer structure... let's replot things with **log axes**. Let's also add **axis labels** so we actually know what is being plotted. As a bonus, we'll add some text to the plot to show **how many** exoplanets are being included."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "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": [
    "# Plot the data with mass (in units of Jupiter masses) on the x-axis\n",
    "plt.plot(example_data['pl_bmassj'], example_data['pl_radj'], '.', alpha=0.3)\n",
    "\n",
    "# Label your axes with units!\n",
    "plt.xlabel('Mass [M$_J$]', fontsize=14)   # You can use LaTex formatting to make your plots look more professional...\n",
    "plt.ylabel('Radius [R$_J$]', fontsize=14) # more on LaTex later in the summer! $_J$ creates a subscript J for Jupiter\n",
    "\n",
    "# Add some text to the plot so we know how many data points there are\n",
    "n_planets = len(example_data) # Number of planets being plotted\n",
    "\n",
    "# plt.text(x-coordinate, y-coordinate, text string, **kwargs) # x and y coordinates are in data units\n",
    "plt.text(1e-3, 1, f'N = {n_planets}', fontsize=14)\n",
    "\n",
    "# Set the x and y-axis scales to be log so we can see structure more easily\n",
    "plt.xscale('log')\n",
    "plt.yscale('log')\n",
    "\n",
    "# At the end, show the plot\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Downloading a sample of exoplanets subject to constraints\n",
    "\n",
    "Now that we've plotted some of the data from the Exoplanet Archive, how do we download it ourselves? How did I get that complicated-looking .csv file with all of the data in the first place?\n",
    "\n",
    "Our mission: \n",
    "\n",
    "1. Go to the [Exoplanet Archive](https://exoplanetarchive.ipac.caltech.edu/) website and navigate to the **Confirmed Planets** table after clicking the **Data** tab at the top of the home page.\n",
    "2. This time, let's **add columns** so we have **planet mass and radius** in **units of Earth mass and Earth radius**\n",
    "3. Enter constraints into the query boxes at the top of the columns to get all of the planets **discovered by *Kepler*** via the **transit method**. Make sure to **exclude** any rows that might have a **null radius measurement** for one reason or another.\n",
    "4. **Download** the table as a **.csv** and **save** it to a **subdirectory** named **\"data\"**. Be sure to give your .csv file an informative name."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Data will be loaded from: data/confirmed_kepler_transiting.csv\n"
     ]
    }
   ],
   "source": [
    "# Like before, let's first create the path to our new .csv file\n",
    "data_fname = 'confirmed_kepler_transiting.csv'\n",
    "data_path = os.path.join(data_dir, data_fname)\n",
    "print(f'Data will be loaded from: {data_path}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(2317, 80)\n"
     ]
    }
   ],
   "source": [
    "# Load the data into a Pandas DataFrame object\n",
    "kepler_data = pd.read_csv(data_path, comment='#')\n",
    "\n",
    "# How many rows and columns do we have this time?\n",
    "print(kepler_data.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Any idea why we have so many rows of planets this time than before? \n",
    "\n",
    "*Hint: We the confirmed_example.csv file was generated with a constraint on a different planet parameter that we didn't include here*"
   ]
  },
  {
   "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>pl_hostname</th>\n",
       "      <th>pl_letter</th>\n",
       "      <th>pl_name</th>\n",
       "      <th>pl_discmethod</th>\n",
       "      <th>pl_controvflag</th>\n",
       "      <th>pl_pnum</th>\n",
       "      <th>pl_orbper</th>\n",
       "      <th>pl_orbpererr1</th>\n",
       "      <th>pl_orbpererr2</th>\n",
       "      <th>pl_orbperlim</th>\n",
       "      <th>pl_orbsmax</th>\n",
       "      <th>pl_orbsmaxerr1</th>\n",
       "      <th>pl_orbsmaxerr2</th>\n",
       "      <th>pl_orbsmaxlim</th>\n",
       "      <th>pl_orbeccen</th>\n",
       "      <th>pl_orbeccenerr1</th>\n",
       "      <th>pl_orbeccenerr2</th>\n",
       "      <th>pl_orbeccenlim</th>\n",
       "      <th>pl_orbincl</th>\n",
