1BedRoom-Chicago Craigslist Rent DataScrape v1.1_New-Visualizations.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Updated: 12/8/2020\n",
    "\n",
    "Scraping Craigslist's rental section to get accurate representation of the prices and square footage of 1 bedrooms throughout different Chicago neighorhoods."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 52
    },
    "colab_type": "code",
    "id": "_jGyBgvjXlXo",
    "outputId": "a5319979-e33b-460f-e3f5-73cc2bb58cb8"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'bs4.element.ResultSet'>\n",
      "120\n"
     ]
    }
   ],
   "source": [
    "\n",
    "#import get to call a get request on the site\n",
    "from requests import get\n",
    "\n",
    "#get the 1st page of the chicago housing prices \n",
    "#get rid of posts without a pic using their filter\n",
    "response = get('https://chicago.craigslist.org/search/chc/apa?hasPic=1&availabilityMode=0')\n",
    "\n",
    "from bs4 import BeautifulSoup\n",
    "html_soup = BeautifulSoup(response.text, 'html.parser')\n",
    "\n",
    "#get the macro-container for the housing posts\n",
    "posts = html_soup.find_all('li', class_= 'result-row')\n",
    "print(type(posts)) #to double check that I got a ResultSet\n",
    "print(len(posts)) #to double check I got 120 (elements/page)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "b1vwc4vZXlaF"
   },
   "outputs": [],
   "source": [
    "#get first post\n",
    "post_one = posts[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "colab_type": "code",
    "id": "BaxtdUl4Xlci",
    "outputId": "9d9cb440-03e9-4eb4-dbb6-2729989a78e9"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'$1,400'"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#price of 1st post\n",
    "post_one_price = post_one.a.text\n",
    "#remove comma from listing. Need to do later for all the posts\n",
    "#post_one_price = post_one.a.text.replace(',', '')\n",
    "post_one_price.strip()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "pqmoMN5VXlg4"
   },
   "outputs": [],
   "source": [
    "#get the time of the post in datetime format\n",
    "post_one_time = post_one.find('time', class_= 'result-date')\n",
    "post_one_datetime = post_one_time['datetime']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "xjHdFsk7XljA"
   },
   "outputs": [],
   "source": [
    "#title is a and that class, link is grabbing the href attribute of that variable\n",
    "post_one_title = post_one.find('a', class_='result-title hdrlnk')\n",
    "post_one_link = post_one_title['href']\n",
    "\n",
    "#easy to grab the post title by taking the text element of the title variable\n",
    "post_one_title_text = post_one_title.text"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [],
   "source": [
    "#execute multiple statements per cell\n",
    "from IPython.core.interactiveshell import InteractiveShell\n",
    "InteractiveShell.ast_node_interactivity = \"all\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 200
    },
    "colab_type": "code",
    "id": "aCOC0VNZXlpN",
    "outputId": "f2483405-30ba-476d-9bc7-7240b120064c"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'2br'"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<span class=\"housing\">\n",
       "                    2br -\n",
       "                </span>"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "ename": "IndexError",
     "evalue": "list index out of range",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mIndexError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-57-48c7016b7f3d>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      8\u001b[0m \u001b[0mpost_one_sqft\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      9\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 10\u001b[1;33m \u001b[0mpost_one_sqft\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mpost_one\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfind\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'span'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mclass_\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;34m'housing'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtext\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msplit\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m2\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m-\u001b[0m\u001b[1;36m3\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     11\u001b[0m \u001b[0mpost_one_sqft\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     12\u001b[0m \u001b[1;31m#post_one_sqft = post_one.find('span', class_ = 'housing').text.split()[2][:-3] #cleans the ft2 at the end\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mIndexError\u001b[0m: list index out of range"
     ]
    }
   ],
   "source": [
    "#grabs the whole segment of housing details. We will need missing value handling in the loop as this kind of detail is not common in posts\n",
    "#the text can be split, and we can use indexing to grab the elements we want. number of bedrooms is the first element.\n",
    "#sqft is the third element\n",
    "post_one_num_bedrooms = post_one.find('span', class_ = 'housing').text.split()[0]\n",
    "post_one_num_bedrooms\n",
    "\n",
    "post_one_sqft = post_one.find('span', class_ = 'housing')\n",
    "post_one_sqft\n",
    "\n",
    "post_one_sqft = post_one.find('span', class_ = 'housing').text.split()[2][:-3]\n",
    "post_one_sqft\n",
    "#post_one_sqft = post_one.find('span', class_ = 'housing').text.split()[2][:-3] #cleans the ft2 at the end"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "-x-QMD_NXlsF"
   },
   "outputs": [],
   "source": [
    "#the neighborhood is grabbed by finding the span class 'result-hood' and pulling the text element from there\n",
    "\n",
    "post_one_hood = posts[0].find('span', class_='result-hood').text"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 520
    },
    "colab_type": "code",
    "id": "-kqViHwzXlwa",
    "outputId": "26f8f94e-c23a-4fd7-9abf-4c7bada70b24"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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      "\n",
      "\n",
      "Scrape complete!\n"
     ]
    }
   ],
   "source": [
    "#build out the loop\n",
    "from time import sleep\n",
    "import re\n",
    "##this will allow us to scrape without getting blocked by craigslist\n",
    "from random import randint #avoid throttling by not sending too many requests one after the other\n",
    "from warnings import warn\n",
    "from time import time\n",
    "from IPython.core.display import clear_output\n",
    "import numpy as np\n",
    "\n",
    "#find the total number of posts to find the limit of the pagination\n",
    "results_num = html_soup.find('div', class_= 'search-legend')\n",
    "results_total = int(results_num.find('span', class_='totalcount').text) #pulled the total count of posts as the upper bound of the pages array\n",
    "\n",
    "#each page has 119 posts so each new page is defined as follows: s=120, s=240, s=360, and so on. So we need to step in size 120 in the np.arange function\n",
    "pages = np.arange(0, results_total+1, 120)\n",
    "\n",
    "iterations = 0\n",
    "\n",
    "post_timing = []\n",
    "post_hoods = []\n",
    "post_title_texts = []\n",
    "bedroom_counts = []\n",
    "sqfts = []\n",
    "post_links = []\n",
    "post_prices = []\n",
    "\n",
    "for page in pages:\n",
    "    \n",
    "    #get request\n",
    "    response = get(\"https://chicago.craigslist.org/search/chc/apa?\" \n",
    "                   + \"s=\" #the parameter for defining the page number \n",
    "                   + str(page) #the page number in the pages array from earlier\n",
    "                   + \"&hasPic=1\"\n",
    "                   + \"&availabilityMode=0\")\n",
    "\n",
    "    sleep(randint(1,5))\n",
    "     \n",
    "    #throw warning for status codes that are not 200\n",
    "    if response.status_code != 200:\n",
    "        warn('Request: {}; Status code: {}'.format(requests, response.status_code))\n",
    "        \n",
    "    #define the html text\n",
    "    page_html = BeautifulSoup(response.text, 'html.parser')\n",
    "    \n",
    "    #define the posts\n",
    "    posts = html_soup.find_all('li', class_= 'result-row')\n",
    "        \n",
    "    #extract data item-wise\n",
    "    for post in posts:\n",
    "\n",
    "        if post.find('span', class_ = 'result-hood') is not None:\n",
    "\n",
    "            #posting date\n",
    "            #grab the datetime element 0 for date and 1 for time\n",
    "            post_datetime = post.find('time', class_= 'result-date')['datetime']\n",
    "            post_timing.append(post_datetime)\n",
    "\n",
    "            #neighborhoods\n",
    "            post_hood = post.find('span', class_= 'result-hood').text\n",
    "            post_hoods.append(post_hood)\n",
    "\n",
    "            #title text\n",
    "            post_title = post.find('a', class_='result-title hdrlnk')\n",
    "            post_title_text = post_title.text\n",
    "            post_title_texts.append(post_title_text)\n",
    "\n",
    "            #post link\n",
    "            post_link = post_title['href']\n",
    "            post_links.append(post_link)\n",
    "            \n",
    "            #removes the \\n whitespace from each side, removes the currency symbol, the comma \n",
    "            #and turns it into an int\n",
    "            post_price = int(post.a.text.strip().replace(\"$\", \"\").replace(\",\",\"\"))\n",
    "            #post_price = int(post.a.text.strip().replace(',', '')\n",
    "            post_prices.append(post_price)\n",
    "                        \n",
    "            if post.find('span', class_ = 'housing') is not None:\n",
    "                \n",
    "                #if the first element is accidentally square footage\n",
    "                if 'ft2' in post.find('span', class_ = 'housing').text.split()[0]:\n",
    "                    \n",
    "                    #make bedroom nan\n",
    "                    bedroom_count = np.nan\n",
    "                    bedroom_counts.append(bedroom_count)\n",
    "                    \n",
    "                    #make sqft the first element\n",
    "                    sqft = int(post.find('span', class_ = 'housing').text.split()[0][:-3])\n",
    "                    sqfts.append(sqft)\n",
    "                    \n",
    "                #if the length of the housing details element is more than 2\n",
    "                elif len(post.find('span', class_ = 'housing').text.split()) > 2:\n",
    "                    \n",
    "                    #therefore element 0 will be bedroom count\n",
    "                    bedroom_count = post.find('span', class_ = 'housing').text.replace(\"br\", \"\").split()[0]\n",
    "                    bedroom_counts.append(bedroom_count)\n",
    "                    \n",
    "                    #and sqft will be number 3, so set these here and append\n",
    "                    sqft = int(post.find('span', class_ = 'housing').text.split()[2][:-3])\n",
    "                    sqfts.append(sqft)\n",
    "                    \n",
    "                #if there is num bedrooms but no sqft\n",
    "                elif len(post.find('span', class_ = 'housing').text.split()) == 2:\n",
    "                    \n",
    "                    #therefore element 0 will be bedroom count\n",
    "                    bedroom_count = post.find('span', class_ = 'housing').text.replace(\"br\", \"\").split()[0]\n",
    "                    bedroom_counts.append(bedroom_count)\n",
    "                    \n",
    "                    #and sqft will be number 3, so set these here and append\n",
    "                    sqft = np.nan\n",
    "                    sqfts.append(sqft)                    \n",
    "                \n",
    "                else:\n",
    "                    bedroom_count = np.nan\n",
    "                    bedroom_counts.append(bedroom_count)\n",
    "                \n",
    "                    sqft = np.nan\n",
    "                    sqfts.append(sqft)\n",
    "                \n",
    "            #if none of those conditions catch, make bedroom nan, this won't be needed    \n",
    "            else:\n",
    "                bedroom_count = np.nan\n",
    "                bedroom_counts.append(bedroom_count)\n",
    "                \n",
    "                sqft = np.nan\n",
    "                sqfts.append(sqft)\n",
    "            #    bedroom_counts.append(bedroom_count)\n",
    "                \n",
    "            #    sqft = np.nan\n",
    "            #    sqfts.append(sqft)\n",
    "                \n",
    "    iterations += 1\n",
