fetch-data.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Fetching breed data\n",
    "\n",
    " - Author: Telmo de Menezes e Silva Filho\n",
    " - email: tmfilho@gmail.com / telmo@de.ufpb.br\n",
    " - Github: @tmfilho\n",
    " - Date: 18 may 2020\n",
    " - Original data source: [American Kennel Club (AKC)](https://www.akc.org)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import re\n",
    "import requests\n",
    "import os\n",
    "from datetime import datetime\n",
    "\n",
    "from bs4 import BeautifulSoup\n",
    "from bs4.element import Tag\n",
    "\n",
    "import pandas as pd\n",
    "from tqdm import tqdm_notebook as tqdm"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Breed description\n",
    "\n",
    "Breed description is presented in two fields in a breed's page:\n",
    "\n",
    " 1. Summarized in a `<div>` at the top of the page, under the main photo slides;\n",
    " 2. Detailed description in a `<div>` in the \"About\" section.\n",
    " \n",
    "Both fields may be missing from a breed's info page."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_description(breed_soup):\n",
    "    try:\n",
    "        first_part = breed_soup.find(\n",
    "                'div', class_='breed-info__content-wrap'\n",
    "        ).get_text().strip()\n",
    "    except:\n",
    "        first_part = ''\n",
    "    \n",
    "    try:\n",
    "        second_part = breed_soup.find(\n",
    "                'div', class_='breed-hero__footer'\n",
    "        ).get_text().strip()\n",
    "    except:\n",
    "        second_part = ''\n",
    "    \n",
    "    description = ' '.join([first_part, second_part])\n",
    "    \n",
    "    # Removing weird characters\n",
    "    # Probably not exhaustive\n",
    "    description = description.replace(\n",
    "        '\\n', '').replace('\\u200b', '').replace('\\xa0', ' ')\n",
    "    return description"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Breed temperament\n",
    "\n",
    "Breed temperament can be found in a `<span>` to the side of the the main photo slides. This field may be missing."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_temperament(breed_soup):\n",
    "    first_part = 'attribute-list__description attribute-list__text '\n",
    "    second_part = 'attribute-list__text--lg mb4 bpm-mb5 pb0 d-block'\n",
    "    class_ = first_part + second_part\n",
    "    try:\n",
    "        return breed_soup.find(\n",
    "            'span', class_=class_\n",
    "        ).get_text()\n",
    "    except:\n",
    "        return ''"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Main breed attributes\n",
    "\n",
    "This is a list including physical attributes and the breed's popularity rank out of 195 most popular breeds. These informations are contained in `<span>` fields under the temperament information. Breed popularity is missing for 82 breeds.\n",
    "\n",
    "### Breed popularity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_popularity(popularity_span):\n",
    "    pop_text = popularity_span.get_text()\n",
    "    return {'popularity': pop_text.split()[1]}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Breed height, weight and life expectancy\n",
    "\n",
    "Breed height, weight and life expectancy can show up in many forms. They can be informed as intervals or a single average number. They can also be listed separately for males and females or for different size categories. Additionally, life expectancy may be given as a minimum value, such as \"12+\". Finally, numbers may be missing altogether, with something like \"Weight: Proportionate to height\" listed instead, as in the [Cane corso](https://www.akc.org/dog-breeds/cane-corso/) page. \n",
    "\n",
    "Thus we used a regular expression to capture any numbers that appear in the descriptions of these attributes. We then return the minimum and the maximum values. If only a single value is found, we return the same number for min and max. If no numbers are found, we return 0 for both min and max, representing missing data. The regex function receives as arguments the `<span>` text, the variable of interest (height, weight or expectancy) and a multiplier. This multiplier is used to convert values in inches or pounds to the metric system."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def general_regex(text, var, mul=1):\n",
    "    reg = re.compile('(\\d+\\.?\\d*)')\n",
    "    results = reg.findall(text)\n",
    "    numbers = [float(value) * mul for value in results]\n",
    "    if len(numbers) == 1:\n",
    "        numbers = numbers * 2\n",
    "    elif len(numbers) == 0:\n",
    "        numbers = [0, 0]\n",
    "    return {\n",
    "        'min_{}'.format(var): min(numbers),\n",
    "        'max_{}'.format(var): max(numbers)\n",
    "    }"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_height(height_span):\n",
    "    ht_text = height_span.get_text()\n",
    "    \n",
    "     # one inch corresponds to 2.54 cm\n",
    "    return general_regex(ht_text, 'height', 2.54)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_weight(weight_span):\n",
    "    wt_text = weight_span.get_text()\n",
    "    \n",
    "     # one pound corresponds to 0.45359237 kg\n",
    "    return general_regex(wt_text, 'weight', 0.45359237) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_expectancy(expectancy_span):\n",
    "    exp_text = expectancy_span.get_text()\n",