       "      <th>pl_orbinclerr1</th>\n",
       "      <th>pl_orbinclerr2</th>\n",
       "      <th>pl_orbincllim</th>\n",
       "      <th>pl_bmassj</th>\n",
       "      <th>pl_bmassjerr1</th>\n",
       "      <th>pl_bmassjerr2</th>\n",
       "      <th>pl_bmassjlim</th>\n",
       "      <th>pl_bmassprov</th>\n",
       "      <th>pl_radj</th>\n",
       "      <th>pl_radjerr1</th>\n",
       "      <th>pl_radjerr2</th>\n",
       "      <th>pl_radjlim</th>\n",
       "      <th>pl_dens</th>\n",
       "      <th>pl_denserr1</th>\n",
       "      <th>pl_denserr2</th>\n",
       "      <th>pl_denslim</th>\n",
       "      <th>pl_ttvflag</th>\n",
       "      <th>pl_kepflag</th>\n",
       "      <th>pl_k2flag</th>\n",
       "      <th>pl_nnotes</th>\n",
       "      <th>ra_str</th>\n",
       "      <th>ra</th>\n",
       "      <th>dec_str</th>\n",
       "      <th>dec</th>\n",
       "      <th>st_dist</th>\n",
       "      <th>st_disterr1</th>\n",
       "      <th>st_disterr2</th>\n",
       "      <th>st_distlim</th>\n",
       "      <th>gaia_dist</th>\n",
       "      <th>gaia_disterr1</th>\n",
       "      <th>gaia_disterr2</th>\n",
       "      <th>gaia_distlim</th>\n",
       "      <th>st_optmag</th>\n",
       "      <th>st_optmagerr</th>\n",
       "      <th>st_optmaglim</th>\n",
       "      <th>st_optband</th>\n",
       "      <th>gaia_gmag</th>\n",
       "      <th>gaia_gmagerr</th>\n",
       "      <th>gaia_gmaglim</th>\n",
       "      <th>st_teff</th>\n",
       "      <th>st_tefferr1</th>\n",
       "      <th>st_tefferr2</th>\n",
       "      <th>st_tefflim</th>\n",
       "      <th>st_mass</th>\n",
       "      <th>st_masserr1</th>\n",
       "      <th>st_masserr2</th>\n",
       "      <th>st_masslim</th>\n",
       "      <th>st_rad</th>\n",
       "      <th>st_raderr1</th>\n",
       "      <th>st_raderr2</th>\n",
       "      <th>st_radlim</th>\n",
       "      <th>rowupdate</th>\n",
       "      <th>pl_masse</th>\n",
       "      <th>pl_masseerr1</th>\n",
       "      <th>pl_masseerr2</th>\n",
       "      <th>pl_masselim</th>\n",
       "      <th>pl_rade</th>\n",
       "      <th>pl_radeerr1</th>\n",
       "      <th>pl_radeerr2</th>\n",
       "      <th>pl_radelim</th>\n",
       "      <th>pl_facility</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>KIC 10525077</td>\n",
       "      <td>b</td>\n",
       "      <td>KIC 10525077 b</td>\n",
       "      <td>Transit</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>854.0830</td>\n",
       "      <td>0.01628</td>\n",
       "      <td>-0.01697</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>89.861</td>\n",
       "      <td>0.096</td>\n",
       "      <td>-0.098</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.491</td>\n",
       "      <td>0.080</td>\n",
       "      <td>-0.071</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>19h09m30.74s</td>\n",
       "      <td>287.378077</td>\n",
       "      <td>+47d46m16.3s</td>\n",
       "      <td>47.771187</td>\n",
       "      <td>1525.31</td>\n",
       "      <td>58.45</td>\n",
       "      <td>-58.45</td>\n",
       "      <td>0</td>\n",
       "      <td>1525.31</td>\n",
       "      <td>58.45</td>\n",
       "      <td>-58.45</td>\n",
       "      <td>0.0</td>\n",
       "      <td>15.355</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>Kepler-band</td>\n",
       "      <td>15.304</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6091.0</td>\n",
       "      <td>164.0</td>\n",
       "      <td>-213.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.01</td>\n",
       "      <td>0.12</td>\n",
       "      <td>-0.12</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.01</td>\n",
       "      <td>0.10</td>\n",
       "      <td>-0.10</td>\n",
       "      <td>0</td>\n",
       "      <td>2016-01-05</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.5</td>\n",
       "      <td>0.9</td>\n",
       "      <td>-0.8</td>\n",
       "      <td>0</td>\n",
       "      <td>Kepler</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>KIC 3558849</td>\n",
       "      <td>b</td>\n",
       "      <td>KIC 3558849 b</td>\n",