    "    print(\"Page \" + str(iterations) + \" scraped successfully!\")\n",
    "\n",
    "print(\"\\n\")\n",
    "\n",
    "print(\"Scrape complete!\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 754
    },
    "colab_type": "code",
    "id": "Qhfokzt7XlzC",
    "outputId": "e418b495-e965-4c4b-e0f9-02892661535a"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 2990 entries, 0 to 2989\n",
      "Data columns (total 7 columns):\n",
      " #   Column        Non-Null Count  Dtype  \n",
      "---  ------        --------------  -----  \n",
      " 0   Posted        2990 non-null   object \n",
      " 1   Neighborhood  2990 non-null   object \n",
      " 2   Post_Title    2990 non-null   object \n",
      " 3   Num_Bedrooms  2704 non-null   object \n",
      " 4   Sqft          1040 non-null   float64\n",
      " 5   URL           2990 non-null   object \n",
      " 6   Price         2990 non-null   int64  \n",
      "dtypes: float64(1), int64(1), object(5)\n",
      "memory usage: 163.6+ KB\n",
      "None\n"
     ]
    },
    {
     "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>Posted</th>\n",
       "      <th>Neighborhood</th>\n",
       "      <th>Post_Title</th>\n",
       "      <th>Num_Bedrooms</th>\n",
       "      <th>Sqft</th>\n",
       "      <th>URL</th>\n",
       "      <th>Price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2020-12-12 20:07</td>\n",
       "      <td>(PILSEN)</td>\n",
       "      <td>AMAZING 2bed/2 bath w/d in unit</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://chicago.craigslist.org/chc/apa/d/chica...</td>\n",
       "      <td>1400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2020-12-12 19:56</td>\n",
       "      <td>(Logan Square)</td>\n",
       "      <td>HUGE 2 br/1 bath + Den - Logan Square - FREE M...</td>\n",
       "      <td>2</td>\n",
       "      <td>1435.0</td>\n",
       "      <td>https://chicago.craigslist.org/chc/apa/d/chica...</td>\n",
       "      <td>1795</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020-12-12 19:28</td>\n",
       "      <td>(Logan Square)</td>\n",
       "      <td>live work loft style apartment</td>\n",
       "      <td>3</td>\n",
       "      <td>950.0</td>\n",
       "      <td>https://chicago.craigslist.org/chc/apa/d/chica...</td>\n",
       "      <td>1600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020-12-12 19:20</td>\n",
       "      <td>(Chicago)</td>\n",
       "      <td>Furnished Wicker Park 1-Bedroom Coachouse!</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://chicago.craigslist.org/chc/apa/d/chica...</td>\n",
       "      <td>2150</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2020-12-12 19:07</td>\n",
       "      <td>(Lincoln Park, Chicago)</td>\n",
       "      <td>Beautiful 1 bedroom 1 bath apartment for rent ...</td>\n",
       "      <td>1</td>\n",
       "      <td>775.0</td>\n",
       "      <td>https://chicago.craigslist.org/chc/apa/d/chica...</td>\n",
       "      <td>1795</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2020-12-12 19:00</td>\n",
       "      <td>(Lincoln Park)</td>\n",
       "      <td>2704 N. Mildred Ave. Unit 2F</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://chicago.craigslist.org/chc/apa/d/chica...</td>\n",
       "      <td>2075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2020-12-12 18:57</td>\n",
       "      <td>(Old Town)</td>\n",
       "      <td>1433 N. Wells St. Unit 3F</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://chicago.craigslist.org/chc/apa/d/chica...</td>\n",
       "      <td>3095</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2020-12-12 18:56</td>\n",
       "      <td>(Lakeview)</td>\n",
       "      <td>3257 N. Sheffield Ave. Unit 302</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://chicago.craigslist.org/chc/apa/d/chica...</td>\n",
       "      <td>1695</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2020-12-12 18:55</td>\n",
       "      <td>(Ranch Triangle)</td>\n",
       "      <td>1817 N. Clybourn Ave. Unit 1</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://chicago.craigslist.org/chc/apa/d/chica...</td>\n",
       "      <td>2545</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2020-12-12 18:53</td>\n",
       "      <td>(West Loop)</td>\n",
       "      <td>123 N. Jefferson St. Unit 4R</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://chicago.craigslist.org/chc/apa/d/chica...</td>\n",
       "      <td>3995</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Posted              Neighborhood  \\\n",
       "0  2020-12-12 20:07                  (PILSEN)   \n",
       "1  2020-12-12 19:56            (Logan Square)   \n",
       "2  2020-12-12 19:28            (Logan Square)   \n",
       "3  2020-12-12 19:20                 (Chicago)   \n",
       "4  2020-12-12 19:07   (Lincoln Park, Chicago)   \n",
       "5  2020-12-12 19:00            (Lincoln Park)   \n",
       "6  2020-12-12 18:57                (Old Town)   \n",
       "7  2020-12-12 18:56                (Lakeview)   \n",
       "8  2020-12-12 18:55          (Ranch Triangle)   \n",
       "9  2020-12-12 18:53               (West Loop)   \n",
       "\n",
       "                                          Post_Title Num_Bedrooms    Sqft  \\\n",
       "0                    AMAZING 2bed/2 bath w/d in unit            2     NaN   \n",
       "1  HUGE 2 br/1 bath + Den - Logan Square - FREE M...            2  1435.0   \n",
       "2                     live work loft style apartment            3   950.0   \n",
       "3         Furnished Wicker Park 1-Bedroom Coachouse!            1     NaN   \n",
       "4  Beautiful 1 bedroom 1 bath apartment for rent ...            1   775.0   \n",
       "5                       2704 N. Mildred Ave. Unit 2F            2     NaN   \n",
       "6                          1433 N. Wells St. Unit 3F            3     NaN   \n",
       "7                    3257 N. Sheffield Ave. Unit 302            1     NaN   \n",
       "8                       1817 N. Clybourn Ave. Unit 1            3     NaN   \n",
       "9                       123 N. Jefferson St. Unit 4R            4     NaN   \n",
       "\n",
       "                                                 URL  Price  \n",
       "0  https://chicago.craigslist.org/chc/apa/d/chica...   1400  \n",
       "1  https://chicago.craigslist.org/chc/apa/d/chica...   1795  \n",
       "2  https://chicago.craigslist.org/chc/apa/d/chica...   1600  \n",
       "3  https://chicago.craigslist.org/chc/apa/d/chica...   2150  \n",
       "4  https://chicago.craigslist.org/chc/apa/d/chica...   1795  \n",
       "5  https://chicago.craigslist.org/chc/apa/d/chica...   2075  \n",
       "6  https://chicago.craigslist.org/chc/apa/d/chica...   3095  \n",
       "7  https://chicago.craigslist.org/chc/apa/d/chica...   1695  \n",
       "8  https://chicago.craigslist.org/chc/apa/d/chica...   2545  \n",
       "9  https://chicago.craigslist.org/chc/apa/d/chica...   3995  "
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "ch_apts = pd.DataFrame({'Posted': post_timing,\n",
    "                       'Neighborhood': post_hoods,\n",
    "                       'Post_Title': post_title_texts,\n",
    "                       'Num_Bedrooms': bedroom_counts,\n",
    "                        'Sqft': sqfts,\n",
    "                        'URL': post_links,\n",
    "                       'Price': post_prices})\n",
    "print(ch_apts.info())\n",
    "ch_apts.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "#export dataframe to csv file\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "TE8SXNrUXl5u"
   },
   "outputs": [],
   "source": [
    "########################DATA CLEANING\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "HTnHEt61Xl82"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "115"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Deleting duplicate postings bc people spam Craigslist with fake postings\n",
    "# the duplicate postings are most likely spam\n",
    "#Displays uniqe posts\n",
    "ch_apts = ch_apts.drop_duplicates(subset='URL')\n",
    "len(ch_apts.drop_duplicates(subset='URL'))\n",
    "\n",
    "#converts the # of bedrooms to a float (since np.nan is a float too)\n",
    "ch_apts['Num_Bedrooms'] = ch_apts['Num_Bedrooms'].apply(lambda x: float(x))\n",
    "\n",
    "#convert datetime string into datetime object to work with it\n",
    "from datetime import datetime\n",
    "ch_apts['Posted'] = pd.to_datetime(ch_apts['Posted'])\n",
    "\n",
    "#Checking neighborhoods that there are with ch_apts['neighborhood'].unique()\n",
    "#Seeing that allowed me to know what I needed to deal with in terms of cleaning those\n",
    "\n",
    "#remove the parenthesis from the left and right of the neighborhoods\n",
    "ch_apts['Neighborhood'] = ch_apts['Neighborhood'].map(lambda x: x.lstrip('(').rstrip(')'))\n",
    "\n",
    "ch_apts['Neighborhood'] = ch_apts['Neighborhood'].apply(lambda x: re.sub(r'[()]+', '', x))\n",
    "\n",
    "#titlecase them\n",
    "ch_apts['Neighborhood'] = ch_apts['Neighborhood'].str.title()\n",
    "\n",
    "#just take the first name of the neighborhood list, splitting on the '/' delimiter\n",
    "ch_apts['Neighborhood'] = ch_apts['Neighborhood'].apply(lambda x: x.split('/')[0])\n",
    "\n",
    "#fix one-offs that\n",
    "########################\n",
    "#####################\n",
    "\n",
    "#UPDATE\n",
    "###################\n",
    "########################\n",
    "#remove whitespaces\n",
    "ch_apts['Neighborhood'] = ch_apts['Neighborhood'].apply(lambda x: x.strip())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 97
    },
    "colab_type": "code",
    "id": "XgR7WxPvXmAG",
    "outputId": "b83d69e4-30a2-4f76-f20d-5e3d04716d1e"
   },
   "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>Posted</th>\n",
       "      <th>Neighborhood</th>\n",
       "      <th>Post_Title</th>\n",
       "      <th>Num_Bedrooms</th>\n",
       "      <th>Sqft</th>\n",
       "      <th>URL</th>\n",
       "      <th>Price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2020-12-12 20:07:00</td>\n",
       "      <td>Pilsen</td>\n",
       "      <td>AMAZING 2bed/2 bath w/d in unit</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://chicago.craigslist.org/chc/apa/d/chica...</td>\n",
       "      <td>1400</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               Posted Neighborhood                       Post_Title  \\\n",
       "0 2020-12-12 20:07:00       Pilsen  AMAZING 2bed/2 bath w/d in unit   \n",
       "\n",
       "   Num_Bedrooms  Sqft                                                URL  \\\n",
       "0           2.0   NaN  https://chicago.craigslist.org/chc/apa/d/chica...   \n",
       "\n",
       "   Price  \n",
       "0   1400  "
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "### EXPLORATORY DATA ANALYSIS\n",
    "#Checking first record\n",
    "ch_apts.head(1)\n",
    "ch_apts.to_csv(r'C:\\\\Users\\\\chris\\\\2020\\Craigslist_New.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Lakeview', 'West Loop', 'River North', 'Chicago',\n",
       "       'East Rogers Park', 'Logan Square', 'South Loop Mccormick Square',\n",
       "       'Portage Park', '6948 S. Talman - Chicago Lawn', 'Mckinley Park',\n",
       "       '75Th & Dan Ryan', 'Edgewater', 'West Lawn, Chicago',\n",
       "       'Lincoln Park', 'Marshall Square', 'Roscoe Village',\n",
       "       'Gold Coast - 1133 N. Dearborn', 'River North - 750 N. Rush',\n",
       "       'Gold Coast - 20 E. Scott', 'Gold Coast - 1330 N. Dearborn',\n",
       "       'River North - 100 W. Chestnut', 'Gold Coast - 1120 N. Lasalle',\n",
       "       'West Loop Chicago', 'Old Town Triangle',\n",
       "       'Mckinley Park, Chicago, Il', 'Marshall Square Chicago Il',\n",
       "       'South Douglas Park West Pilsen', 'Brickyard',\n",
       "       'Prime Brighton Park  60632', 'Pilsen', 'South Loop',\n",
       "       'Chicago, Illinois', 'Andersonville', 'Gold Coast',\n",
       "       'Lincoln Square', 'Wrigleyville', 'Auburn Gresham',\n",
       "       'Chicago Lakeview Area', 'Rogers Park', 'Bucktown', 'East Village',\n",
       "       'Edgewater - Andersonville', 'Wicker Park', 'Uptown',\n",
       "       'Chicago Bridgeport', 'Buena Park', 'Lakeview East', 'Sauganash',\n",
       "       'Midway Area', 'Streeterville', 'Loop', 'Fulton', 'Old Town',\n",
       "       'Humboldt Park', 'Andersonville, Chicago'], dtype=object)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "array(['Lakeview', 'West Loop', 'River North', 'Chicago',\n",
       "       'East Rogers Park', 'Logan Square', 'South Loop Mccormick Square',\n",
       "       'Portage Park', '6948 S. Talman - Chicago Lawn', 'Mckinley Park',\n",