    "    return general_regex(exp_text, 'expectancy') "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Breed group\n",
    "\n",
    "The AKC classifies 198 of the 277 breeds into seven main groups:\n",
    "\n",
    " 1. Sporting;\n",
    " 2. Hound;\n",
    " 3. Working;\n",
    " 4. Terrier;\n",
    " 5. Toy;\n",
    " 6. Non-Sporting;\n",
    " 7. Herding.\n",
    " \n",
    "The remaining 79 breeds are categorized into two extra groups:\n",
    "\n",
    " 1. Miscellaneous Class;\n",
    " 2. Foundation Stock Service.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_group(group_span):\n",
    "    return {'group': group_span.get_text()}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Returning the attributes\n",
    "\n",
    "Two problems are addressed by the dict and function below: \n",
    " 1. Popularity may be missing;\n",
    " 2. All attributes are available in id-less `<span>` tags with the same class attribute.\n",
    " \n",
    "Therefore we take all `<span>` tags with class `'attribute-list__description attribute-list__text'` (which contain the attribute values) and all `<span>` tags with class `'attribute-list__term attribute-list__text'` (which contain the attribute name). And we loop over these lists, calling functions from the `attr_function`, indexed by attribute name."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "attr_function = {\n",
    "    'AKC Breed Popularity': get_popularity,\n",
    "    'Height': get_height,\n",
    "    'Weight': get_weight,\n",
    "    'Life Expectancy': get_expectancy,\n",
    "    'Group': get_group\n",
    "}\n",
    "\n",
    "def get_main_attributes(breed_soup):\n",
    "        \n",
    "    breed_attr_terms = breed_soup.find_all(\n",
    "        'span', class_='attribute-list__term attribute-list__text'\n",
    "    )\n",
    "    # When pressent, the first span is the temperament\n",
    "    if 'Temperament' in breed_attr_terms[0].get_text():\n",
    "        breed_attr_terms = breed_attr_terms[1:]\n",
    "    \n",
    "    breed_attr_values = breed_soup.find_all(\n",
    "        'span', class_='attribute-list__description attribute-list__text'\n",
    "    )\n",
    "    \n",
    "    attributes = {}\n",
    "    \n",
    "    for term_span, value_span in zip (breed_attr_terms, breed_attr_values):\n",
    "        term = term_span.get_text().replace(':', '')\n",
    "        attributes.update(attr_function[term](value_span))\n",
    "    \n",
    "    return attributes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Breed care\n",
    "\n",
    "Information about the breed's care requirements is given in five \"progress bars\", which are actually `<div>` tags  with relative width corresponding to how much of a certain kind of care the breed needs. These are acompanied by a categorization of the breed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_care_info(breed_soup):\n",
    "    titles = breed_soup.find_all(\n",
    "        'h4', class_='bar-graph__title'\n",
    "    )\n",
    "    \n",
    "    values = breed_soup.find_all(\n",
    "        'div', class_='bar-graph__section'\n",
    "    )\n",
    "    \n",
    "    categories = breed_soup.find_all(\n",
    "        'div', class_='bar-graph__text'\n",
    "    )\n",
    "    \n",
    "    care_dict = {}\n",
    "    \n",
    "    for (title, value, category) in zip (titles, values, categories):\n",
    "        t = title.get_text().lower().replace(' ', '_')\n",
    "        t = t[t.find('/') + 1:]\n",
    "        care_dict[t + '_value'] = float(\n",
    "            value['style'].split()[1].split('%')[0]\n",
    "        ) / 100\n",
    "        care_dict[t + '_category'] = category.get_text()\n",
    "    \n",
    "    return care_dict"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## The breed class"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "class Breed:\n",
    "    def __init__(self, url):\n",
    "        self.url = url\n",
    "        breed_page = requests.get(url)\n",
    "        breed_soup = BeautifulSoup(breed_page.content, 'html.parser')\n",
    "\n",
    "        self.breed_info = {}\n",
    "        self.breed_info['description'] = get_description(breed_soup)    \n",
    "        self.breed_info['temperament'] = get_temperament(breed_soup)\n",
    "        self.breed_info.update(get_main_attributes(breed_soup))\n",
    "        self.breed_info.update(get_care_info(breed_soup))\n",
    "        \n",
    "    def get_info(self):  \n",
    "        return self.breed_info"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Running everything"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_data():\n",
    "    page = requests.get('https://www.akc.org/dog-breeds/')\n",
    "    soup = BeautifulSoup(page.content, 'html.parser')\n",
    "    \n",
    "    # An HTML select tag with all the breeds and their urls\n",
    "    breed_select = soup.find('select', id='breed-search')\n",
    "    \n",
    "    # Keeping only children from breed_select which are actually breeds\n",
    "    breeds = [\n",
    "        tag for tag in breed_select.children if type(tag) is Tag and tag['value']\n",
    "    ]\n",
    "    \n",
    "    breed_dict = {\n",
    "        breed.get_text(): Breed(breed['value']).get_info(\n",
    "        ) for breed in tqdm(breeds)\n",
    "    }\n",
    "    \n",
    "    return breed_dict"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "version_major": 2,
