coral_names_cleanup.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Coral Names Cleanup\n",
    "\n",
    "I have multiple csv files containing the coral name and the corresponding file name.  I need to sort these into groups by type of coral so that I can create directories for each of the coral types for model training."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import os\n",
    "import re"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "pd.set_option('display.max_rows', None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "filepath = './coral_names'\n",
    "filelist = os.listdir(filepath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "29"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(filelist)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "dfs = []\n",
    "for file in filelist:\n",
    "    names = pd.read_csv(os.path.join(filepath, file), delimiter='|', header=0, names=['coral_name', 'filename'])\n",
    "    names['file'] = re.search(r\"(?<=files\\_)(.*)(?=\\.csv)\", file)[0]\n",
    "    dfs.append(names)\n",
    "    \n",
    "df = pd.concat(dfs, ignore_index=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": true
   },
   "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>coral_name</th>\n",
       "      <th>filename</th>\n",
       "      <th>file</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>56054</th>\n",
       "      <td>Orange Rainbow Ricordea Mushroom</td>\n",
       "      <td>https://www.reef2reef.com/proxy.php?image=http...</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56055</th>\n",
       "      <td>Orange Rainbow Ricordea Mushroom</td>\n",
       "      <td>https://www.reef2reef.com/proxy.php?image=http...</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56056</th>\n",
       "      <td>Orange Rainbow Ricordea Mushroom</td>\n",
       "      <td>https://www.reef2reef.com/proxy.php?image=http...</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56057</th>\n",
       "      <td>Sour Willy Ricordea Mushroom</td>\n",
       "      <td>https://www.reef2reef.com/proxy.php?image=http...</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56058</th>\n",
       "      <td>Lime Willy Ricordea Mushroom</td>\n",
       "      <td>https://www.reef2reef.com/proxy.php?image=http...</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                             coral_name  \\\n",
       "56054  Orange Rainbow Ricordea Mushroom   \n",
       "56055  Orange Rainbow Ricordea Mushroom   \n",
       "56056  Orange Rainbow Ricordea Mushroom   \n",
       "56057      Sour Willy Ricordea Mushroom   \n",
       "56058      Lime Willy Ricordea Mushroom   \n",
       "\n",
       "                                                filename file  \n",
       "56054  https://www.reef2reef.com/proxy.php?image=http...   13  \n",
       "56055  https://www.reef2reef.com/proxy.php?image=http...   13  \n",
       "56056  https://www.reef2reef.com/proxy.php?image=http...   13  \n",
       "56057  https://www.reef2reef.com/proxy.php?image=http...   13  \n",
       "56058  https://www.reef2reef.com/proxy.php?image=http...   13  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.tail(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# from the filename, grab everything starting with the last %2F\n",
    "df['shortfilename'] = df['filename'].str.extract(r'(\\%2F(?:.(?!\\%2F))+$)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# grab everything after %2F up through .jpg, which is the name of the file I am looking for\n",
    "df['shortfilename'] = df['shortfilename'].str.extract(r'(?<=\\%2F)(.+\\.jpg)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# remove notations for non-WYSIWYG (what you see is what you get)\n",
    "df['coral_name'] = df['coral_name'].str.replace(' - (NON-WYSIWYG)', '', regex=False)\n",
    "df['coral_name'] = df['coral_name'].str.replace(' - MED (NON-WYSIWYG)', '', regex=False)\n",
    "df['coral_name'] = df['coral_name'].str.replace(' - SM (NON-WYSIWYG)', '', regex=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Begin mapping to coral types to define directory structure.\n",
    "\n",
    "For more details on the families of corals listed below, please see https://marinespecies.org/aphia.php?p=search. For a summary of stony corals, please see https://biophysics.sbg.ac.at/coral/family.htm.\n",
    "\n",
    "Note that some situations will require special attention to order of operations.  For example, I cannot use `contains` with `acropora` without first capturing `anacropora`.\n",
    "\n",
    "There are also numerous spelling errors that need to be corrected.  For example, `Ausssie Lord` versus `Aussie Lord`.\n",
    "\n",
    "STILL TO DO\n",
    "- Multiple corals on one frag, such as `Pulsing Xenia and Favia Combo`\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# zoas, palys, and anemones\n",
    "df['coral_type'] = np.where(df['coral_name'].str.contains('zoanthid', case=False), 'Zoanthid', None)\n",
    "\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('dragon eye combo', case=False), \n",
    "    'Zoanthid', df['coral_type']\n",
    ")\n",
    "\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('palythoa', case=False), \n",
    "    'Palythoa', df['coral_type']\n",
    ")\n",
    "\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('anemone', case=False), \n",
    "    'Anemone', df['coral_type']\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# mushrooms\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('rhodactis', case=False), \n",
    "    'Rhodactis', df['coral_type']\n",
    ")\n",
    "\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('ricordea', case=False), \n",
    "    'Ricordea', df['coral_type']\n",
    ")\n",
    "\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('yuma', case=False), \n",
    "    'Yuma', df['coral_type']\n",
    ")\n",
    "\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('mushroom', case=False), \n",
    "    'Mushroom', df['coral_type']\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# xeniidae\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('anthelia|anthellia', case=False), \n",
    "    'Anthelia', df['coral_type']\n",
    ")\n",
    "\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('cespitularia', case=False), \n",
    "    'Cespitularia', df['coral_type']\n",
    ")\n",