       "       '75Th & Dan Ryan', 'Edgewater', 'West Lawn, Chicago',\n",
       "       'Lincoln Park', 'Marshall Square', 'Roscoe Village',\n",
       "       'Gold Coast - 1133 N. Dearborn', 'River North - 750 N. Rush',\n",
       "       'Gold Coast - 20 E. Scott', 'Gold Coast - 1330 N. Dearborn',\n",
       "       'River North - 100 W. Chestnut', 'Gold Coast - 1120 N. Lasalle',\n",
       "       'West Loop Chicago', 'Old Town Triangle',\n",
       "       'Mckinley Park, Chicago, Il', 'Marshall Square Chicago Il',\n",
       "       'South Douglas Park West Pilsen', 'Brickyard',\n",
       "       'Prime Brighton Park  60632', 'Pilsen', 'South Loop',\n",
       "       'Chicago, Illinois', 'Andersonville', 'Gold Coast',\n",
       "       'Lincoln Square', 'Wrigleyville', 'Auburn Gresham',\n",
       "       'Chicago Lakeview Area', 'Rogers Park', 'Bucktown', 'East Village',\n",
       "       'Edgewater - Andersonville', 'Wicker Park', 'Uptown',\n",
       "       'Chicago Bridgeport', 'Buena Park', 'Lakeview East', 'Sauganash',\n",
       "       'Midway Area', 'Streeterville', 'Loop', 'Fulton', 'Old Town',\n",
       "       'Humboldt Park', 'Andersonville, Chicago'], dtype=object)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Checking unique neighborhood names\n",
    "ch_apts.Neighborhood.unique()\n",
    "\n",
    "#removing listings that have addresses as listings\n",
    "ch_apts = ch_apts[(ch_apts.Neighborhood != '1624 W. Division Street Wicker Park')]\n",
    "ch_apts = ch_apts[(ch_apts.Neighborhood != '775 West Diversey Pkwy.')]\n",
    "ch_apts = ch_apts[(ch_apts.Neighborhood != '3257 W Eastwood')]\n",
    "ch_apts = ch_apts[(ch_apts.Neighborhood != '4354 N Ashland')]\n",
    "ch_apts = ch_apts[(ch_apts.Neighborhood != 'All Pets')]\n",
    "ch_apts = ch_apts[(ch_apts.Neighborhood != '3750 N. Troy Street Apt. 1')]\n",
    "ch_apts = ch_apts[(ch_apts.Neighborhood != '1550 S Hamlin  North Lawndale')]\n",
    "ch_apts = ch_apts[(ch_apts.Neighborhood != '8901 S Loomis - Brainerd Senior Center')]\n",
    "ch_apts = ch_apts[(ch_apts.Neighborhood != '1436-40 W Thorndale')]\n",
    "ch_apts = ch_apts[(ch_apts.Neighborhood != '3257 W Eastwood')]\n",
    "ch_apts = ch_apts[(ch_apts.Neighborhood != '1234 W Loyola')]\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "#(ch_apts.Neighborhood != 10)]\n",
    "\n",
    "ch_apts.Neighborhood.unique()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 1000
    },
    "colab_type": "code",
    "id": "xm8yaMzelE_J",
    "outputId": "44a8000c-67df-4648-d5a2-2572a78994f0"
   },
   "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>Posted</th>\n",
       "      <th>Neighborhood</th>\n",
       "      <th>Post_Title</th>\n",
       "      <th>Num_Bedrooms</th>\n",
       "      <th>Sqft</th>\n",
       "      <th>URL</th>\n",
       "      <th>Price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2020-12-12 18:47:00</td>\n",
       "      <td>Lakeview</td>\n",
       "      <td>3600 N. Hermitage Ave. Unit 2</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://chicago.craigslist.org/chc/apa/d/chica...</td>\n",
       "      <td>2145</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2020-12-12 18:44:00</td>\n",
       "      <td>West Loop</td>\n",
       "      <td>1501 W. Jackson St. Unit G</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://chicago.craigslist.org/chc/apa/d/chica...</td>\n",
       "      <td>1845</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020-12-12 18:37:00</td>\n",
       "      <td>River North</td>\n",
       "      <td>2 BED 2 BATH RIVER NORTH</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1300.0</td>\n",
       "      <td>https://chicago.craigslist.org/chc/apa/d/chica...</td>\n",
       "      <td>2995</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020-12-12 18:24:00</td>\n",
       "      <td>Chicago</td>\n",
       "      <td>2BD / 1BA Apartment</td>\n",
       "      <td>2.0</td>\n",
       "      <td>950.0</td>\n",
       "      <td>https://chicago.craigslist.org/chc/apa/d/chica...</td>\n",
       "      <td>1350</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2020-12-12 18:10:00</td>\n",
       "      <td>Rogers Park</td>\n",
       "      <td>Amazing duplex, best location 3bd 2bath in Rog...</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1600.0</td>\n",
       "      <td>https://chicago.craigslist.org/chc/apa/d/chica...</td>\n",
       "      <td>1995</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\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",
       "      <th>110</th>\n",
       "      <td>2020-12-12 06:17:00</td>\n",
       "      <td>Humboldt Park</td>\n",
       "      <td>Bright 1 FURNISHED Bdrm/1 Bath in Humboldt Park</td>\n",
       "      <td>1.0</td>\n",
       "      <td>725.0</td>\n",
       "      <td>https://chicago.craigslist.org/chc/apa/d/chica...</td>\n",
       "      <td>1350</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111</th>\n",
       "      <td>2020-12-12 05:21:00</td>\n",
       "      <td>West Loop</td>\n",
       "      <td>2 Bedroom 2 Bath</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://chicago.craigslist.org/chc/apa/d/chica...</td>\n",
       "      <td>2635</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112</th>\n",
       "      <td>2020-12-12 03:56:00</td>\n",
       "      <td>Chicago</td>\n",
       "      <td>3 Bedroom Ready To Move In</td>\n",
       "      <td>3.0</td>\n",
       "      <td>967.0</td>\n",
       "      <td>https://chicago.craigslist.org/chc/apa/d/chica...</td>\n",
       "      <td>850</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113</th>\n",
       "      <td>2020-12-12 00:16:00</td>\n",
       "      <td>Uptown</td>\n",
       "      <td>3 bedroom apt Edgewater/uptown</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://chicago.craigslist.org/chc/apa/d/chica...</td>\n",
       "      <td>1800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>114</th>\n",
       "      <td>2020-12-11 22:57:00</td>\n",
       "      <td>Pilsen</td>\n",
       "      <td>Artist loft three bedroom two baths</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1400.0</td>\n",
       "      <td>https://chicago.craigslist.org/chc/apa/d/chica...</td>\n",
       "      <td>1450</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>115 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                 Posted   Neighborhood  \\\n",
       "0   2020-12-12 18:47:00       Lakeview   \n",
       "1   2020-12-12 18:44:00      West Loop   \n",
       "2   2020-12-12 18:37:00    River North   \n",
       "3   2020-12-12 18:24:00        Chicago   \n",
       "4   2020-12-12 18:10:00    Rogers Park   \n",
       "..                  ...            ...   \n",
       "110 2020-12-12 06:17:00  Humboldt Park   \n",
       "111 2020-12-12 05:21:00      West Loop   \n",
       "112 2020-12-12 03:56:00        Chicago   \n",
       "113 2020-12-12 00:16:00         Uptown   \n",
       "114 2020-12-11 22:57:00         Pilsen   \n",
       "\n",
       "                                            Post_Title  Num_Bedrooms    Sqft  \\\n",
       "0                        3600 N. Hermitage Ave. Unit 2           3.0     NaN   \n",
       "1                           1501 W. Jackson St. Unit G           2.0     NaN   \n",
       "2                             2 BED 2 BATH RIVER NORTH           2.0  1300.0   \n",
       "3                                  2BD / 1BA Apartment           2.0   950.0   \n",
       "4    Amazing duplex, best location 3bd 2bath in Rog...           3.0  1600.0   \n",
       "..                                                 ...           ...     ...   \n",
       "110    Bright 1 FURNISHED Bdrm/1 Bath in Humboldt Park           1.0   725.0   \n",
       "111                                   2 Bedroom 2 Bath           2.0     NaN   \n",
       "112                         3 Bedroom Ready To Move In           3.0   967.0   \n",
       "113                     3 bedroom apt Edgewater/uptown           3.0     NaN   \n",
       "114                Artist loft three bedroom two baths           3.0  1400.0   \n",
       "\n",
       "                                                   URL  Price  \n",
       "0    https://chicago.craigslist.org/chc/apa/d/chica...   2145  \n",
       "1    https://chicago.craigslist.org/chc/apa/d/chica...   1845  \n",
       "2    https://chicago.craigslist.org/chc/apa/d/chica...   2995  \n",
       "3    https://chicago.craigslist.org/chc/apa/d/chica...   1350  \n",
       "4    https://chicago.craigslist.org/chc/apa/d/chica...   1995  \n",
       "..                                                 ...    ...  \n",
       "110  https://chicago.craigslist.org/chc/apa/d/chica...   1350  \n",
       "111  https://chicago.craigslist.org/chc/apa/d/chica...   2635  \n",
       "112  https://chicago.craigslist.org/chc/apa/d/chica...    850  \n",
       "113  https://chicago.craigslist.org/chc/apa/d/chica...   1800  \n",
       "114  https://chicago.craigslist.org/chc/apa/d/chica...   1450  \n",
       "\n",
       "[115 rows x 7 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Correcting neighborhood names\n",
    "for Post_Title in ch_apts:\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('Andersonville'), 'Neighborhood'] = 'Andersonville'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('andersonville'), 'Neighborhood'] = 'Andersonville'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('Archer Heights'), 'Neighborhood'] = 'Archer Heights'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('archer Heights'), 'Neighborhood'] = 'Archer Heights'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('Ashburn'), 'Neighborhood'] = 'Ashburn'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('ashburn'), 'Neighborhood'] = 'Ashburn'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('Austin'), 'Neighborhood'] = 'Austin'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('austin'), 'Neighborhood'] = 'Austin'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('avon'), 'Neighborhood'] = 'Avondale'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('Avon'), 'Neighborhood'] = 'Avondale'  \n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('Albany'), 'Neighborhood'] = 'Albany Park'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('albany'), 'Neighborhood'] = 'Albany Park'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('Beverly'), 'Neighborhood'] = 'Beverly'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('beverly'), 'Neighborhood'] = 'Beverly'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('buck'), 'Neighborhood'] = 'Bucktown'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('Buck'), 'Neighborhood'] = 'Bucktown'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('Boys'), 'Neighborhood'] = 'Boystown'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('boys'), 'Neighborhood'] = 'Boystown'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('China'), 'Neighborhood'] = 'Chinatown'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('china'), 'Neighborhood'] = 'Chinatown'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('Depaul'), 'Neighborhood'] = 'Depaul'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('depaul'), 'Neighborhood'] = 'Depaul'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('Edison'), 'Neighborhood'] = 'Edison Park'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('edison'), 'Neighborhood'] = 'Edison Park'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('Edgewater'), 'Neighborhood'] = 'Edgewater'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('edgewater'), 'Neighborhood'] = 'Edgewater'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('Englewood'), 'Neighborhood'] = 'Englewood'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('englewood'), 'Neighborhood'] = 'Englewood'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('Galewood'), 'Neighborhood'] = 'Galewood'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('galewood'), 'Neighborhood'] = 'Galewood'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('Garfield Park'), 'Neighborhood'] = 'Garfield Park'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('garfield Park'), 'Neighborhood'] = 'Garfield Park'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('Gold Coast'), 'Neighborhood'] = 'Gold Coast'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('gold'), 'Neighborhood'] = 'Gold Coast'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('Gresham'), 'Neighborhood'] = 'Gresham'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('gresham'), 'Neighborhood'] = 'Gresham'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('Humb'), 'Neighborhood'] = 'Humboldt Park'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('humb'), 