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      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=277), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
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   ],
   "source": [
    "breed_dict = get_data()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Converting data to DataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "breed_df = pd.DataFrame.from_dict(\n",
    "    breed_dict, orient='index'\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<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>description</th>\n",
       "      <th>temperament</th>\n",
       "      <th>popularity</th>\n",
       "      <th>min_height</th>\n",
       "      <th>max_height</th>\n",
       "      <th>min_weight</th>\n",
       "      <th>max_weight</th>\n",
       "      <th>min_expectancy</th>\n",
       "      <th>max_expectancy</th>\n",
       "      <th>group</th>\n",
       "      <th>grooming_frequency_value</th>\n",
       "      <th>grooming_frequency_category</th>\n",
       "      <th>shedding_value</th>\n",
       "      <th>shedding_category</th>\n",
       "      <th>energy_level_value</th>\n",
       "      <th>energy_level_category</th>\n",
       "      <th>trainability_value</th>\n",
       "      <th>trainability_category</th>\n",
       "      <th>demeanor_value</th>\n",
       "      <th>demeanor_category</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>Affenpinscher</td>\n",
       "      <td>The Affen’s apish look has been described many...</td>\n",
       "      <td>Confident, Famously Funny, Fearless</td>\n",
       "      <td>148</td>\n",
       "      <td>22.86</td>\n",
       "      <td>29.21</td>\n",
       "      <td>3.175147</td>\n",
       "      <td>4.535924</td>\n",
       "      <td>12.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>Toy Group</td>\n",
       "      <td>0.6</td>\n",
       "      <td>2-3 Times a Week Brushing</td>\n",
       "      <td>0.6</td>\n",
       "      <td>Seasonal</td>\n",
       "      <td>0.6</td>\n",
       "      <td>Regular Exercise</td>\n",
       "      <td>0.8</td>\n",
       "      <td>Easy Training</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Outgoing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Afghan Hound</td>\n",
       "      <td>The Afghan Hound is an ancient breed, his whol...</td>\n",
       "      <td>Dignified, Profoundly Loyal, Aristocratic</td>\n",
       "      <td>113</td>\n",
       "      <td>63.50</td>\n",
       "      <td>68.58</td>\n",
       "      <td>22.679619</td>\n",
       "      <td>27.215542</td>\n",
       "      <td>12.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>Hound Group</td>\n",
       "      <td>0.8</td>\n",
       "      <td>Daily Brushing</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Infrequent</td>\n",
       "      <td>0.8</td>\n",
       "      <td>Energetic</td>\n",
       "      <td>0.2</td>\n",
       "      <td>May be Stubborn</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Aloof/Wary</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Airedale Terrier</td>\n",
       "      <td>The Airedale Terrier is the largest of all ter...</td>\n",
       "      <td>Friendly, Clever, Courageous</td>\n",
       "      <td>60</td>\n",
       "      <td>58.42</td>\n",
       "      <td>58.42</td>\n",
       "      <td>22.679619</td>\n",
       "      <td>31.751466</td>\n",
       "      <td>11.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>Terrier Group</td>\n",
       "      <td>0.6</td>\n",
       "      <td>2-3 Times a Week Brushing</td>\n",
       "      <td>0.4</td>\n",
       "      <td>Occasional</td>\n",
       "      <td>0.6</td>\n",
       "      <td>Regular Exercise</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Eager to Please</td>\n",
       "      <td>0.8</td>\n",
       "      <td>Friendly</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Akita</td>\n",
       "      <td>Akitas are burly, heavy-boned spitz-type dogs ...</td>\n",
       "      <td>Courageous, Dignified, Profoundly Loyal</td>\n",
       "      <td>47</td>\n",
       "      <td>60.96</td>\n",
       "      <td>71.12</td>\n",
       "      <td>31.751466</td>\n",
       "      <td>58.967008</td>\n",
       "      <td>10.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>Working Group</td>\n",
       "      <td>0.8</td>\n",
       "      <td>Daily Brushing</td>\n",
       "      <td>0.6</td>\n",
       "      <td>Seasonal</td>\n",
       "      <td>0.8</td>\n",
       "      <td>Energetic</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Eager to Please</td>\n",
       "      <td>0.6</td>\n",
       "      <td>Alert/Responsive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Alaskan Malamute</td>\n",
       "      <td>The Alaskan Malamute stands 23 to 25 inches at...</td>\n",
       "      <td>Affectionate, Loyal, Playful</td>\n",
       "      <td>58</td>\n",
       "      <td>58.42</td>\n",
       "      <td>63.50</td>\n",
       "      <td>34.019428</td>\n",
       "      <td>38.555351</td>\n",
       "      <td>10.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>Working Group</td>\n",
       "      <td>0.6</td>\n",
       "      <td>2-3 Times a Week Brushing</td>\n",
       "      <td>0.6</td>\n",
       "      <td>Seasonal</td>\n",
       "      <td>0.8</td>\n",
       "      <td>Energetic</td>\n",
       "      <td>0.4</td>\n",