    "\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('efflatounaria', case=False), \n",
    "    'Efflatounaria', df['coral_type']\n",
    ")\n",
    "\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('sympodium', case=False), \n",
    "    'Sympodium', df['coral_type']\n",
    ")\n",
    "\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('pulsing xenia', case=False), \n",
    "    'Pulsing Xenia', df['coral_type']\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "# other soft corals\n",
    "\n",
    "# alcyoniidae\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('colt', case=False), \n",
    "    'Colt', df['coral_type']\n",
    ")\n",
    "\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('leather|lobophytum', case=False), \n",
    "    'Leather', df['coral_type']\n",
    ")\n",
    "\n",
    "# tubiporidae\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('pipe organ', case=False), \n",
    "    'Pipe Organ', df['coral_type']\n",
    ")\n",
    "\n",
    "# clavulariidae\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('star polyp', case=False), \n",
    "    'Star Polyp', df['coral_type']\n",
    ")\n",
    "\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('GSP', case=True), \n",
    "    'Star Polyp', df['coral_type']\n",
    ")\n",
    "\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('clove (?:combo )?polyp', case=False), \n",
    "    'Clove Polyp', df['coral_type']\n",
    ")\n",
    "\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('daisy polyp', case=False), \n",
    "    'Daisy Polyp', df['coral_type']\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "# euphyllia\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('frogspawn', case=False), \n",
    "    'Frogspawn', df['coral_type']\n",
    ")\n",
    "\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.endswith('Frog'), \n",
    "    'Frogspawn', df['coral_type']\n",
    ")\n",
    "\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('frammer', case=False), \n",
    "    'Frammer', df['coral_type']\n",
    ")\n",
    "\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('cristata', case=False), \n",
    "    'Cristata', df['coral_type']\n",
    ")\n",
    "\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.endswith('Torch'), \n",
    "    'Torch', df['coral_type']\n",
    ")\n",
    "\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('torch xl', case=False), \n",
    "    'Torch', df['coral_type']\n",
    ")\n",
    "\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.endswith('Hammer'), \n",
    "    'Hammer', df['coral_type']\n",
    ")\n",
    "\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.endswith('Hammers'), \n",
    "    'Hammer', df['coral_type']\n",
    ")\n",
    "\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('Hammer - 2 Heads|Hammer - 3 Heads', case=False), \n",
    "    'Hammer', df['coral_type']\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "# other euphyllidae\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('bubble coral', case=False), # plerogyra\n",
    "    'Bubble', df['coral_type']\n",
    ")\n",
    "\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('elegance', case=False), \n",
    "    'Elegance', df['coral_type']\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "# acroporidae\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('anacropora', case=False), \n",
    "    'Anacropora', df['coral_type']\n",
    ")\n",
    "\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('astreopora', case=False), \n",
    "    'Astreopora', df['coral_type']\n",
    ")\n",
    "\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('montipora|montoipora', case=False), \n",
    "    'Montipora', df['coral_type']\n",
    ")\n",
    "\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.endswith('Digitata'), \n",
    "    'Montipora', df['coral_type']\n",
    ")\n",
    "\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.endswith('Acropora'), \n",
    "    'Acropora', df['coral_type']\n",
    ")\n",
    "\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.endswith('Acrpopora'), \n",
    "    'Acropora', df['coral_type']\n",
    ")\n",
    "\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.endswith('Acro'), \n",
    "    'Acropora', df['coral_type']\n",
    ")\n",
    "\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('acroproa', case=False), \n",
    "    'Acropora', df['coral_type']\n",
    ")\n",
    "\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.endswith('Mirabilis'), \n",
    "    'Acropora', df['coral_type']\n",
    ")\n",
    "\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.endswith('Acropora - New Release!'), \n",
    "    'Acropora', df['coral_type']\n",
    ")\n",
    "\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.endswith('Acropora - New Release'), \n",
    "    'Acropora', df['coral_type']\n",
    ")\n",
    "\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.endswith('Acropora '), \n",
    "    'Acropora', df['coral_type']\n",
    ")\n",
    "\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('Acropora - XL|Acropora - LG|blue stag|Acropora LG|Acropora XL', case=False), \n",
    "    'Acropora', df['coral_type']\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "# astrocoeniidae\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('stylocoeniella', case=False), \n",
    "    'Stylocoeniella', df['coral_type']\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "# pocilloporidae\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('pocillopora|pocillipora', case=False), \n",
    "    'Pocillopora', df['coral_type']\n",
    ")\n",
    "\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('stylophora', case=False), \n",
    "    'Stylophora', df['coral_type']\n",
    ")\n",
    "\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('birdnest|birdsnest', case=False), \n",
    "    'Seriatopora', df['coral_type']\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "# oculinidae\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('galaxea', case=False), \n",
    "    'Galaxea', df['coral_type']\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "# meandrinidae\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "# siderastreidae\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('psammocora|pssamacora', case=False), \n",