'Neighborhood'] = 'Humboldt Park'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('Hyde'), 'Neighborhood'] = 'Hyde Park'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('hyde'), 'Neighborhood'] = 'Hyde Park'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('Jefferson'), 'Neighborhood'] = 'Jefferson Park'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('jefferson'), 'Neighborhood'] = 'Jefferson Park'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('Kenwood'), 'Neighborhood'] = 'Kenwood'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('kenwood'), 'Neighborhood'] = 'Kenwood'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('Lakeview'), 'Neighborhood'] = 'Lakeview'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('lakeview'), 'Neighborhood'] = 'Lakeview'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('Little Village'), 'Neighborhood'] = 'Little Village'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('Little village'), 'Neighborhood'] = 'Little Village'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('little village'), 'Neighborhood'] = 'Little Village'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('lil village'), 'Neighborhood'] = 'Little Village'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('Lil village'), 'Neighborhood'] = 'Little Village'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('Lincoln Park'), 'Neighborhood'] = 'Lincoln Park'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('lincoln park'), 'Neighborhood'] = 'Lincoln Park'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('Lincoln Square'), 'Neighborhood'] = 'Lincoln Square'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('lincoln square'), 'Neighborhood'] = 'Lincoln Square'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('Logan'), 'Neighborhood'] = 'Logan Square'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('logan'), 'Neighborhood'] = 'Logan Square'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('Marquette Park'), 'Neighborhood'] = 'Marquette Park'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('marquette park'), 'Neighborhood'] = 'Marquette Park'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('Midway'), 'Neighborhood'] = 'Midway'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('midway'), 'Neighborhood'] = 'Midway'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('Mount Greenwood'), 'Neighborhood'] = 'Mount Greenwood'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('mount greenwood'), 'Neighborhood'] = 'Mount Greenwood'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('Norwood'), 'Neighborhood'] = 'Norwood Park'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('norwood'), 'Neighborhood'] = 'Norwood Park'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('Irving'), 'Neighborhood'] = 'Irving Park'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('irving'), 'Neighborhood'] = 'Irving Park'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('Old Town'), 'Neighborhood'] = 'Old Town'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('old town'), 'Neighborhood'] = 'Old Town'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('Pilsen'), 'Neighborhood'] = 'Pilsen'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('pilsen'), 'Neighborhood'] = 'Pilsen'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('Portage'), 'Neighborhood'] = 'Portage Park'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('portage'), 'Neighborhood'] = 'Portage Park'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('Pullman'), 'Neighborhood'] = 'Pullman'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('pullman'), 'Neighborhood'] = 'Pullman'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('Ravens'), 'Neighborhood'] = 'Ravenswood'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('ravens'), 'Neighborhood'] = 'Ravenswood'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('River North'), 'Neighborhood'] = 'River North'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('river north'), 'Neighborhood'] = 'River North'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('River West'), 'Neighborhood'] = 'River West'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('river west'), 'Neighborhood'] = 'River West'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('Rogers'), 'Neighborhood'] = 'Rogers Park'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('rogers'), 'Neighborhood'] = 'Rogers Park'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('rodgers'), 'Neighborhood'] = 'Rogers Park'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('Roscoe Village'), 'Neighborhood'] = 'Roscoe Village'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('roscoe village'), 'Neighborhood'] = 'Roscoe Village'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('Sauganash'), 'Neighborhood'] = 'Sauganash'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('sauganash'), 'Neighborhood'] = 'Sauganash'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('South Loop'), 'Neighborhood'] = 'South Loop'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('south loop'), 'Neighborhood'] = 'South Loop'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('South Shore'), 'Neighborhood'] = 'South Shore'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('south shore'), 'Neighborhood'] = 'South Shore'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('Streeter'), 'Neighborhood'] = 'Streeterville'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('streeter'), 'Neighborhood'] = 'Streeterville'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('Uptown'), 'Neighborhood'] = 'Uptown'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('uptown'), 'Neighborhood'] = 'Uptown'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('West Loop'), 'Neighborhood'] = 'West Loop'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('west loop'), 'Neighborhood'] = 'West Loop'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('West Town'), 'Neighborhood'] = 'West Town'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('west town'), 'Neighborhood'] = 'West Town'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('Wicker'), 'Neighborhood'] = 'Wicker Park'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('wicker'), 'Neighborhood'] = 'Wicker Park'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('Wrigleyville'), 'Neighborhood'] = 'Wrigleyville'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('wrigleyville'), 'Neighborhood'] = 'Wrigleyville'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('wrigley'), 'Neighborhood'] = 'Wrigleyville'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('Ukrainian Village'), 'Neighborhood'] = 'Ukrainian Village'\n",
    "  ch_apts.loc[ch_apts['Post_Title'].str.contains('ukrainian village'), 'Neighborhood'] = 'Ukrainian Village'\n",
    "\n",
    "ch_apts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 225
    },
    "colab_type": "code",
    "id": "LoRKReDVXmDd",
    "outputId": "bc2140ee-1e95-4432-b6f2-8ec4625c4689"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 115 entries, 0 to 114\n",
      "Data columns (total 7 columns):\n",
      " #   Column        Non-Null Count  Dtype         \n",
      "---  ------        --------------  -----         \n",
      " 0   Posted        115 non-null    datetime64[ns]\n",
      " 1   Neighborhood  115 non-null    object        \n",
      " 2   Post_Title    115 non-null    object        \n",
      " 3   Num_Bedrooms  104 non-null    float64       \n",
      " 4   Sqft          40 non-null     float64       \n",
      " 5   URL           115 non-null    object        \n",
      " 6   Price         115 non-null    int64         \n",
      "dtypes: datetime64[ns](1), float64(2), int64(1), object(3)\n",
      "memory usage: 7.2+ KB\n"
     ]
    }
   ],
   "source": [
    "ch_apts.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 414
    },
    "colab_type": "code",
    "id": "fnfRnj7TXog2",
    "outputId": "e87b5fa2-e06c-4fd4-94b4-fbe196ca01e8"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'C:\\\\Users\\\\chris\\\\2020'"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd, numpy as np\n",
    "\n",
    "#get current directory\n",
    "%pwd\n",
    "\n",
    "#export dataframe to csv file\n",
    "ch_apts.to_csv(r'C:\\\\Users\\\\chris\\\\2020\\Craigslist-Data.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 115 entries, 0 to 114\n",
      "Data columns (total 8 columns):\n",
      " #   Column        Non-Null Count  Dtype  \n",
      "---  ------        --------------  -----  \n",
      " 0   Unnamed: 0    115 non-null    int64  \n",
      " 1   Posted        115 non-null    object \n",
      " 2   Neighborhood  115 non-null    object \n",
      " 3   Post_Title    115 non-null    object \n",
      " 4   Num_Bedrooms  104 non-null    float64\n",
      " 5   Sqft          40 non-null     float64\n",
      " 6   URL           115 non-null    object \n",
      " 7   Price         115 non-null    int64  \n",
      "dtypes: float64(2), int64(2), object(4)\n",
      "memory usage: 7.3+ KB\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(115, 8)"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "Index(['Unnamed: 0', 'Posted', 'Neighborhood', 'Post_Title', 'Num_Bedrooms',\n",
       "       'Sqft', 'URL', 'Price'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#use created file\n",
    "chicago_apts = pd.read_csv(\"Craigslist-Data.csv\")\n",
    "\n",
    "chicago_apts.info()\n",
    "chicago_apts.shape\n",
    "chicago_apts.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 413
    },
    "colab_type": "code",
    "id": "wUJGdnDxXo1b",
    "outputId": "998c602a-36bb-4094-aa40-5724ad331ef7",
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 720x432 with 0 Axes>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "(array([23., 27., 28., 12.,  5., 10.,  5.,  2.,  2.,  1.]),\n",
       " array([ 670. , 1052.5, 1435. , 1817.5, 2200. , 2582.5, 2965. , 3347.5,\n",
       "        3730. , 4112.5, 4495. ]),\n",
       " <a list of 10 Patch objects>)"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0, 'Price')"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Count')"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Distribution of Rent')"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#start to look at the distributions\n",
    "from matplotlib import figure\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "\n",
    "plt.figure(figsize=(10, 6))\n",
    "sns.set_style('darkgrid')\n",
    "sns.set()\n",
    "plt.hist(chicago_apts['Price'], edgecolor='black');\n",
    "plt.xlabel(\"Price\")\n",
    "plt.ylabel('Count')\n",
    "plt.title(\"Distribution of Rent\");\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x29011141388>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set(color_codes=True)\n",
    "sns.distplot(chicago_apts['Price'], color='g')\n",
    "plt.show()\n",
    "\n",
    "# Show the plot\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x29013a45b88>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x29013a45b88>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x29013a45b88>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x29013a45b88>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x29013a45b88>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x29013a45b88>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x29013a45b88>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x29013a45b88>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x29013a45b88>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x29013a45b88>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x29013a45b88>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x29013a45b88>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for p in sns.palettes.SEABORN_PALETTES:\n",
    "    sns.set_palette(p)\n",
    "    sns.distplot(chicago_apts['Sqft'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x29013c51788>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "[(350, 2100),\n",
       " Text(0.5, 0, '1 Bedroom Fair Market Rent'),\n",
       " Text(0.5, 1.0, 'US Rent')]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create a figure and axes\n",
    "fig, ax = plt.subplots()\n",
    "\n",
    "# Plot the distribution of rents\n",
    "sns.distplot(chicago_apts['Price'], ax=ax)\n",
    "\n",
    "# Modify the properties of the plot\n",
    "ax.set(xlabel=\"1 Bedroom Fair Market Rent\",\n",
    "       xlim=(350,2100),\n",
    "       title=\"US Rent\")\n",
    "\n",
    "# Display the plot\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x29013cb8f48>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "[(250, 2250),\n",
       " Text(0.5, 0, 'Sq Footage of Chicago Apts'),\n",