       "      <td>Independent</td>\n",
       "      <td>0.8</td>\n",
       "      <td>Friendly</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Wirehaired Vizsla</td>\n",
       "      <td>WVs are close relatives of Vizslas but a disti...</td>\n",
       "      <td>Gentle, Loyal, Trainable</td>\n",
       "      <td>167</td>\n",
       "      <td>54.61</td>\n",
       "      <td>63.50</td>\n",
       "      <td>20.411657</td>\n",
       "      <td>29.483504</td>\n",
       "      <td>12.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>Sporting Group</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Occasional Bath/Brush</td>\n",
       "      <td>0.6</td>\n",
       "      <td>Seasonal</td>\n",
       "      <td>0.8</td>\n",
       "      <td>Energetic</td>\n",
       "      <td>0.6</td>\n",
       "      <td>Agreeable</td>\n",
       "      <td>0.6</td>\n",
       "      <td>Alert/Responsive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Working Kelpie</td>\n",
       "      <td>The overall appearance of the Working Kelpie i...</td>\n",
       "      <td>Alert, Eager, Intelligent</td>\n",
       "      <td>NaN</td>\n",
       "      <td>48.26</td>\n",
       "      <td>63.50</td>\n",
       "      <td>12.700586</td>\n",
       "      <td>27.215542</td>\n",
       "      <td>12.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>Foundation Stock Service</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Occasional Bath/Brush</td>\n",
       "      <td>0.6</td>\n",
       "      <td>Seasonal</td>\n",
       "      <td>0.8</td>\n",
       "      <td>Energetic</td>\n",
       "      <td>0.4</td>\n",
       "      <td>Independent</td>\n",
       "      <td>0.6</td>\n",
       "      <td>Alert/Responsive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Xoloitzcuintli</td>\n",
       "      <td>The Xoloitzcuintli (show-low-eats-queen-tlee) ...</td>\n",
       "      <td>Loyal, Alert, Calm</td>\n",
       "      <td>140</td>\n",
       "      <td>25.40</td>\n",
       "      <td>58.42</td>\n",
       "      <td>4.535924</td>\n",
       "      <td>24.947580</td>\n",
       "      <td>13.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>Non-Sporting Group</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Occasional Bath/Brush</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Infrequent</td>\n",
       "      <td>0.8</td>\n",
       "      <td>Energetic</td>\n",
       "      <td>0.6</td>\n",
       "      <td>Agreeable</td>\n",
       "      <td>0.6</td>\n",
       "      <td>Alert/Responsive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Yakutian Laika</td>\n",
       "      <td>For centuries the Yakutian Laika was an irrepl...</td>\n",
       "      <td>Affectionate, Intelligent, Active</td>\n",
       "      <td>NaN</td>\n",
       "      <td>53.34</td>\n",
       "      <td>58.42</td>\n",
       "      <td>18.143695</td>\n",
       "      <td>24.947580</td>\n",
       "      <td>10.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>Foundation Stock Service</td>\n",
       "      <td>0.4</td>\n",
       "      <td>Weekly Brushing</td>\n",
       "      <td>0.6</td>\n",
       "      <td>Seasonal</td>\n",
       "      <td>0.8</td>\n",
       "      <td>Energetic</td>\n",
       "      <td>0.2</td>\n",
       "      <td>May be Stubborn</td>\n",
       "      <td>0.4</td>\n",
       "      <td>Reserved with Strangers</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Yorkshire Terrier</td>\n",
       "      <td>The Yorkshire Terrier is a compact, toy-size t...</td>\n",
       "      <td>Affectionate, Sprightly, Tomboyish</td>\n",
       "      <td>10</td>\n",
       "      <td>17.78</td>\n",
       "      <td>20.32</td>\n",
       "      <td>3.175147</td>\n",
       "      <td>3.175147</td>\n",
       "      <td>11.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>Toy Group</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Specialty/Professional</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Infrequent</td>\n",
       "      <td>0.6</td>\n",
       "      <td>Regular Exercise</td>\n",
       "      <td>0.2</td>\n",
       "      <td>May be Stubborn</td>\n",
       "      <td>0.8</td>\n",
       "      <td>Friendly</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>277 rows × 20 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                         description  \\\n",
       "Affenpinscher      The Affen’s apish look has been described many...   \n",
       "Afghan Hound       The Afghan Hound is an ancient breed, his whol...   \n",
       "Airedale Terrier   The Airedale Terrier is the largest of all ter...   \n",
       "Akita              Akitas are burly, heavy-boned spitz-type dogs ...   \n",
       "Alaskan Malamute   The Alaskan Malamute stands 23 to 25 inches at...   \n",
       "...                                                              ...   \n",
       "Wirehaired Vizsla  WVs are close relatives of Vizslas but a disti...   \n",
       "Working Kelpie     The overall appearance of the Working Kelpie i...   \n",
       "Xoloitzcuintli     The Xoloitzcuintli (show-low-eats-queen-tlee) ...   \n",
       "Yakutian Laika     For centuries the Yakutian Laika was an irrepl...   \n",
       "Yorkshire Terrier  The Yorkshire Terrier is a compact, toy-size t...   \n",
       "\n",
       "                                                 temperament popularity  \\\n",