    "    'Psammocora', df['coral_type']\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "# agariciidae\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('pavona', case=False), \n",
    "    'Pavona', df['coral_type']\n",
    ")\n",
    "\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('leptoseris', case=False), \n",
    "    'Leptoseris', df['coral_type']\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "# fungiidae\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('plate coral|diaseris', case=False), \n",
    "    'Plate', df['coral_type']\n",
    ")\n",
    "\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('lithophyllon', case=False), \n",
    "    'Lithophyllon', df['coral_type']\n",
    ")\n",
    "\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('tongue coral', case=False), \n",
    "    'Tongue', df['coral_type']\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "# pectiniidae\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('chalice|mycedium', case=False), \n",
    "    'Chalice', df['coral_type']\n",
    ")\n",
    "\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('pectinia', case=False), \n",
    "    'Pectinia', df['coral_type']\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "# merulinidae\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('hydnophora', case=False), \n",
    "    'Hydnophora', df['coral_type']\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "# dendrophylliidae\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('turbinaria', case=False), \n",
    "    'Turbinaria', df['coral_type']\n",
    ")\n",
    "\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('duncan', case=False), # duncanopsammia\n",
    "    'Duncan', df['coral_type']\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "# caryophylliidae\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "# mussidae\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('blasto', case=False), \n",
    "    'Blastomussa', df['coral_type']\n",
    ")\n",
    "\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('micromussa', case=False), \n",
    "    'Micromussa', df['coral_type']\n",
    ")\n",
    "\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.endswith('Echinata'), # acanthastrea echinata\n",
    "    'Echinata', df['coral_type']\n",
    ")\n",
    "\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.endswith('Echinata '),\n",
    "    'Echinata', df['coral_type']\n",
    ")\n",
    "\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('lobophyllia', case=False), \n",
    "    'Lobophyllia', df['coral_type']\n",
    ")\n",
    "\n",
    "# formerly known as symphyllia\n",
    "# now australophyllia wilsoni\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('symphyllia|wilsoni', case=False), \n",
    "    'Wilsoni', df['coral_type']\n",
    ")\n",
    "\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('cynarina', case=False), \n",
    "    'Cynarina', df['coral_type']\n",
    ")\n",
    "\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('scolymia', case=False), \n",
    "    'Scolymia', df['coral_type']\n",
    ")\n",
    "\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('acanthophyllia', case=False), \n",
    "    'Acanthophyllia', df['coral_type']\n",
    ")\n",
    "\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('bowerbanki', case=False), \n",
    "    'Bowerbanki', df['coral_type']\n",
    ")\n",
    "\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('australomussa', case=False), \n",
    "    'Australomussa', df['coral_type']\n",
    ")\n",
    "\n",
    "# micromussa lordhowensis aka acan lord aka aussie lord aka indo lord\n",
    "# reclassified from acanthastrea to micromussa in 2016\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('aussie lord', case=False), \n",
    "    'Lord', df['coral_type']\n",
    ")\n",
    "\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('aussoe|ausssie', case=False), \n",
    "    'Lord', df['coral_type']\n",
    ")\n",
    "\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('indo lord|stone lord', case=False), \n",
    "    'Lord', df['coral_type']\n",
    ")\n",
    "\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('bubblegum lord|cheesecake lord|cotton candy lord|solar flare lord', case=False), \n",
    "    'Lord', df['coral_type']\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "# faviidae\n",
    "\n",
    "# entratentacular budding\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('plesiastrea', case=False), \n",
    "    'Plesiastrea', df['coral_type']\n",
    ")\n",
    "\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('leptastrea', case=False), \n",
    "    'Leptastrea', df['coral_type']\n",
    ")\n",
    "\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('cyphastrea', case=False), \n",
    "    'Cyphastrea', df['coral_type']\n",
    ")\n",
    "\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.endswith('Candy Cane'),\n",
    "    'Caulastrea', df['coral_type']\n",
    ")\n",
    "\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.endswith('Candy Canes'),\n",
    "    'Caulastrea', df['coral_type']\n",
    ")\n",
    "\n",
    "# intratentacular budding\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.endswith('Trumpet'),\n",
    "    'Caulastrea', df['coral_type']\n",
    ")\n",
    "\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('favites', case=False), \n",
    "    'Favites', df['coral_type']\n",
    ")\n",
    "\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.endswith('War Coral'), \n",
    "    'Favites', df['coral_type']\n",
    ")\n",
    "\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('goniastrea', case=False), \n",
    "    'Goniastrea', df['coral_type']\n",
    ")\n",
    "\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('platygyra|platygra|playtygra', case=False), \n",
    "    'Platygyra', df['coral_type']\n",
    ")\n",
    "\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('oulophyllia', case=False), \n",
    "    'Oulophyllia', df['coral_type']\n",
    ")\n",
    "\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('echinopora', case=False), \n",
    "    'Echinopora', df['coral_type']\n",
    ")\n",
    "\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('favia', case=False), \n",
    "    'Favia', df['coral_type']\n",
    ")\n",