       " Text(0.5, 1.0, 'US Rent')]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create a figure and axes\n",
    "fig, ax = plt.subplots()\n",
    "\n",
    "# Plot the distribution of rents\n",
    "sns.distplot(chicago_apts['Sqft'], ax=ax)\n",
    "\n",
    "# Modify the properties of the plot\n",
    "ax.set(xlabel=\"Sq Footage of Chicago Apts\",\n",
    "       xlim=(250,2250),\n",
    "       title=\"US Rent\")\n",
    "\n",
    "# Display the plot\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Sqft                            420.0   450.0   500.0   508.0   600.0   \\\n",
      "Neighborhood                                                             \n",
      "6948 S. Talman - Chicago Lawn        0       0       1       0       0   \n",
      "Auburn Gresham                       0       0       0       0       0   \n",
      "Brickyard                            0       0       0       0       0   \n",
      "Bucktown                             0       0       0       0       1   \n",
      "Chicago                              0       0       0       0       0   \n",
      "Gold Coast                           0       0       0       0       0   \n",
      "Humboldt Park                        0       0       0       0       0   \n",
      "Jefferson Park                       0       0       0       0       0   \n",
      "Lincoln Park                         0       0       0       0       0   \n",
      "Logan Square                         0       1       0       0       0   \n",
      "Marshall Square                      0       0       0       1       0   \n",
      "Marshall Square Chicago Il           0       0       0       0       0   \n",
      "Mckinley Park                        0       0       0       0       0   \n",
      "Pilsen                               0       0       0       0       0   \n",
      "Prime Brighton Park  60632           0       0       0       0       0   \n",
      "River North                          0       0       0       0       0   \n",
      "Rogers Park                          1       0       0       0       0   \n",
      "Roscoe Village                       0       0       0       0       0   \n",
      "Sauganash                            0       0       0       0       0   \n",
      "South Douglas Park West Pilsen       0       0       0       0       0   \n",
      "South Loop                           0       0       0       0       0   \n",
      "South Loop Mccormick Square          0       0       0       0       0   \n",
      "West Lawn, Chicago                   0       0       0       0       0   \n",
      "West Loop                            0       0       0       0       0   \n",
      "Wicker Park                          0       0       0       0       0   \n",
      "\n",
      "Sqft                            605.0   650.0   700.0   725.0   778.0   ...  \\\n",
      "Neighborhood                                                            ...   \n",
      "6948 S. Talman - Chicago Lawn        0       0       1       0       0  ...   \n",
      "Auburn Gresham                       1       0       0       0       0  ...   \n",
      "Brickyard                            0       0       0       0       0  ...   \n",
      "Bucktown                             0       0       0       0       0  ...   \n",
      "Chicago                              0       1       0       0       0  ...   \n",
      "Gold Coast                           0       0       0       0       0  ...   \n",
      "Humboldt Park                        0       0       0       1       0  ...   \n",
      "Jefferson Park                       0       1       0       0       0  ...   \n",
      "Lincoln Park                         0       0       0       0       0  ...   \n",
      "Logan Square                         0       0       0       0       0  ...   \n",
      "Marshall Square                      0       0       0       0       0  ...   \n",
      "Marshall Square Chicago Il           0       0       0       0       0  ...   \n",
      "Mckinley Park                        0       0       1       0       0  ...   \n",
      "Pilsen                               0       0       0       0       1  ...   \n",
      "Prime Brighton Park  60632           0       0       0       0       0  ...   \n",
      "River North                          0       0       0       0       0  ...   \n",
      "Rogers Park                          0       0       0       0       0  ...   \n",
      "Roscoe Village                       0       0       0       0       0  ...   \n",
      "Sauganash                            0       0       0       0       0  ...   \n",
      "South Douglas Park West Pilsen       0       0       0       0       0  ...   \n",
      "South Loop                           0       0       0       0       0  ...   \n",
      "South Loop Mccormick Square          0       0       0       0       0  ...   \n",
      "West Lawn, Chicago                   0       0       0       0       0  ...   \n",
      "West Loop                            0       0       0       0       0  ...   \n",
      "Wicker Park                          0       0       0       0       0  ...   \n",
      "\n",
      "Sqft                            1175.0  1200.0  1250.0  1300.0  1400.0  \\\n",
      "Neighborhood                                                             \n",
      "6948 S. Talman - Chicago Lawn        0       0       0       0       0   \n",
      "Auburn Gresham                       0       0       0       0       0   \n",
      "Brickyard                            0       0       0       0       0   \n",
      "Bucktown                             0       0       1       0       0   \n",
      "Chicago                              0       0       0       0       0   \n",
      "Gold Coast                           0       0       0       0       0   \n",
      "Humboldt Park                        0       0       0       0       0   \n",
      "Jefferson Park                       0       0       0       0       0   \n",
      "Lincoln Park                         1       1       1       0       0   \n",
      "Logan Square                         0       0       0       0       0   \n",
      "Marshall Square                      0       0       0       0       0   \n",
      "Marshall Square Chicago Il           0       0       0       0       0   \n",
      "Mckinley Park                        0       0       0       0       0   \n",
      "Pilsen                               0       0       0       0       1   \n",
      "Prime Brighton Park  60632           0       0       0       0       0   \n",
      "River North                          0       0       0       1       0   \n",
      "Rogers Park                          0       0       0       0       0   \n",
      "Roscoe Village                       0       0       0       0       0   \n",
      "Sauganash                            0       0       0       0       0   \n",
      "South Douglas Park West Pilsen       0       0       0       0       0   \n",
      "South Loop                           0       0       0       0       0   \n",
      "South Loop Mccormick Square          0       0       0       0       0   \n",
      "West Lawn, Chicago                   0       0       0       0       0   \n",
      "West Loop                            0       0       0       0       0   \n",
      "Wicker Park                          0       0       0       1       0   \n",
      "\n",
      "Sqft                            1450.0  1500.0  1600.0  2200.0  2400.0  \n",
      "Neighborhood                                                            \n",
      "6948 S. Talman - Chicago Lawn        0       0       0       0       0  \n",
      "Auburn Gresham                       0       0       0       0       0  \n",
      "Brickyard                            0       0       0       0       0  \n",
      "Bucktown                             0       0       0       0       0  \n",
      "Chicago                              0       0       0       0       0  \n",
      "Gold Coast                           0       0       0       0       0  \n",
      "Humboldt Park                        0       0       0       0       0  \n",
      "Jefferson Park                       0       0       0       0       0  \n",
      "Lincoln Park                         0       0       0       0       0  \n",
      "Logan Square                         0       0       0       0       0  \n",
      "Marshall Square                      0       0       0       0       0  \n",
      "Marshall Square Chicago Il           0       0       1       0       0  \n",
      "Mckinley Park                        0       0       0       0       0  \n",
      "Pilsen                               0       1       1       0       0  \n",
      "Prime Brighton Park  60632           0       0       0       0       0  \n",
      "River North                          0       0       0       0       0  \n",
      "Rogers Park                          0       0       1       0       0  \n",
      "Roscoe Village                       0       0       0       0       1  \n",
      "Sauganash                            1       0       0       0       0  \n",
      "South Douglas Park West Pilsen       0       0       0       0       0  \n",
      "South Loop                           0       0       0       0       0  \n",
      "South Loop Mccormick Square          0       0       0       0       0  \n",
      "West Lawn, Chicago                   0       0       0       0       0  \n",
      "West Loop                            0       0       0       1       0  \n",
      "Wicker Park                          0       0       0       0       0  \n",
      "\n",
      "[25 rows x 27 columns]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x29014719dc8>"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "(array([ 0.5,  2.5,  4.5,  6.5,  8.5, 10.5, 12.5, 14.5, 16.5, 18.5, 20.5,\n",
       "        22.5, 24.5]),\n",
       " <a list of 13 Text yticklabel objects>)"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "(array([ 0.5,  1.5,  2.5,  3.5,  4.5,  5.5,  6.5,  7.5,  8.5,  9.5, 10.5,\n",
       "        11.5, 12.5, 13.5, 14.5, 15.5, 16.5, 17.5, 18.5, 19.5, 20.5, 21.5,\n",
       "        22.5, 23.5, 24.5, 25.5, 26.5]),\n",
       " <a list of 27 Text xticklabel objects>)"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create a crosstab table of the data\n",
    "pd_crosstab = pd.crosstab(chicago_apts[\"Neighborhood\"], chicago_apts[\"Sqft\"])\n",
    "print(pd_crosstab)\n",
    "# Plot a heatmap of the table\n",
    "sns.heatmap(pd_crosstab)\n",
    "# Rotate tick marks for visibility\n",
    "plt.yticks(rotation=0)\n",
    "plt.xticks(rotation=90)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "from statistics import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x29013d54188>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "[(400, 3000),\n",
       " Text(0.5, 0, 'Chicago Fair Market Rent'),\n",
       " Text(0.5, 1.0, 'Chicago Rent')]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "ename": "TypeError",