       "Affenpinscher            Confident, Famously Funny, Fearless        148   \n",
       "Afghan Hound       Dignified, Profoundly Loyal, Aristocratic        113   \n",
       "Airedale Terrier                Friendly, Clever, Courageous         60   \n",
       "Akita                Courageous, Dignified, Profoundly Loyal         47   \n",
       "Alaskan Malamute                Affectionate, Loyal, Playful         58   \n",
       "...                                                      ...        ...   \n",
       "Wirehaired Vizsla                   Gentle, Loyal, Trainable        167   \n",
       "Working Kelpie                     Alert, Eager, Intelligent        NaN   \n",
       "Xoloitzcuintli                            Loyal, Alert, Calm        140   \n",
       "Yakutian Laika             Affectionate, Intelligent, Active        NaN   \n",
       "Yorkshire Terrier         Affectionate, Sprightly, Tomboyish         10   \n",
       "\n",
       "                   min_height  max_height  min_weight  max_weight  \\\n",
       "Affenpinscher           22.86       29.21    3.175147    4.535924   \n",
       "Afghan Hound            63.50       68.58   22.679619   27.215542   \n",
       "Airedale Terrier        58.42       58.42   22.679619   31.751466   \n",
       "Akita                   60.96       71.12   31.751466   58.967008   \n",
       "Alaskan Malamute        58.42       63.50   34.019428   38.555351   \n",
       "...                       ...         ...         ...         ...   \n",
       "Wirehaired Vizsla       54.61       63.50   20.411657   29.483504   \n",
       "Working Kelpie          48.26       63.50   12.700586   27.215542   \n",
       "Xoloitzcuintli          25.40       58.42    4.535924   24.947580   \n",
       "Yakutian Laika          53.34       58.42   18.143695   24.947580   \n",
       "Yorkshire Terrier       17.78       20.32    3.175147    3.175147   \n",
       "\n",
       "                   min_expectancy  max_expectancy                     group  \\\n",
       "Affenpinscher                12.0            15.0                 Toy Group   \n",
       "Afghan Hound                 12.0            15.0               Hound Group   \n",
       "Airedale Terrier             11.0            14.0             Terrier Group   \n",
       "Akita                        10.0            13.0             Working Group   \n",
       "Alaskan Malamute             10.0            14.0             Working Group   \n",
       "...                           ...             ...                       ...   \n",
       "Wirehaired Vizsla            12.0            14.0            Sporting Group   \n",
       "Working Kelpie               12.0            15.0  Foundation Stock Service   \n",
       "Xoloitzcuintli               13.0            18.0        Non-Sporting Group   \n",
       "Yakutian Laika               10.0            12.0  Foundation Stock Service   \n",
       "Yorkshire Terrier            11.0            15.0                 Toy Group   \n",
       "\n",
       "                   grooming_frequency_value grooming_frequency_category  \\\n",
       "Affenpinscher                           0.6   2-3 Times a Week Brushing   \n",
       "Afghan Hound                            0.8              Daily Brushing   \n",
       "Airedale Terrier                        0.6   2-3 Times a Week Brushing   \n",
       "Akita                                   0.8              Daily Brushing   \n",
       "Alaskan Malamute                        0.6   2-3 Times a Week Brushing   \n",
       "...                                     ...                         ...   \n",
       "Wirehaired Vizsla                       0.2       Occasional Bath/Brush   \n",
       "Working Kelpie                          0.2       Occasional Bath/Brush   \n",
       "Xoloitzcuintli                          0.2       Occasional Bath/Brush   \n",
       "Yakutian Laika                          0.4             Weekly Brushing   \n",
       "Yorkshire Terrier                       1.0      Specialty/Professional   \n",
       "\n",
       "                   shedding_value shedding_category  energy_level_value  \\\n",
       "Affenpinscher                 0.6          Seasonal                 0.6   \n",
       "Afghan Hound                  0.2        Infrequent                 0.8   \n",
       "Airedale Terrier              0.4        Occasional                 0.6   \n",
       "Akita                         0.6          Seasonal                 0.8   \n",
       "Alaskan Malamute              0.6          Seasonal                 0.8   \n",
       "...                           ...               ...                 ...   \n",
       "Wirehaired Vizsla             0.6          Seasonal                 0.8   \n",
       "Working Kelpie                0.6          Seasonal                 0.8   \n",
       "Xoloitzcuintli                0.2        Infrequent                 0.8   \n",
       "Yakutian Laika                0.6          Seasonal                 0.8   \n",
       "Yorkshire Terrier             0.2        Infrequent                 0.6   \n",
       "\n",
       "                  energy_level_category  trainability_value  \\\n",
       "Affenpinscher          Regular Exercise                 0.8   \n",
       "Afghan Hound                  Energetic                 0.2   \n",
       "Airedale Terrier       Regular Exercise                 1.0   \n",