       "      <td>Transit</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1322.3000</td>\n",
       "      <td>386.10000</td>\n",
       "      <td>-11.20000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>89.973</td>\n",
       "      <td>0.023</td>\n",
       "      <td>-0.031</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.616</td>\n",
       "      <td>0.089</td>\n",
       "      <td>-0.080</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>19h39m47.96s</td>\n",
       "      <td>294.949847</td>\n",
       "      <td>+38d36m18.7s</td>\n",
       "      <td>38.605197</td>\n",
       "      <td>1258.75</td>\n",
       "      <td>35.41</td>\n",
       "      <td>-35.41</td>\n",
       "      <td>0</td>\n",
       "      <td>1258.75</td>\n",
       "      <td>35.41</td>\n",
       "      <td>-35.41</td>\n",
       "      <td>0.0</td>\n",
       "      <td>14.218</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>Kepler-band</td>\n",
       "      <td>14.167</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6175.0</td>\n",
       "      <td>168.0</td>\n",
       "      <td>-194.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.98</td>\n",
       "      <td>0.11</td>\n",
       "      <td>-0.11</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.01</td>\n",
       "      <td>0.11</td>\n",
       "      <td>-0.11</td>\n",
       "      <td>0</td>\n",
       "      <td>2016-01-05</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.9</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-0.9</td>\n",
       "      <td>0</td>\n",
       "      <td>Kepler</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>KIC 5437945</td>\n",
       "      <td>b</td>\n",
       "      <td>KIC 5437945 b</td>\n",
       "      <td>Transit</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>440.7813</td>\n",
       "      <td>0.00563</td>\n",
       "      <td>-0.00577</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>89.904</td>\n",
       "      <td>0.066</td>\n",
       "      <td>-0.086</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.571</td>\n",
       "      <td>0.143</td>\n",
       "      <td>-0.143</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>19h13m53.97s</td>\n",
       "      <td>288.474857</td>\n",
       "      <td>+40d39m04.9s</td>\n",
       "      <td>40.651357</td>\n",
       "      <td>1322.48</td>\n",
       "      <td>29.86</td>\n",
       "      <td>-29.86</td>\n",
       "      <td>0</td>\n",
       "      <td>1322.48</td>\n",
       "      <td>29.86</td>\n",
       "      <td>-29.86</td>\n",
       "      <td>0.0</td>\n",
       "      <td>13.771</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>Kepler-band</td>\n",
       "      <td>13.751</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6340.0</td>\n",
       "      <td>176.0</td>\n",
       "      <td>-199.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.07</td>\n",
       "      <td>0.17</td>\n",
       "      <td>-0.17</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.24</td>\n",
       "      <td>0.29</td>\n",
       "      <td>-0.29</td>\n",
       "      <td>0</td>\n",
       "      <td>2016-01-05</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.4</td>\n",
       "      <td>1.6</td>\n",
       "      <td>-1.6</td>\n",
       "      <td>0</td>\n",
       "      <td>Kepler</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>KIC 5951458</td>\n",
       "      <td>b</td>\n",
       "      <td>KIC 5951458 b</td>\n",
       "      <td>Transit</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1320.1000</td>\n",
       "      <td>12401.80000</td>\n",
       "      <td>-152.50000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>89.799</td>\n",
       "      <td>0.090</td>\n",
       "      <td>-0.120</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.589</td>\n",
       "      <td>2.346</td>\n",
       "      <td>-0.375</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>19h15m57.98s</td>\n",
       "      <td>288.991582</td>\n",
       "      <td>+41d13m22.9s</td>\n",
       "      <td>41.223038</td>\n",
       "      <td>758.78</td>\n",
       "      <td>12.71</td>\n",
       "      <td>-12.71</td>\n",
       "      <td>0</td>\n",
       "      <td>758.78</td>\n",