    "\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('golden goose favis', case=False), \n",
    "    'Favia', df['coral_type']\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "# trachyphylliidae\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('trachyphyllia|trachyphllia', case=False), \n",
    "    'Trachyphyllia', df['coral_type']\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "# poritidae\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('goniopora', case=False), \n",
    "    'Goniopora', df['coral_type']\n",
    ")\n",
    "\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('alveopora', case=False), \n",
    "    'Alveopora', df['coral_type']\n",
    ")\n",
    "\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_type'].isna() \n",
    "    & df['coral_name'].str.contains('porites', case=False), \n",
    "    'Porites', df['coral_type']\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "# manual cleanup for bad names, such as \"$79\" or \"(CLICK HERE TO BUY!)\"\n",
    "df.iloc[0,4] = 'Zoanthid'\n",
    "df.iloc[1,4] = 'Zoanthid'\n",
    "df.iloc[2,4] = 'Zoanthid'\n",
    "df.iloc[3,4] = 'Zoanthid'\n",
    "df.iloc[4,4] = 'Zoanthid'\n",
    "df.iloc[5,4] = 'Zoanthid'\n",
    "df.iloc[6,4] = 'Zoanthid'\n",
    "df.iloc[7,4] = 'Zoanthid'\n",
    "df.iloc[8,4] = 'Zoanthid'\n",
    "df.iloc[9,4] = 'Zoanthid'\n",
    "df.iloc[10,4] = 'Zoanthid'\n",
    "df.iloc[11,4] = 'Zoanthid'\n",
    "df.iloc[12,4] = 'Zoanthid'\n",
    "df.iloc[13,4] = 'Zoanthid'\n",
    "df.iloc[14,4] = 'Zoanthid'\n",
    "df.iloc[316,4] = 'Delete'\n",
    "df.iloc[317,4] = 'Zoanthid'\n",
    "df.iloc[318,4] = 'Zoanthid'\n",
    "df.iloc[319,4] = 'Zoanthid'\n",
    "df.iloc[320,4] = 'Zoanthid'\n",
    "df.iloc[321,4] = 'Zoanthid'\n",
    "df.iloc[322,4] = 'Zoanthid'\n",
    "df.iloc[323,4] = 'Delete'\n",
    "df.iloc[324,4] = 'Zoanthid'\n",
    "df.iloc[325,4] = 'Zoanthid'\n",
    "df.iloc[326,4] = 'Zoanthid'\n",
    "df.iloc[327,4] = 'Zoanthid'\n",
    "df.iloc[328,4] = 'Zoanthid'\n",
    "df.iloc[329,4] = 'Zoanthid'\n",
    "df.iloc[330,4] = 'Zoanthid'\n",
    "df.iloc[331,4] = 'Zoanthid'\n",
    "df.iloc[332,4] = 'Zoanthid'\n",
    "df.iloc[333,4] = 'Zoanthid'\n",
    "df.iloc[334,4] = 'Zoanthid'\n",
    "df.iloc[335,4] = 'Zoanthid'\n",
    "df.iloc[336,4] = 'Zoanthid'\n",
    "df.iloc[337,4] = 'Zoanthid'\n",
    "df.iloc[338,4] = 'Zoanthid'\n",
    "df.iloc[339,4] = 'Zoanthid'\n",
    "df.iloc[340,4] = 'Zoanthid'\n",
    "df.iloc[341,4] = 'Zoanthid'\n",
    "df.iloc[342,4] = 'Zoanthid'\n",
    "df.iloc[343,4] = 'Palythoa'\n",
    "df.iloc[344,4] = 'Zoanthid'\n",
    "df.iloc[345,4] = 'Zoanthid'\n",
    "df.iloc[618,4] = 'Delete'\n",
    "df.iloc[1108,4] = 'Delete'\n",
    "df.iloc[1321,4] = 'Delete'\n",
    "df.iloc[1322,4] = 'Delete'\n",
    "df.iloc[1323,4] = 'Delete'\n",
    "df.iloc[1324,4] = 'Delete'\n",
    "df.iloc[1325,4] = 'Delete'\n",
    "df.iloc[1326,4] = 'Platygyra'\n",
    "df.iloc[1327,4] = 'Cyphastrea'\n",
    "df.iloc[1328,4] = 'Favia'\n",
    "df.iloc[1329,4] = 'Alveopora'\n",
    "df.iloc[1330,4] = 'Favia'\n",
    "df.iloc[1637,4] = 'Delete'\n",
    "df.iloc[1638,4] = 'Zoanthid'\n",
    "df.iloc[1639,4] = 'Zoanthid'\n",
    "df.iloc[1640,4] = 'Zoanthid'\n",
    "df.iloc[1641,4] = 'Delete'\n",
    "df.iloc[1642,4] = 'Zoanthid'\n",
    "df.iloc[2687,4] = 'Delete'\n",
    "df.iloc[2736,4] = 'Delete'\n",
    "df.iloc[5495,4] = 'Delete'\n",
    "df.iloc[5496,4] = 'Delete'\n",
    "df.iloc[5497,4] = 'Delete'\n",
    "df.iloc[5498,4] = 'Delete'\n",
    "df.iloc[5499,4] = 'Delete'\n",
    "df.iloc[5500,4] = 'Delete'\n",
    "df.iloc[14973,4] = 'Zoanthid'\n",
    "df.iloc[14974,4] = 'Acropora'\n",
    "df.iloc[14975,4] = 'Blastomussa'\n",
    "df.iloc[14976,4] = 'Pipe Organ'\n",
    "df.iloc[14977,4] = 'Lord'\n",
    "df.iloc[14978,4] = 'Goniastrea'\n",
    "df.iloc[14979,4] = 'Hammer'\n",
    "df.iloc[14980,4] = 'Ricordea'\n",
    "df.iloc[14981,4] = 'Lord'\n",
    "df.iloc[22998,4] = 'Montipora'\n",
    "df.iloc[22999,4] = 'Ricordea'\n",
    "df.iloc[23000,4] = 'Zoanthid'\n",
    "df.iloc[23001,4] = 'Caulastrea'\n",
    "df.iloc[23002,4] = 'Platygyra'\n",
    "df.iloc[24276,4] = 'Lord'\n",
    "df.iloc[24277,4] = 'Duncan'\n",
    "df.iloc[24278,4] = 'Chalice'\n",
    "df.iloc[24279,4] = 'Zoanthid'\n",
    "df.iloc[24280,4] = 'Seriatopora'\n",
    "df.iloc[26490,4] = 'Montipora'\n",
    "df.iloc[26491,4] = 'Ricordea'\n",
    "df.iloc[26492,4] = 'Zoanthid'\n",
    "df.iloc[26493,4] = 'Caulastrea'\n",
    "df.iloc[26494,4] = 'Platygyra'\n",
    "df.iloc[26596,4] = 'Delete'\n",
    "df.iloc[26810,4] = 'Delete'\n",
    "df.iloc[26818,4] = 'Montipora'\n",
    "df.iloc[27575,4] = 'Torch'\n",
    "df.iloc[27576,4] = 'Ricordea'\n",
    "df.iloc[27842,4] = 'Lord'\n",
    "df.iloc[27843,4] = 'Duncan'\n",
    "df.iloc[27844,4] = 'Chalice'\n",
    "df.iloc[27845,4] = 'Zoanthid'\n",
    "df.iloc[27846,4] = 'Seriatopora'\n",
    "df.iloc[28321,4] = 'Delete'\n",
    "df.iloc[28729,4] = 'Delete'\n",
    "df.iloc[28730,4] = 'Goniastrea'\n",
    "df.iloc[28731,4] = 'Favia'\n",
    "df.iloc[28732,4] = 'Favia'\n",
    "df.iloc[28733,4] = 'Zoanthid'\n",
    "df.iloc[28734,4] = 'Lord'\n",
    "df.iloc[28735,4] = 'Ricordea'\n",
    "df.iloc[28743,4] = 'Delete'\n",
    "df.iloc[28933,4] = 'Chalice'\n",
    "df.iloc[28934,4] = 'Favia'\n",
    "df.iloc[28935,4] = 'Favia'\n",
    "df.iloc[28936,4] = 'Zoanthid'\n",
    "df.iloc[28937,4] = 'Zoanthid'\n",
    "df.iloc[28938,4] = 'Echinata'\n",
    "df.iloc[29063,4] = 'Acropora'\n",
    "df.iloc[32554,4] = 'Favia'\n",
    "df.iloc[32555,4] = 'Favia'\n",
    "df.iloc[32556,4] = 'Favia'\n",
    "df.iloc[32557,4] = 'Montipora'\n",
    "df.iloc[33363,4] = 'Delete'\n",
    "df.iloc[33364,4] = 'Delete'\n",
    "df.iloc[33365,4] = 'Delete'\n",
    "df.iloc[33366,4] = 'Delete'\n",
    "df.iloc[33367,4] = 'Delete'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "# for all the \"Mystery\" corals without pictures, correct into the \"Delete\" category\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_name'].str.contains('mystery', case=False), \n",
    "    'Delete', df['coral_type']\n",
    ")\n",
    "# except for \"Mystery Machine Aussie Lord\", which needs to be \"Lord\"\n",
    "df['coral_type'] = np.where(\n",
    "    df['coral_name'].str.contains('mystery machine', case=False), \n",