     "evalue": "'>' not supported between instances of 'float' and 'function'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-25-990c0e8e22f9>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      9\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     10\u001b[0m \u001b[1;31m# Add vertical lines for the median and mean\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 11\u001b[1;33m \u001b[0max\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0maxvline\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mmedian\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcolor\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'm'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mlabel\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'Median'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mlinestyle\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'--'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mlinewidth\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m2\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     12\u001b[0m \u001b[0max\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0maxvline\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mmean\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcolor\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'b'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mlabel\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'Mean'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mlinestyle\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'-'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mlinewidth\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m2\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     13\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\anaconda3\\lib\\site-packages\\matplotlib\\axes\\_axes.py\u001b[0m in \u001b[0;36maxvline\u001b[1;34m(self, x, ymin, ymax, **kwargs)\u001b[0m\n\u001b[0;32m    929\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_process_unit_info\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mxdata\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mkwargs\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    930\u001b[0m         \u001b[0mxx\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mconvert_xunits\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 931\u001b[1;33m         \u001b[0mscalex\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m(\u001b[0m\u001b[0mxx\u001b[0m \u001b[1;33m<\u001b[0m \u001b[0mxmin\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mor\u001b[0m \u001b[1;33m(\u001b[0m\u001b[0mxx\u001b[0m \u001b[1;33m>\u001b[0m \u001b[0mxmax\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    932\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    933\u001b[0m         \u001b[0mtrans\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_xaxis_transform\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mwhich\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'grid'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mTypeError\u001b[0m: '>' not supported between instances of 'float' and 'function'"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from statistics import *\n",
    "\n",
    "# Create figure and axes / plot\n",
    "fig, ax = plt.subplots()\n",
    "sns.distplot(chicago_apts['Price'], ax=ax)\n",
    "\n",
    "# Customize the labels and limits\n",
    "ax.set(xlabel=\"Chicago Fair Market Rent\", xlim=(400,3000), title=\"Chicago Rent\")\n",
    "\n",
    "# Add vertical lines for the median and mean\n",
    "ax.axvline(x=median, color='m', label='Median', linestyle='--', linewidth=2)\n",
    "ax.axvline(x=mean, color='b', label='Mean', linestyle='-', linewidth=2)\n",
    "\n",
    "# Show the legend and plot the data\n",
    "ax.legend()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'df' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-49-4e5935302b8b>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      4\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      5\u001b[0m \u001b[1;31m# alter df to be dataset with 2 bedrooms\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 6\u001b[1;33m \u001b[0msns\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdistplot\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdf\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'fmr_1'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0max\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0max0\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      7\u001b[0m \u001b[0max0\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mset\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mxlabel\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m\"1 Bedroom Fair Market Rent\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mxlim\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m100\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;36m1500\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      8\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mNameError\u001b[0m: name 'df' is not defined"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1080x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "##NEED TO CREATE 1 Bedroom and 2 Bedroom datasets\n",
    "# Create a plot with 1 row and 2 columns that share the y axis label\n",
    "fig, (ax0, ax1) = plt.subplots(nrows=1, ncols=2, sharey=True)\n",
    "\n",
    "# alter df to be dataset with 2 bedrooms\n",
    "sns.distplot(df['fmr_1'], ax=ax0)\n",
    "ax0.set(xlabel=\"1 Bedroom Fair Market Rent\", xlim=(100,1500))\n",
    "\n",
    "# alter df to be dataset with 2 bedrooms\n",
    "sns.distplot(df['fmr_2'], ax=ax1)\n",
    "ax1.set(xlabel=\"2 Bedroom Fair Market Rent\", xlim=(100,1500))\n",
    "\n",
    "# Display the plot\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "from matplotlib.ticker import PercentFormatter\n",
    "ax.yaxis.set_major_formatter(PercentFormatter(1.0))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 529
    },
    "colab_type": "code",
    "id": "2Eor2W_qXoz9",
    "outputId": "8af2344e-9691-4744-cc93-99c89f85aac6"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pylab as pylab\n",
    "params = {'legend.fontsize': 'x-large',\n",
    "          'figure.figsize': (15, 5),\n",
    "         'axes.labelsize': 'x-large',\n",
    "         'axes.titlesize':'x-large',\n",
    "         'xtick.labelsize':'x-large',\n",
    "         'ytick.labelsize':'x-large'}\n",
    "pylab.rcParams.update(params)\n",
    "\n",
    "plt.figure(figsize=(12, 8))\n",
    "sns.scatterplot(x='Price', y='Sqft', hue='Num_Bedrooms', palette='summer', x_jitter=True, y_jitter=True, s=100, data=ch_apts.dropna())\n",
    "plt.legend(fontsize=12)\n",
    "plt.xlabel(\"Price\", fontsize=18)\n",
    "plt.ylabel(\"Square Footage\", fontsize=18);\n",
    "plt.title(\"Price vs. Square Footage Colored by Number of Bedrooms\", fontsize=18);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 522
    },
    "colab_type": "code",
    "id": "JxFiuvMgXow_",
    "outputId": "2025d02c-67af-41b2-bda5-5b853987432d"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12, 8))\n",
    "sns.regplot(x='Price', y='Sqft', data=ch_apts.dropna());\n",
    "plt.title('Price vs. Square Footage Regression Plot');\n",
    "plt.xlabel(\"Price (USD)\");\n",
    "plt.ylabel(\"Square Feet\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 141
    },
    "colab_type": "code",
    "id": "382JUVRFXoup",
    "outputId": "02b5696c-05e2-489f-ef93-a26279be8df6"
   },
   "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>Num_Bedrooms</th>\n",
       "      <th>Sqft</th>\n",
       "      <th>Price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Num_Bedrooms</th>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.517720</td>\n",
       "      <td>0.532440</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sqft</th>\n",
       "      <td>0.51772</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.596988</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Price</th>\n",
       "      <td>0.53244</td>\n",
       "      <td>0.596988</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Num_Bedrooms      Sqft     Price\n",
       "Num_Bedrooms       1.00000  0.517720  0.532440\n",
       "Sqft               0.51772  1.000000  0.596988\n",
       "Price              0.53244  0.596988  1.000000"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#correlations of # of bedrooms, sqft and price\n",
    "ch_apts.corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 1000
    },
    "colab_type": "code",
    "id": "EVFEsr5pXosE",
    "outputId": "eb662494-eec7-4abe-9fb1-950f9487372f"
   },
   "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>Num_Bedrooms</th>\n",
       "      <th>Sqft</th>\n",
       "      <th>Price</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Neighborhood</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>6948 S. Talman - Chicago Lawn</th>\n",
       "      <td>1.500000</td>\n",
       "      <td>600.00</td>\n",
       "      <td>800.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75Th &amp; Dan Ryan</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>850.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Andersonville</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>800.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Auburn Gresham</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>605.00</td>\n",
       "      <td>750.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brickyard</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>900.00</td>\n",
       "      <td>1295.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bucktown</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>925.00</td>\n",
       "      <td>1362.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Buena Park</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>850.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Chicago</th>\n",
       "      <td>2.200000</td>\n",
       "      <td>893.40</td>\n",
       "      <td>1360.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Chicago Bridgeport</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1900.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Chicago Lakeview Area</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>998.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>East Village</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1467.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Edgewater</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1017.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Edgewater - Andersonville</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1475.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Fulton</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1350.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gold Coast</th>\n",
       "      <td>1.600000</td>\n",
       "      <td>1000.00</td>\n",
       "      <td>1924.833333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gold Coast - 1120 N. Lasalle</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1329.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gold Coast - 1330 N. Dearborn</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1260.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Humboldt Park</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>725.00</td>\n",
       "      <td>1350.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jefferson Park</th>\n",
       "      <td>2.500000</td>\n",
       "      <td>650.00</td>\n",
       "      <td>2522.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lakeview</th>\n",
       "      <td>1.900000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1849.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lincoln Park</th>\n",
       "      <td>2.100000</td>\n",
       "      <td>1118.75</td>\n",
       "      <td>2571.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lincoln Square</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1100.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Logan Square</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>675.00</td>\n",
       "      <td>1742.800000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Loop</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1300.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Marshall Square</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>508.00</td>\n",
       "      <td>950.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Marshall Square Chicago Il</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>1600.00</td>\n",
       "      <td>1800.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mckinley Park</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>700.00</td>\n",
       "      <td>1125.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mckinley Park, Chicago, Il</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1750.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Midway Area</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>675.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Old Town</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1685.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pilsen</th>\n",
       "      <td>2.600000</td>\n",
       "      <td>1319.50</td>\n",
       "      <td>1605.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Portage Park</th>\n",
       "      <td>2.666667</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1445.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Prime Brighton Park  60632</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>850.00</td>\n",
       "      <td>975.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>River North</th>\n",
       "      <td>1.600000</td>\n",
       "      <td>1300.00</td>\n",
       "      <td>2145.800000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>River North - 100 W. Chestnut</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1525.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rogers Park</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>1010.00</td>\n",
       "      <td>1435.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Roscoe Village</th>\n",
       "      <td>4.000000</td>\n",