       "      <td>12.71</td>\n",
       "      <td>-12.71</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12.713</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>Kepler-band</td>\n",
       "      <td>12.688</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6258.0</td>\n",
       "      <td>170.0</td>\n",
       "      <td>-183.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.98</td>\n",
       "      <td>0.21</td>\n",
       "      <td>-0.21</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.52</td>\n",
       "      <td>0.82</td>\n",
       "      <td>-0.82</td>\n",
       "      <td>0</td>\n",
       "      <td>2016-01-05</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.6</td>\n",
       "      <td>26.3</td>\n",
       "      <td>-4.2</td>\n",
       "      <td>0</td>\n",
       "      <td>Kepler</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>KOI-7892</td>\n",
       "      <td>b</td>\n",
       "      <td>KIC 8540376 b</td>\n",
       "      <td>Transit</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>31.8099</td>\n",
       "      <td>0.00919</td>\n",
       "      <td>-0.00933</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>89.300</td>\n",
       "      <td>0.490</td>\n",
       "      <td>-0.720</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.366</td>\n",
       "      <td>0.196</td>\n",
       "      <td>-0.170</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>18h49m30.61s</td>\n",
       "      <td>282.377530</td>\n",
       "      <td>+44d41m40.5s</td>\n",
       "      <td>44.694592</td>\n",
       "      <td>1106.37</td>\n",
       "      <td>23.26</td>\n",
       "      <td>-23.26</td>\n",
       "      <td>0</td>\n",
       "      <td>1106.37</td>\n",
       "      <td>23.26</td>\n",
       "      <td>-23.26</td>\n",
       "      <td>0.0</td>\n",
       "      <td>14.294</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>Kepler-band</td>\n",
       "      <td>14.217</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6474.0</td>\n",
       "      <td>178.0</td>\n",
       "      <td>-267.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.04</td>\n",
       "      <td>0.20</td>\n",
       "      <td>-0.20</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.26</td>\n",
       "      <td>0.56</td>\n",
       "      <td>-0.56</td>\n",
       "      <td>0</td>\n",
       "      <td>2016-01-05</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.1</td>\n",
       "      <td>2.2</td>\n",
       "      <td>-1.9</td>\n",
       "      <td>0</td>\n",
       "      <td>Kepler</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    pl_hostname pl_letter         pl_name pl_discmethod  pl_controvflag  \\\n",
       "0  KIC 10525077         b  KIC 10525077 b       Transit               0   \n",
       "1   KIC 3558849         b   KIC 3558849 b       Transit               0   \n",
       "2   KIC 5437945         b   KIC 5437945 b       Transit               0   \n",
       "3   KIC 5951458         b   KIC 5951458 b       Transit               0   \n",
       "4      KOI-7892         b   KIC 8540376 b       Transit               0   \n",
       "\n",
       "   pl_pnum  pl_orbper  pl_orbpererr1  pl_orbpererr2  pl_orbperlim  pl_orbsmax  \\\n",
       "0        1   854.0830        0.01628       -0.01697           0.0         NaN   \n",
       "1        1  1322.3000      386.10000      -11.20000           0.0         NaN   \n",
       "2        2   440.7813        0.00563       -0.00577           0.0         NaN   \n",
       "3        1  1320.1000    12401.80000     -152.50000           0.0         NaN   \n",
       "4        2    31.8099        0.00919       -0.00933           0.0         NaN   \n",
       "\n",
       "   pl_orbsmaxerr1  pl_orbsmaxerr2  pl_orbsmaxlim  pl_orbeccen  \\\n",
       "0             NaN             NaN            NaN          NaN   \n",
       "1             NaN             NaN            NaN          NaN   \n",
       "2             NaN             NaN            NaN          NaN   \n",
       "3             NaN             NaN            NaN          NaN   \n",
       "4             NaN             NaN            NaN          NaN   \n",
       "\n",