    "    'Lord', df['coral_type']\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "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>coral_type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Tongue</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Elegance</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Australomussa</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Echinopora</th>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Frammer</th>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cynarina</th>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Efflatounaria</th>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Acanthophyllia</th>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Trachyphyllia</th>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cristata</th>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Oulophyllia</th>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Plesiastrea</th>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bubble</th>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Plate</th>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Colt</th>\n",
       "      <td>26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wilsoni</th>\n",
       "      <td>51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Scolymia</th>\n",
       "      <td>53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pectinia</th>\n",
       "      <td>56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sympodium</th>\n",
       "      <td>69</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lobophyllia</th>\n",
       "      <td>73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cespitularia</th>\n",
       "      <td>89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Yuma</th>\n",
       "      <td>92</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Daisy Polyp</th>\n",
       "      <td>99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pocillopora</th>\n",
       "      <td>128</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Galaxea</th>\n",
       "      <td>134</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Anacropora</th>\n",
       "      <td>140</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Anthelia</th>\n",
       "      <td>144</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Anemone</th>\n",
       "      <td>147</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Astreopora</th>\n",
       "      <td>154</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lithophyllon</th>\n",
       "      <td>202</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hydnophora</th>\n",
       "      <td>203</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pavona</th>\n",
       "      <td>203</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Alveopora</th>\n",
       "      <td>204</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Micromussa</th>\n",
       "      <td>222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Caulastrea</th>\n",
       "      <td>241</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Frogspawn</th>\n",
       "      <td>268</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Palythoa</th>\n",
       "      <td>278</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Porites</th>\n",
       "      <td>303</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Goniastrea</th>\n",
       "      <td>319</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pipe Organ</th>\n",
       "      <td>331</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Torch</th>\n",
       "      <td>376</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Duncan</th>\n",
       "      <td>408</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Stylophora</th>\n",
       "      <td>412</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Turbinaria</th>\n",
       "      <td>465</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Star Polyp</th>\n",
       "      <td>523</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Clove Polyp</th>\n",
       "      <td>525</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Delete</th>\n",
       "      <td>526</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Leather</th>\n",
       "      <td>553</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mushroom</th>\n",
       "      <td>575</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pulsing Xenia</th>\n",
       "      <td>623</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rhodactis</th>\n",
       "      <td>625</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Leptastrea</th>\n",
       "      <td>700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bowerbanki</th>\n",
       "      <td>729</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Psammocora</th>\n",
       "      <td>825</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Stylocoeniella</th>\n",
       "      <td>891</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hammer</th>\n",
       "      <td>899</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Echinata</th>\n",
       "      <td>939</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Leptoseris</th>\n",
       "      <td>942</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Blastomussa</th>\n",
       "      <td>998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Platygyra</th>\n",
       "      <td>1199</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Goniopora</th>\n",
       "      <td>1360</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Seriatopora</th>\n",
       "      <td>1433</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ricordea</th>\n",
       "      <td>1606</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Favites</th>\n",
       "      <td>2305</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cyphastrea</th>\n",
       "      <td>2365</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Chalice</th>\n",
       "      <td>2477</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lord</th>\n",
       "      <td>2513</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Favia</th>\n",
       "      <td>3528</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Montipora</th>\n",
       "      <td>3747</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Acropora</th>\n",
       "      <td>6557</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zoanthid</th>\n",