       "Akita                         Energetic                 1.0   \n",
       "Alaskan Malamute              Energetic                 0.4   \n",
       "...                                 ...                 ...   \n",
       "Wirehaired Vizsla             Energetic                 0.6   \n",
       "Working Kelpie                Energetic                 0.4   \n",
       "Xoloitzcuintli                Energetic                 0.6   \n",
       "Yakutian Laika                Energetic                 0.2   \n",
       "Yorkshire Terrier      Regular Exercise                 0.2   \n",
       "\n",
       "                  trainability_category  demeanor_value  \\\n",
       "Affenpinscher             Easy Training             1.0   \n",
       "Afghan Hound            May be Stubborn             0.2   \n",
       "Airedale Terrier        Eager to Please             0.8   \n",
       "Akita                   Eager to Please             0.6   \n",
       "Alaskan Malamute            Independent             0.8   \n",
       "...                                 ...             ...   \n",
       "Wirehaired Vizsla             Agreeable             0.6   \n",
       "Working Kelpie              Independent             0.6   \n",
       "Xoloitzcuintli                Agreeable             0.6   \n",
       "Yakutian Laika          May be Stubborn             0.4   \n",
       "Yorkshire Terrier       May be Stubborn             0.8   \n",
       "\n",
       "                         demeanor_category  \n",
       "Affenpinscher                     Outgoing  \n",
       "Afghan Hound                    Aloof/Wary  \n",
       "Airedale Terrier                  Friendly  \n",
       "Akita                     Alert/Responsive  \n",
       "Alaskan Malamute                  Friendly  \n",
       "...                                    ...  \n",
       "Wirehaired Vizsla         Alert/Responsive  \n",
       "Working Kelpie            Alert/Responsive  \n",
       "Xoloitzcuintli            Alert/Responsive  \n",
       "Yakutian Laika     Reserved with Strangers  \n",
       "Yorkshire Terrier                 Friendly  \n",
       "\n",
       "[277 rows x 20 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "breed_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>description</th>\n",
       "      <th>temperament</th>\n",
       "      <th>popularity</th>\n",
       "      <th>min_height</th>\n",
       "      <th>max_height</th>\n",
       "      <th>min_weight</th>\n",
       "      <th>max_weight</th>\n",
       "      <th>min_expectancy</th>\n",
       "      <th>max_expectancy</th>\n",
       "      <th>group</th>\n",
       "      <th>grooming_frequency_value</th>\n",
       "      <th>grooming_frequency_category</th>\n",
       "      <th>shedding_value</th>\n",
       "      <th>shedding_category</th>\n",
       "      <th>energy_level_value</th>\n",
       "      <th>energy_level_category</th>\n",
       "      <th>trainability_value</th>\n",
       "      <th>trainability_category</th>\n",
       "      <th>demeanor_value</th>\n",
       "      <th>demeanor_category</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>count</td>\n",
       "      <td>277</td>\n",
       "      <td>277</td>\n",
       "      <td>198</td>\n",
       "      <td>277.000000</td>\n",
       "      <td>277.000000</td>\n",
       "      <td>275.000000</td>\n",
       "      <td>275.000000</td>\n",
       "      <td>274.000000</td>\n",
       "      <td>274.000000</td>\n",
       "      <td>277</td>\n",
       "      <td>270.000000</td>\n",
       "      <td>270</td>\n",
       "      <td>257.000000</td>\n",
       "      <td>257</td>\n",
       "      <td>271.000000</td>\n",
       "      <td>271</td>\n",
       "      <td>253.000000</td>\n",
       "      <td>253</td>\n",
       "      <td>252.000000</td>\n",
       "      <td>252</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>unique</td>\n",
       "      <td>276</td>\n",
       "      <td>268</td>\n",
       "      <td>191</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>9</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>top</td>\n",
       "      <td>Poodles come in three size varieties: Standard...</td>\n",
       "      <td>Friendly, Smart, Willing to Please</td>\n",
       "      <td>7</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>Foundation Stock Service</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Weekly Brushing</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Seasonal</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Regular Exercise</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Agreeable</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Friendly</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>freq</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>3</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>68</td>\n",
       "      <td>NaN</td>\n",
       "      <td>119</td>\n",
       "      <td>NaN</td>\n",
       "      <td>125</td>\n",
       "      <td>NaN</td>\n",
       "      <td>118</td>\n",
       "      <td>NaN</td>\n",
       "      <td>77</td>\n",
       "      <td>NaN</td>\n",
       "      <td>77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>mean</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>44.225801</td>\n",
       "      <td>52.720588</td>\n",
       "      <td>17.888858</td>\n",
       "      <td>27.291416</td>\n",