       "      <td>2400.00</td>\n",
       "      <td>4495.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sauganash</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>1450.00</td>\n",
       "      <td>1700.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South Douglas Park West Pilsen</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>900.00</td>\n",
       "      <td>1095.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South Loop</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>900.00</td>\n",
       "      <td>1497.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South Loop Mccormick Square</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>855.00</td>\n",
       "      <td>2100.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Streeterville</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1745.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Uptown</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1262.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>West Lawn, Chicago</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>1000.00</td>\n",
       "      <td>1050.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>West Loop</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>1650.00</td>\n",
       "      <td>2438.571429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wicker Park</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>1300.00</td>\n",
       "      <td>1840.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wrigleyville</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3395.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                Num_Bedrooms     Sqft        Price\n",
       "Neighborhood                                                      \n",
       "6948 S. Talman - Chicago Lawn       1.500000   600.00   800.000000\n",
       "75Th & Dan Ryan                     3.000000      NaN   850.000000\n",
       "Andersonville                            NaN      NaN   800.000000\n",
       "Auburn Gresham                      1.000000   605.00   750.000000\n",
       "Brickyard                           2.000000   900.00  1295.000000\n",
       "Bucktown                            2.000000   925.00  1362.500000\n",
       "Buena Park                               NaN      NaN   850.000000\n",
       "Chicago                             2.200000   893.40  1360.000000\n",
       "Chicago Bridgeport                  3.000000      NaN  1900.000000\n",
       "Chicago Lakeview Area               1.000000      NaN   998.000000\n",
       "East Village                        2.000000      NaN  1467.000000\n",
       "Edgewater                           1.000000      NaN  1017.250000\n",
       "Edgewater - Andersonville           2.000000      NaN  1475.000000\n",
       "Fulton                              1.000000      NaN  1350.000000\n",
       "Gold Coast                          1.600000  1000.00  1924.833333\n",
       "Gold Coast - 1120 N. Lasalle             NaN      NaN  1329.000000\n",
       "Gold Coast - 1330 N. Dearborn       1.000000      NaN  1260.000000\n",
       "Humboldt Park                       1.000000   725.00  1350.000000\n",
       "Jefferson Park                      2.500000   650.00  2522.500000\n",
       "Lakeview                            1.900000      NaN  1849.750000\n",
       "Lincoln Park                        2.100000  1118.75  2571.500000\n",
       "Lincoln Square                      1.000000      NaN  1100.000000\n",
       "Logan Square                        2.000000   675.00  1742.800000\n",
       "Loop                                1.000000      NaN  1300.000000\n",
       "Marshall Square                     2.000000   508.00   950.000000\n",
       "Marshall Square Chicago Il          2.000000  1600.00  1800.000000\n",
       "Mckinley Park                       2.000000   700.00  1125.000000\n",
       "Mckinley Park, Chicago, Il          3.000000      NaN  1750.000000\n",
       "Midway Area                         2.000000      NaN   675.000000\n",
       "Old Town                            1.000000      NaN  1685.000000\n",
       "Pilsen                              2.600000  1319.50  1605.000000\n",
       "Portage Park                        2.666667      NaN  1445.000000\n",
       "Prime Brighton Park  60632          2.000000   850.00   975.000000\n",
       "River North                         1.600000  1300.00  2145.800000\n",
       "River North - 100 W. Chestnut       1.000000      NaN  1525.000000\n",
       "Rogers Park                         3.000000  1010.00  1435.000000\n",
       "Roscoe Village                      4.000000  2400.00  4495.000000\n",
       "Sauganash                           3.000000  1450.00  1700.000000\n",
       "South Douglas Park West Pilsen      2.000000   900.00  1095.000000\n",
       "South Loop                          1.000000   900.00  1497.500000\n",
       "South Loop Mccormick Square         2.000000   855.00  2100.000000\n",
       "Streeterville                       1.000000      NaN  1745.000000\n",
       "Uptown                              2.000000      NaN  1262.000000\n",
       "West Lawn, Chicago                  2.000000  1000.00  1050.000000\n",
       "West Loop                           2.000000  1650.00  2438.571429\n",
       "Wicker Park                         2.000000  1300.00  1840.666667\n",
       "Wrigleyville                        3.000000      NaN  3395.000000"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#group by neighborhood\n",
    "ch_apts.groupby('Neighborhood').mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 901
    },
    "colab_type": "code",
    "id": "29mw0QmmXonp",
    "outputId": "0311e2cc-1497-4959-fa79-107f4d340fa2"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Neighborhood\n",
       "Midway Area                        675.000000\n",
       "Auburn Gresham                     750.000000\n",
       "6948 S. Talman - Chicago Lawn      800.000000\n",
       "Andersonville                      800.000000\n",
       "75Th & Dan Ryan                    850.000000\n",
       "Buena Park                         850.000000\n",
       "Marshall Square                    950.000000\n",
       "Prime Brighton Park  60632         975.000000\n",
       "Chicago Lakeview Area              998.000000\n",
       "Edgewater                         1017.250000\n",
       "West Lawn, Chicago                1050.000000\n",
       "South Douglas Park West Pilsen    1095.000000\n",
       "Lincoln Square                    1100.000000\n",
       "Mckinley Park                     1125.000000\n",
       "Gold Coast - 1330 N. Dearborn     1260.000000\n",
       "Uptown                            1262.000000\n",
       "Brickyard                         1295.000000\n",
       "Loop                              1300.000000\n",
       "Gold Coast - 1120 N. Lasalle      1329.000000\n",
       "Humboldt Park                     1350.000000\n",
       "Fulton                            1350.000000\n",
       "Chicago                           1360.000000\n",
       "Bucktown                          1362.500000\n",
       "Rogers Park                       1435.000000\n",
       "Portage Park                      1445.000000\n",
       "East Village                      1467.000000\n",
       "Edgewater - Andersonville         1475.000000\n",
       "South Loop                        1497.500000\n",
       "River North - 100 W. Chestnut     1525.000000\n",
       "Pilsen                            1605.000000\n",
       "Old Town                          1685.000000\n",
       "Sauganash                         1700.000000\n",
       "Logan Square                      1742.800000\n",
       "Streeterville                     1745.000000\n",
       "Mckinley Park, Chicago, Il        1750.000000\n",
       "Marshall Square Chicago Il        1800.000000\n",
       "Wicker Park                       1840.666667\n",
       "Lakeview                          1849.750000\n",
       "Chicago Bridgeport                1900.000000\n",
       "Gold Coast                        1924.833333\n",
       "South Loop Mccormick Square       2100.000000\n",
       "River North                       2145.800000\n",
       "West Loop                         2438.571429\n",
       "Jefferson Park                    2522.500000\n",
       "Lincoln Park                      2571.500000\n",
       "Wrigleyville                      3395.000000\n",
       "Roscoe Village                    4495.000000\n",
       "Name: Price, dtype: float64"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#sort price to find cheapest\n",
    "ch_apts.groupby('Neighborhood').mean()['Price'].sort_values()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 842
    },
    "colab_type": "code",
    "id": "kuHF75vEXl3Z",
    "outputId": "275d0023-82f1-4e09-c595-2e046eb98a12"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,10))\n",
    "params = {'legend.fontsize': 'x-large',\n",
    "          'figure.figsize': (15, 5),\n",
    "         'axes.labelsize': 'x-large',\n",
    "         'axes.titlesize':'x-large',\n",
    "         'xtick.labelsize':'x-large',\n",
    "         'ytick.labelsize':'x-large'}\n",
    "pylab.rcParams.update(params)\n",
    "\n",
    "sns.boxplot(x='Neighborhood', y='Price', data=ch_apts)\n",
    "plt.xlabel(\"Neighborhood\");\n",
    "plt.xticks(rotation=75)\n",
    "plt.ylabel(\"Price USD\");\n",
    "plt.title(\"Prices by Neighborhood - Boxplots\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "HXfJa2EVXl2E"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Lakeview', 'Lincoln Park', 'West Loop', 'Gold Coast', 'Chicago']"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "############################\n",
    "############################\n",
    "# 1 bedroom apts\n",
    "###########################\n",
    "###########################\n",
    "###########################\n",
    "\n",
    "# get 5 most popular neighborhoods \n",
    "chicago_apts['Neighborhood'].value_counts()[:5].index.tolist()\n",
    "\n",
    "#break it down and do a sns barplot below with the Neighborhood hue so you can compare those different areas\n",
    "#sns.stripplot(data=chicago_apts, y=\"Price\",x=\"Num_Bedrooms\", jitter=True)\n",
    "#sns.barplot(data=chicago_apts, y= \"Price\", x=\"Num_Bedrooms\",hue=\"Neighborhood\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 115 entries, 0 to 114\n",
      "Data columns (total 8 columns):\n",
      " #   Column        Non-Null Count  Dtype  \n",
      "---  ------        --------------  -----  \n",
      " 0   Unnamed: 0    115 non-null    int64  \n",
      " 1   Posted        115 non-null    object \n",
      " 2   Neighborhood  115 non-null    object \n",
      " 3   Post_Title    115 non-null    object \n",
      " 4   Num_Bedrooms  104 non-null    float64\n",
      " 5   Sqft          40 non-null     float64\n",
      " 6   URL           115 non-null    object \n",
      " 7   Price         115 non-null    int64  \n",
      "dtypes: float64(2), int64(2), object(4)\n",
      "memory usage: 7.3+ KB\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(115, 8)"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "Index(['Unnamed: 0', 'Posted', 'Neighborhood', 'Post_Title', 'Num_Bedrooms',\n",
       "       'Sqft', 'URL', 'Price'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "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>Unnamed: 0</th>\n",
       "      <th>Posted</th>\n",
       "      <th>Neighborhood</th>\n",
       "      <th>Post_Title</th>\n",
       "      <th>Num_Bedrooms</th>\n",
       "      <th>Sqft</th>\n",
       "      <th>URL</th>\n",
       "      <th>Price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>2020-12-12 18:47:00</td>\n",
       "      <td>Lakeview</td>\n",
       "      <td>3600 N. Hermitage Ave. Unit 2</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://chicago.craigslist.org/chc/apa/d/chica...</td>\n",
       "      <td>2145</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>2020-12-12 18:44:00</td>\n",
       "      <td>West Loop</td>\n",
       "      <td>1501 W. Jackson St. Unit G</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://chicago.craigslist.org/chc/apa/d/chica...</td>\n",
       "      <td>1845</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>2020-12-12 18:37:00</td>\n",
       "      <td>River North</td>\n",
       "      <td>2 BED 2 BATH RIVER NORTH</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1300.0</td>\n",
       "      <td>https://chicago.craigslist.org/chc/apa/d/chica...</td>\n",
       "      <td>2995</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>2020-12-12 18:24:00</td>\n",
       "      <td>Chicago</td>\n",