       "      <td>10040</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                coral_type\n",
       "Tongue                   1\n",
       "Elegance                 2\n",
       "Australomussa            2\n",
       "Echinopora               6\n",
       "Frammer                  7\n",
       "Cynarina                 9\n",
       "Efflatounaria            9\n",
       "Acanthophyllia          10\n",
       "Trachyphyllia           11\n",
       "Cristata                16\n",
       "Oulophyllia             23\n",
       "Plesiastrea             23\n",
       "Bubble                  23\n",
       "Plate                   24\n",
       "Colt                    26\n",
       "Wilsoni                 51\n",
       "Scolymia                53\n",
       "Pectinia                56\n",
       "Sympodium               69\n",
       "Lobophyllia             73\n",
       "Cespitularia            89\n",
       "Yuma                    92\n",
       "Daisy Polyp             99\n",
       "Pocillopora            128\n",
       "Galaxea                134\n",
       "Anacropora             140\n",
       "Anthelia               144\n",
       "Anemone                147\n",
       "Astreopora             154\n",
       "Lithophyllon           202\n",
       "Hydnophora             203\n",
       "Pavona                 203\n",
       "Alveopora              204\n",
       "Micromussa             222\n",
       "Caulastrea             241\n",
       "Frogspawn              268\n",
       "Palythoa               278\n",
       "Porites                303\n",
       "Goniastrea             319\n",
       "Pipe Organ             331\n",
       "Torch                  376\n",
       "Duncan                 408\n",
       "Stylophora             412\n",
       "Turbinaria             465\n",
       "Star Polyp             523\n",
       "Clove Polyp            525\n",
       "Delete                 526\n",
       "Leather                553\n",
       "Mushroom               575\n",
       "Pulsing Xenia          623\n",
       "Rhodactis              625\n",
       "Leptastrea             700\n",
       "Bowerbanki             729\n",
       "Psammocora             825\n",
       "Stylocoeniella         891\n",
       "Hammer                 899\n",
       "Echinata               939\n",
       "Leptoseris             942\n",
       "Blastomussa            998\n",
       "Platygyra             1199\n",
       "Goniopora             1360\n",
       "Seriatopora           1433\n",
       "Ricordea              1606\n",
       "Favites               2305\n",
       "Cyphastrea            2365\n",
       "Chalice               2477\n",
       "Lord                  2513\n",
       "Favia                 3528\n",
       "Montipora             3747\n",
       "Acropora              6557\n",
       "Zoanthid             10040"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['coral_type'].value_counts(dropna=False, ascending=True).to_frame()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "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>coral_name</th>\n",
       "      <th>filename</th>\n",
       "      <th>file</th>\n",
       "      <th>shortfilename</th>\n",
       "      <th>coral_type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>$79</td>\n",
       "      <td>https://www.reef2reef.com/proxy.php?image=http...</td>\n",
       "      <td>6</td>\n",
       "      <td>LSMAY-22-13-647.jpg</td>\n",
       "      <td>Zoanthid</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>$59</td>\n",
       "      <td>https://www.reef2reef.com/proxy.php?image=http...</td>\n",
       "      <td>6</td>\n",
       "      <td>LSMAY-30-64-151.jpg</td>\n",
       "      <td>Zoanthid</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>$29</td>\n",
       "      <td>https://www.reef2reef.com/proxy.php?image=http...</td>\n",
       "      <td>6</td>\n",
       "      <td>LSMAY-24-68-443.jpg</td>\n",
       "      <td>Zoanthid</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>$69</td>\n",
       "      <td>https://www.reef2reef.com/proxy.php?image=http...</td>\n",
       "      <td>6</td>\n",
       "      <td>LSMAY-24-84-814.jpg</td>\n",
       "      <td>Zoanthid</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>$119</td>\n",
       "      <td>https://www.reef2reef.com/proxy.php?image=http...</td>\n",
       "      <td>6</td>\n",
       "      <td>LSMAY-26-82-597.jpg</td>\n",
       "      <td>Zoanthid</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  coral_name                                           filename file  \\\n",
       "0        $79  https://www.reef2reef.com/proxy.php?image=http...    6   \n",
       "1        $59  https://www.reef2reef.com/proxy.php?image=http...    6   \n",
       "2        $29  https://www.reef2reef.com/proxy.php?image=http...    6   \n",
       "3        $69  https://www.reef2reef.com/proxy.php?image=http...    6   \n",
       "4       $119  https://www.reef2reef.com/proxy.php?image=http...    6   \n",
       "\n",
       "         shortfilename coral_type  \n",
       "0  LSMAY-22-13-647.jpg   Zoanthid  \n",
       "1  LSMAY-30-64-151.jpg   Zoanthid  \n",
       "2  LSMAY-24-68-443.jpg   Zoanthid  \n",
       "3  LSMAY-24-84-814.jpg   Zoanthid  \n",
       "4  LSMAY-26-82-597.jpg   Zoanthid  "
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "56059"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "# set coral_type to \"Delete\" if original image file is missing from download\n",
    "df['coral_type'] = np.where(\n",
    "    df['shortfilename'].isna(), \n",
    "    'Delete', df['coral_type']\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df.drop_duplicates(\n",
    "    subset=['filename', 'shortfilename', 'coral_type'], keep='first'\n",
    ").reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "37731"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "#df[df.duplicated(subset=['filename', 'shortfilename'], keep=False)].sort_values(by=['shortfilename']).head(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "# duplicate files (from filename and shortfilename) listed multiple ways\n",
    "# set coral_type to \"Delete\" for incorrect listings\n",
    "df.iloc[[5383,18751,6457], 4] = 'Delete'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "# final dataframe includes all coral types except \"Delete\"\n",