       "   pl_orbeccenerr1  pl_orbeccenerr2  pl_orbeccenlim  pl_orbincl  \\\n",
       "0              NaN              NaN             NaN      89.861   \n",
       "1              NaN              NaN             NaN      89.973   \n",
       "2              NaN              NaN             NaN      89.904   \n",
       "3              NaN              NaN             NaN      89.799   \n",
       "4              NaN              NaN             NaN      89.300   \n",
       "\n",
       "   pl_orbinclerr1  pl_orbinclerr2  pl_orbincllim  pl_bmassj  pl_bmassjerr1  \\\n",
       "0           0.096          -0.098            0.0        NaN            NaN   \n",
       "1           0.023          -0.031            0.0        NaN            NaN   \n",
       "2           0.066          -0.086            0.0        NaN            NaN   \n",
       "3           0.090          -0.120            0.0        NaN            NaN   \n",
       "4           0.490          -0.720            0.0        NaN            NaN   \n",
       "\n",
       "   pl_bmassjerr2  pl_bmassjlim pl_bmassprov  pl_radj  pl_radjerr1  \\\n",
       "0            NaN           NaN          NaN    0.491        0.080   \n",
       "1            NaN           NaN          NaN    0.616        0.089   \n",
       "2            NaN           NaN          NaN    0.571        0.143   \n",
       "3            NaN           NaN          NaN    0.589        2.346   \n",
       "4            NaN           NaN          NaN    0.366        0.196   \n",
       "\n",
       "   pl_radjerr2  pl_radjlim  pl_dens  pl_denserr1  pl_denserr2  pl_denslim  \\\n",
       "0       -0.071           0      NaN          NaN          NaN         NaN   \n",
       "1       -0.080           0      NaN          NaN          NaN         NaN   \n",
       "2       -0.143           0      NaN          NaN          NaN         NaN   \n",
       "3       -0.375           0      NaN          NaN          NaN         NaN   \n",
       "4       -0.170           0      NaN          NaN          NaN         NaN   \n",
       "\n",
       "   pl_ttvflag  pl_kepflag  pl_k2flag  pl_nnotes        ra_str          ra  \\\n",
       "0           0           1          0          1  19h09m30.74s  287.378077   \n",
       "1           0           1          0          0  19h39m47.96s  294.949847   \n",
       "2           0           1          0          1  19h13m53.97s  288.474857   \n",
       "3           0           1          0          0  19h15m57.98s  288.991582   \n",
       "4           0           1          0          0  18h49m30.61s  282.377530   \n",
       "\n",
       "        dec_str        dec  st_dist  st_disterr1  st_disterr2  st_distlim  \\\n",
       "0  +47d46m16.3s  47.771187  1525.31        58.45       -58.45           0   \n",
       "1  +38d36m18.7s  38.605197  1258.75        35.41       -35.41           0   \n",
       "2  +40d39m04.9s  40.651357  1322.48        29.86       -29.86           0   \n",
       "3  +41d13m22.9s  41.223038   758.78        12.71       -12.71           0   \n",
       "4  +44d41m40.5s  44.694592  1106.37        23.26       -23.26           0   \n",
       "\n",
       "   gaia_dist  gaia_disterr1  gaia_disterr2  gaia_distlim  st_optmag  \\\n",
       "0    1525.31          58.45         -58.45           0.0     15.355   \n",
       "1    1258.75          35.41         -35.41           0.0     14.218   \n",
       "2    1322.48          29.86         -29.86           0.0     13.771   \n",
       "3     758.78          12.71         -12.71           0.0     12.713   \n",
       "4    1106.37          23.26         -23.26           0.0     14.294   \n",
       "\n",
       "   st_optmagerr  st_optmaglim   st_optband  gaia_gmag  gaia_gmagerr  \\\n",
       "0           NaN             0  Kepler-band     15.304           NaN   \n",
       "1           NaN             0  Kepler-band     14.167           NaN   \n",
       "2           NaN             0  Kepler-band     13.751           NaN   \n",
       "3           NaN             0  Kepler-band     12.688           NaN   \n",
       "4           NaN             0  Kepler-band     14.217           NaN   \n",
       "\n",
       "   gaia_gmaglim  st_teff  st_tefferr1  st_tefferr2  st_tefflim  st_mass  \\\n",