       "      <td>11.306569</td>\n",
       "      <td>13.832117</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.425926</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.529183</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.712915</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.624506</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.620635</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <td>std</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14.238298</td>\n",
       "      <td>15.885454</td>\n",
       "      <td>12.290600</td>\n",
       "      <td>19.061416</td>\n",
       "      <td>1.817949</td>\n",
       "      <td>2.016668</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.198306</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.189068</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.168927</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.247271</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.201713</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <td>min</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12.700000</td>\n",
       "      <td>17.780000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.200000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.200000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.200000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.200000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.200000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>25%</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>33.020000</td>\n",
       "      <td>38.100000</td>\n",
       "      <td>8.164663</td>\n",
       "      <td>12.927383</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>13.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.200000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.400000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.600000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.400000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.400000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>50%</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>45.085000</td>\n",
       "      <td>53.340000</td>\n",
       "      <td>15.875733</td>\n",
       "      <td>24.947580</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>14.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.400000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.600000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.600000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.600000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.600000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>75%</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>55.880000</td>\n",
       "      <td>66.040000</td>\n",
       "      <td>22.679619</td>\n",
       "      <td>34.019428</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>15.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.600000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.600000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.800000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.800000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.800000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>max</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>76.200000</td>\n",
       "      <td>88.900000</td>\n",
       "      <td>68.038855</td>\n",
       "      <td>108.862169</td>\n",
       "      <td>16.000000</td>\n",
       "      <td>19.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                              description  \\\n",
       "count                                                 277   \n",
       "unique                                                276   \n",
       "top     Poodles come in three size varieties: Standard...   \n",
       "freq                                                    2   \n",
       "mean                                                  NaN   \n",
       "std                                                   NaN   \n",
       "min                                                   NaN   \n",
       "25%                                                   NaN   \n",
       "50%                                                   NaN   \n",
       "75%                                                   NaN   \n",
       "max                                                   NaN   \n",
       "\n",
       "                               temperament popularity  min_height  max_height  \\\n",
       "count                                  277        198  277.000000  277.000000   \n",
       "unique                                 268        191         NaN         NaN   \n",
       "top     Friendly, Smart, Willing to Please          7         NaN         NaN   \n",
       "freq                                     3          3         NaN         NaN   \n",
       "mean                                   NaN        NaN   44.225801   52.720588   \n",
       "std                                    NaN        NaN   14.238298   15.885454   \n",
       "min                                    NaN        NaN   12.700000   17.780000   \n",
       "25%                                    NaN        NaN   33.020000   38.100000   \n",
       "50%                                    NaN        NaN   45.085000   53.340000   \n",
       "75%                                    NaN        NaN   55.880000   66.040000   \n",