    "df = df[df['coral_type'] != 'Delete']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "37364"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['filepath'] = 'scraped_images_' + df['file'].astype(str) + '/' + df['shortfilename']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "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>coral_name</th>\n",
       "      <th>filename</th>\n",
       "      <th>file</th>\n",
       "      <th>shortfilename</th>\n",
       "      <th>coral_type</th>\n",
       "      <th>filepath</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>$79</td>\n",
       "      <td>https://www.reef2reef.com/proxy.php?image=http...</td>\n",
       "      <td>6</td>\n",
       "      <td>LSMAY-22-13-647.jpg</td>\n",
       "      <td>Zoanthid</td>\n",
       "      <td>scraped_images_6/LSMAY-22-13-647.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>$59</td>\n",
       "      <td>https://www.reef2reef.com/proxy.php?image=http...</td>\n",
       "      <td>6</td>\n",
       "      <td>LSMAY-30-64-151.jpg</td>\n",
       "      <td>Zoanthid</td>\n",
       "      <td>scraped_images_6/LSMAY-30-64-151.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>$29</td>\n",
       "      <td>https://www.reef2reef.com/proxy.php?image=http...</td>\n",
       "      <td>6</td>\n",
       "      <td>LSMAY-24-68-443.jpg</td>\n",
       "      <td>Zoanthid</td>\n",
       "      <td>scraped_images_6/LSMAY-24-68-443.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>$69</td>\n",
       "      <td>https://www.reef2reef.com/proxy.php?image=http...</td>\n",
       "      <td>6</td>\n",
       "      <td>LSMAY-24-84-814.jpg</td>\n",
       "      <td>Zoanthid</td>\n",
       "      <td>scraped_images_6/LSMAY-24-84-814.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>$119</td>\n",
       "      <td>https://www.reef2reef.com/proxy.php?image=http...</td>\n",
       "      <td>6</td>\n",
       "      <td>LSMAY-26-82-597.jpg</td>\n",
       "      <td>Zoanthid</td>\n",
       "      <td>scraped_images_6/LSMAY-26-82-597.jpg</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  coral_name                                           filename file  \\\n",
       "0        $79  https://www.reef2reef.com/proxy.php?image=http...    6   \n",
       "1        $59  https://www.reef2reef.com/proxy.php?image=http...    6   \n",
       "2        $29  https://www.reef2reef.com/proxy.php?image=http...    6   \n",
       "3        $69  https://www.reef2reef.com/proxy.php?image=http...    6   \n",
       "4       $119  https://www.reef2reef.com/proxy.php?image=http...    6   \n",
       "\n",
       "         shortfilename coral_type                              filepath  \n",
       "0  LSMAY-22-13-647.jpg   Zoanthid  scraped_images_6/LSMAY-22-13-647.jpg  \n",
       "1  LSMAY-30-64-151.jpg   Zoanthid  scraped_images_6/LSMAY-30-64-151.jpg  \n",
       "2  LSMAY-24-68-443.jpg   Zoanthid  scraped_images_6/LSMAY-24-68-443.jpg  \n",
       "3  LSMAY-24-84-814.jpg   Zoanthid  scraped_images_6/LSMAY-24-84-814.jpg  \n",
       "4  LSMAY-26-82-597.jpg   Zoanthid  scraped_images_6/LSMAY-26-82-597.jpg  "
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "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>coral_type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Australomussa</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tongue</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Elegance</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Echinopora</th>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cynarina</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Acanthophyllia</th>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Frammer</th>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Trachyphyllia</th>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Efflatounaria</th>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Colt</th>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bubble</th>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cristata</th>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Oulophyllia</th>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Plesiastrea</th>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Plate</th>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Anthelia</th>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pectinia</th>\n",
       "      <td>34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Scolymia</th>\n",
       "      <td>36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wilsoni</th>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sympodium</th>\n",
       "      <td>43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Yuma</th>\n",
       "      <td>54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Daisy Polyp</th>\n",
       "      <td>54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cespitularia</th>\n",
       "      <td>59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lobophyllia</th>\n",
       "      <td>61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pocillopora</th>\n",
       "      <td>80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Astreopora</th>\n",
       "      <td>93</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Galaxea</th>\n",
       "      <td>101</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Anemone</th>\n",
       "      <td>106</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Alveopora</th>\n",
       "      <td>116</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Anacropora</th>\n",
       "      <td>117</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hydnophora</th>\n",
       "      <td>140</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Micromussa</th>\n",
       "      <td>143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lithophyllon</th>\n",
       "      <td>150</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Frogspawn</th>\n",
       "      <td>151</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Caulastrea</th>\n",
       "      <td>163</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pavona</th>\n",
       "      <td>168</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Palythoa</th>\n",
       "      <td>190</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pipe Organ</th>\n",