       "0           0.0   6091.0        164.0       -213.0         0.0     1.01   \n",
       "1           0.0   6175.0        168.0       -194.0         0.0     0.98   \n",
       "2           0.0   6340.0        176.0       -199.0         0.0     1.07   \n",
       "3           0.0   6258.0        170.0       -183.0         0.0     0.98   \n",
       "4           0.0   6474.0        178.0       -267.0         0.0     1.04   \n",
       "\n",
       "   st_masserr1  st_masserr2  st_masslim  st_rad  st_raderr1  st_raderr2  \\\n",
       "0         0.12        -0.12         0.0    1.01        0.10       -0.10   \n",
       "1         0.11        -0.11         0.0    1.01        0.11       -0.11   \n",
       "2         0.17        -0.17         0.0    1.24        0.29       -0.29   \n",
       "3         0.21        -0.21         0.0    1.52        0.82       -0.82   \n",
       "4         0.20        -0.20         0.0    1.26        0.56       -0.56   \n",
       "\n",
       "   st_radlim   rowupdate  pl_masse  pl_masseerr1  pl_masseerr2  pl_masselim  \\\n",
       "0          0  2016-01-05       NaN           NaN           NaN          NaN   \n",
       "1          0  2016-01-05       NaN           NaN           NaN          NaN   \n",
       "2          0  2016-01-05       NaN           NaN           NaN          NaN   \n",
       "3          0  2016-01-05       NaN           NaN           NaN          NaN   \n",
       "4          0  2016-01-05       NaN           NaN           NaN          NaN   \n",
       "\n",
       "   pl_rade  pl_radeerr1  pl_radeerr2  pl_radelim pl_facility  \n",
       "0      5.5          0.9         -0.8           0      Kepler  \n",
       "1      6.9          1.0         -0.9           0      Kepler  \n",
       "2      6.4          1.6         -1.6           0      Kepler  \n",
       "3      6.6         26.3         -4.2           0      Kepler  \n",
       "4      4.1          2.2         -1.9           0      Kepler  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "kepler_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "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": [
    "# Make a histogram of planet's in units of Earth radius\n",
    "plt.hist(kepler_data['pl_rade'], bins=10) # Plot the histogram\n",
    "\n",
    "# Label the axes\n",
    "plt.xlabel('Radius [R$_\\oplus$]', fontsize=14)\n",
    "plt.ylabel('N', fontsize=14)\n",
    "\n",
    "# Show the plot\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "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": [
    "# Create bins that are uniformly-sized in log space\n",
    "log_bins = np.logspace(np.log10(0.3), np.log10(20), 50)\n",
    "plt.hist(kepler_data['pl_rade'], bins = log_bins)\n",
    "\n",
    "# Log scale on the x-axis\n",
    "plt.xscale('log')\n",
    "\n",
    "# Label the axes\n",
    "plt.xlabel('Radius [R$_\\oplus$]', fontsize=14) # More LaTex. \\oplus gives us the symbol for Earth\n",
    "plt.ylabel('N', fontsize=14)\n",
    "\n",
    "# Show the plot\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It looks like the distribution of planets has some sort of **bimodality** between about 1 and 2 Earth masses. Let's zoom in on that area by **restricting our x-axis limits**."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "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": [
    "plt.hist(kepler_data['pl_rade'], bins = log_bins) # Using the same bins as above\n",
    "\n",
    "# Let's zoom in on the distribution of planet radii in this region\n",
    "plt.xlim([1., 5]) # Units of Earth radius\n",
    "\n",
    "# Same plot housekeeping as above\n",
    "# -------------------------------\n",
    "# Log scale on the x-axis\n",
    "plt.xscale('log')\n",
    "\n",
    "# Label the axes\n",
    "plt.xlabel('Radius [R$_\\oplus$]', fontsize=14) # More LaTex. \\oplus gives us the symbol for Earth\n",
    "plt.ylabel('N', fontsize=14)\n",
    "\n",
    "# Show the plot\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Are there **any notable features** in this distribution of planets by radius? Can you relate to something you learnt yesterday?"
   ]
  }
 ],
 "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
}