       "max                                    NaN        NaN   76.200000   88.900000   \n",
       "\n",
       "        min_weight  max_weight  min_expectancy  max_expectancy  \\\n",
       "count   275.000000  275.000000      274.000000      274.000000   \n",
       "unique         NaN         NaN             NaN             NaN   \n",
       "top            NaN         NaN             NaN             NaN   \n",
       "freq           NaN         NaN             NaN             NaN   \n",
       "mean     17.888858   27.291416       11.306569       13.832117   \n",
       "std      12.290600   19.061416        1.817949        2.016668   \n",
       "min       0.000000    0.000000        0.000000        0.000000   \n",
       "25%       8.164663   12.927383       10.000000       13.000000   \n",
       "50%      15.875733   24.947580       12.000000       14.000000   \n",
       "75%      22.679619   34.019428       12.000000       15.000000   \n",
       "max      68.038855  108.862169       16.000000       19.000000   \n",
       "\n",
       "                           group  grooming_frequency_value  \\\n",
       "count                        277                270.000000   \n",
       "unique                         9                       NaN   \n",
       "top     Foundation Stock Service                       NaN   \n",
       "freq                          68                       NaN   \n",
       "mean                         NaN                  0.425926   \n",
       "std                          NaN                  0.198306   \n",
       "min                          NaN                  0.200000   \n",
       "25%                          NaN                  0.200000   \n",
       "50%                          NaN                  0.400000   \n",
       "75%                          NaN                  0.600000   \n",
       "max                          NaN                  1.000000   \n",
       "\n",
       "       grooming_frequency_category  shedding_value shedding_category  \\\n",
       "count                          270      257.000000               257   \n",
       "unique                           5             NaN                 5   \n",
       "top                Weekly Brushing             NaN          Seasonal   \n",
       "freq                           119             NaN               125   \n",
       "mean                           NaN        0.529183               NaN   \n",
       "std                            NaN        0.189068               NaN   \n",
       "min                            NaN        0.200000               NaN   \n",
       "25%                            NaN        0.400000               NaN   \n",
       "50%                            NaN        0.600000               NaN   \n",
       "75%                            NaN        0.600000               NaN   \n",
       "max                            NaN        1.000000               NaN   \n",
       "\n",
       "        energy_level_value energy_level_category  trainability_value  \\\n",
       "count           271.000000                   271          253.000000   \n",
       "unique                 NaN                     5                 NaN   \n",
       "top                    NaN      Regular Exercise                 NaN   \n",
       "freq                   NaN                   118                 NaN   \n",
       "mean              0.712915                   NaN            0.624506   \n",
       "std               0.168927                   NaN            0.247271   \n",
       "min               0.200000                   NaN            0.200000   \n",
       "25%               0.600000                   NaN            0.400000   \n",
       "50%               0.600000                   NaN            0.600000   \n",
       "75%               0.800000                   NaN            0.800000   \n",
       "max               1.000000                   NaN            1.000000   \n",
       "\n",
       "       trainability_category  demeanor_value demeanor_category  \n",
       "count                    253      252.000000               252  \n",
       "unique                     5             NaN                 5  \n",
       "top                Agreeable             NaN          Friendly  \n",
       "freq                      77             NaN                77  \n",
       "mean                     NaN        0.620635               NaN  \n",
       "std                      NaN        0.201713               NaN  \n",
       "min                      NaN        0.200000               NaN  \n",
       "25%                      NaN        0.400000               NaN  \n",
       "50%                      NaN        0.600000               NaN  \n",
       "75%                      NaN        0.800000               NaN  \n",
       "max                      NaN        1.000000               NaN  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "breed_df.describe(include='all')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Saving DataFrame as csv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "if not os.path.exists('data/'):\n",
    "    os.makedirs('data/')\n",
    "    \n",
    "breed_df.to_csv('data/akc-data-{}.csv'.format(datetime.today()))\n",
    "breed_df.to_csv('data/akc-data-latest.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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