       "      <td>205</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Goniastrea</th>\n",
       "      <td>207</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Porites</th>\n",
       "      <td>215</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Duncan</th>\n",
       "      <td>250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Torch</th>\n",
       "      <td>277</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Stylophora</th>\n",
       "      <td>282</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Turbinaria</th>\n",
       "      <td>308</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Clove Polyp</th>\n",
       "      <td>311</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pulsing Xenia</th>\n",
       "      <td>325</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Star Polyp</th>\n",
       "      <td>335</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Leather</th>\n",
       "      <td>341</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mushroom</th>\n",
       "      <td>365</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rhodactis</th>\n",
       "      <td>366</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bowerbanki</th>\n",
       "      <td>453</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Leptastrea</th>\n",
       "      <td>465</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Stylocoeniella</th>\n",
       "      <td>541</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Psammocora</th>\n",
       "      <td>583</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hammer</th>\n",
       "      <td>620</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Leptoseris</th>\n",
       "      <td>639</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Echinata</th>\n",
       "      <td>643</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Blastomussa</th>\n",
       "      <td>700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Platygyra</th>\n",
       "      <td>768</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Goniopora</th>\n",
       "      <td>823</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Seriatopora</th>\n",
       "      <td>932</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ricordea</th>\n",
       "      <td>1115</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Favites</th>\n",
       "      <td>1491</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cyphastrea</th>\n",
       "      <td>1506</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Chalice</th>\n",
       "      <td>1704</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lord</th>\n",
       "      <td>1725</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Favia</th>\n",
       "      <td>2297</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Montipora</th>\n",
       "      <td>2629</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Acropora</th>\n",
       "      <td>4719</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zoanthid</th>\n",
       "      <td>6959</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                coral_type\n",
       "Australomussa            1\n",
       "Tongue                   1\n",
       "Elegance                 2\n",
       "Echinopora               3\n",
       "Cynarina                 5\n",
       "Acanthophyllia           6\n",
       "Frammer                  6\n",
       "Trachyphyllia            7\n",
       "Efflatounaria            7\n",
       "Colt                    13\n",
       "Bubble                  13\n",
       "Cristata                16\n",
       "Oulophyllia             17\n",
       "Plesiastrea             17\n",
       "Plate                   19\n",
       "Anthelia                33\n",
       "Pectinia                34\n",
       "Scolymia                36\n",
       "Wilsoni                 40\n",
       "Sympodium               43\n",
       "Yuma                    54\n",
       "Daisy Polyp             54\n",
       "Cespitularia            59\n",
       "Lobophyllia             61\n",
       "Pocillopora             80\n",
       "Astreopora              93\n",
       "Galaxea                101\n",
       "Anemone                106\n",
       "Alveopora              116\n",
       "Anacropora             117\n",
       "Hydnophora             140\n",
       "Micromussa             143\n",
       "Lithophyllon           150\n",
       "Frogspawn              151\n",
       "Caulastrea             163\n",
       "Pavona                 168\n",
       "Palythoa               190\n",
       "Pipe Organ             205\n",
       "Goniastrea             207\n",
       "Porites                215\n",
       "Duncan                 250\n",
       "Torch                  277\n",
       "Stylophora             282\n",
       "Turbinaria             308\n",
       "Clove Polyp            311\n",
       "Pulsing Xenia          325\n",
       "Star Polyp             335\n",
       "Leather                341\n",
       "Mushroom               365\n",
       "Rhodactis              366\n",
       "Bowerbanki             453\n",
       "Leptastrea             465\n",
       "Stylocoeniella         541\n",
       "Psammocora             583\n",
       "Hammer                 620\n",
       "Leptoseris             639\n",
       "Echinata               643\n",
       "Blastomussa            700\n",
       "Platygyra              768\n",
       "Goniopora              823\n",
       "Seriatopora            932\n",
       "Ricordea              1115\n",
       "Favites               1491\n",
       "Cyphastrea            1506\n",
       "Chalice               1704\n",
       "Lord                  1725\n",
       "Favia                 2297\n",
       "Montipora             2629\n",
       "Acropora              4719\n",
       "Zoanthid              6959"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['coral_type'].value_counts(dropna=False, ascending=True).to_frame()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "# create files for sorting images into folders based on coral_type\n",
    "for coral in df['coral_type'].unique():\n",
    "    df[df['coral_type'] == coral].filepath.to_csv('coral_types_filepaths/'+coral+'.txt', header=None, index=None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "coral_id",
   "language": "python",
   "name": "coral_id"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}