       "      <td>2BD / 1BA Apartment</td>\n",
       "      <td>2.0</td>\n",
       "      <td>950.0</td>\n",
       "      <td>https://chicago.craigslist.org/chc/apa/d/chica...</td>\n",
       "      <td>1350</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>2020-12-12 18:10:00</td>\n",
       "      <td>Rogers Park</td>\n",
       "      <td>Amazing duplex, best location 3bd 2bath in Rog...</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1600.0</td>\n",
       "      <td>https://chicago.craigslist.org/chc/apa/d/chica...</td>\n",
       "      <td>1995</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0               Posted Neighborhood  \\\n",
       "0           0  2020-12-12 18:47:00     Lakeview   \n",
       "1           1  2020-12-12 18:44:00    West Loop   \n",
       "2           2  2020-12-12 18:37:00  River North   \n",
       "3           3  2020-12-12 18:24:00      Chicago   \n",
       "4           4  2020-12-12 18:10:00  Rogers Park   \n",
       "\n",
       "                                          Post_Title  Num_Bedrooms    Sqft  \\\n",
       "0                      3600 N. Hermitage Ave. Unit 2           3.0     NaN   \n",
       "1                         1501 W. Jackson St. Unit G           2.0     NaN   \n",
       "2                           2 BED 2 BATH RIVER NORTH           2.0  1300.0   \n",
       "3                                2BD / 1BA Apartment           2.0   950.0   \n",
       "4  Amazing duplex, best location 3bd 2bath in Rog...           3.0  1600.0   \n",
       "\n",
       "                                                 URL  Price  \n",
       "0  https://chicago.craigslist.org/chc/apa/d/chica...   2145  \n",
       "1  https://chicago.craigslist.org/chc/apa/d/chica...   1845  \n",
       "2  https://chicago.craigslist.org/chc/apa/d/chica...   2995  \n",
       "3  https://chicago.craigslist.org/chc/apa/d/chica...   1350  \n",
       "4  https://chicago.craigslist.org/chc/apa/d/chica...   1995  "
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Focusing on 1 bedroom apts\n",
    "#use created file\n",
    "chicago_apts = pd.read_csv(\"Craigslist-Data.csv\")\n",
    "\n",
    "chicago_apts.info()\n",
    "chicago_apts.shape\n",
    "chicago_apts.columns\n",
    "chicago_apts.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(39, 8)"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "one = chicago_apts[chicago_apts.Num_Bedrooms.eq(1.0)]\n",
    "one.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#start to look at the distributions\n",
    "from matplotlib import figure\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "\n",
    "plt.figure(figsize=(10, 6))\n",
    "plt.hist(one['Price'], edgecolor='black');\n",
    "plt.xlabel(\"Price\")\n",
    "plt.ylabel('Count')\n",
    "plt.title(\"Distribution of Rent for 1 bedroom Apts in Chicago\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pylab as pylab\n",
    "params = {'legend.fontsize': 'x-large',\n",
    "          'figure.figsize': (15, 5),\n",
    "         'axes.labelsize': 'x-large',\n",
    "         'axes.titlesize':'x-large',\n",
    "         'xtick.labelsize':'x-large',\n",
    "         'ytick.labelsize':'x-large'}\n",
    "pylab.rcParams.update(params)\n",
    "\n",
    "plt.figure(figsize=(12, 8))\n",
    "sns.scatterplot(x='Price', y='Sqft', hue='Num_Bedrooms', palette='summer', x_jitter=True, y_jitter=True, s=125, data=one.dropna())\n",
    "plt.legend(fontsize=12)\n",
    "plt.xlabel(\"Price\", fontsize=18)\n",
    "plt.ylabel(\"Square Footage\", fontsize=18);\n",
    "plt.title(\"Price vs. Square Footage Colored by Number of Bedrooms\", fontsize=18);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12, 8))\n",
    "sns.regplot(x='Price', y='Sqft', data=one.dropna());\n",
    "plt.title('Price vs. Square Footage Regression Plot');\n",
    "plt.xlabel(\"Price (USD)\");\n",
    "plt.ylabel(\"Square Feet\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "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>Num_Bedrooms</th>\n",
       "      <th>Sqft</th>\n",
       "      <th>Price</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Neighborhood</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>6948 S. Talman - Chicago Lawn</th>\n",
       "      <td>1.500000</td>\n",
       "      <td>600.00</td>\n",
       "      <td>800.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75Th &amp; Dan Ryan</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>850.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Andersonville</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>800.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Auburn Gresham</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>605.00</td>\n",
       "      <td>750.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brickyard</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>900.00</td>\n",
       "      <td>1295.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bucktown</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>925.00</td>\n",
       "      <td>1362.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Buena Park</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>850.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Chicago</th>\n",
       "      <td>2.200000</td>\n",
       "      <td>893.40</td>\n",
       "      <td>1360.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Chicago Bridgeport</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1900.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Chicago Lakeview Area</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>998.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>East Village</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1467.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Edgewater</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1017.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Edgewater - Andersonville</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1475.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Fulton</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1350.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gold Coast</th>\n",
       "      <td>1.600000</td>\n",
       "      <td>1000.00</td>\n",
       "      <td>1924.833333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gold Coast - 1120 N. Lasalle</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1329.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gold Coast - 1330 N. Dearborn</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1260.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Humboldt Park</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>725.00</td>\n",
       "      <td>1350.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jefferson Park</th>\n",
       "      <td>2.500000</td>\n",
       "      <td>650.00</td>\n",
       "      <td>2522.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lakeview</th>\n",
       "      <td>1.900000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1849.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lincoln Park</th>\n",
       "      <td>2.100000</td>\n",
       "      <td>1118.75</td>\n",
       "      <td>2571.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lincoln Square</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1100.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Logan Square</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>675.00</td>\n",
       "      <td>1742.800000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Loop</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1300.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Marshall Square</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>508.00</td>\n",
       "      <td>950.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Marshall Square Chicago Il</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>1600.00</td>\n",
       "      <td>1800.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mckinley Park</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>700.00</td>\n",
       "      <td>1125.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mckinley Park, Chicago, Il</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1750.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Midway Area</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>675.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Old Town</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1685.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pilsen</th>\n",
       "      <td>2.600000</td>\n",
       "      <td>1319.50</td>\n",
       "      <td>1605.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Portage Park</th>\n",
       "      <td>2.666667</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1445.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Prime Brighton Park  60632</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>850.00</td>\n",
       "      <td>975.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>River North</th>\n",
       "      <td>1.600000</td>\n",
       "      <td>1300.00</td>\n",
       "      <td>2145.800000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>River North - 100 W. Chestnut</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1525.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rogers Park</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>1010.00</td>\n",
       "      <td>1435.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Roscoe Village</th>\n",
       "      <td>4.000000</td>\n",
       "      <td>2400.00</td>\n",
       "      <td>4495.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sauganash</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>1450.00</td>\n",
       "      <td>1700.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South Douglas Park West Pilsen</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>900.00</td>\n",
       "      <td>1095.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South Loop</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>900.00</td>\n",
       "      <td>1497.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South Loop Mccormick Square</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>855.00</td>\n",
       "      <td>2100.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Streeterville</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1745.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Uptown</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1262.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>West Lawn, Chicago</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>1000.00</td>\n",
       "      <td>1050.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>West Loop</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>1650.00</td>\n",
       "      <td>2438.571429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wicker Park</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>1300.00</td>\n",
       "      <td>1840.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wrigleyville</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3395.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                Num_Bedrooms     Sqft        Price\n",
       "Neighborhood                                                      \n",
       "6948 S. Talman - Chicago Lawn       1.500000   600.00   800.000000\n",
       "75Th & Dan Ryan                     3.000000      NaN   850.000000\n",
       "Andersonville                            NaN      NaN   800.000000\n",
       "Auburn Gresham                      1.000000   605.00   750.000000\n",
       "Brickyard                           2.000000   900.00  1295.000000\n",
       "Bucktown                            2.000000   925.00  1362.500000\n",
       "Buena Park                               NaN      NaN   850.000000\n",
       "Chicago                             2.200000   893.40  1360.000000\n",
       "Chicago Bridgeport                  3.000000      NaN  1900.000000\n",
       "Chicago Lakeview Area               1.000000      NaN   998.000000\n",
       "East Village                        2.000000      NaN  1467.000000\n",
       "Edgewater                           1.000000      NaN  1017.250000\n",
       "Edgewater - Andersonville           2.000000      NaN  1475.000000\n",
       "Fulton                              1.000000      NaN  1350.000000\n",
       "Gold Coast                          1.600000  1000.00  1924.833333\n",
       "Gold Coast - 1120 N. Lasalle             NaN      NaN  1329.000000\n",
       "Gold Coast - 1330 N. Dearborn       1.000000      NaN  1260.000000\n",
       "Humboldt Park                       1.000000   725.00  1350.000000\n",
       "Jefferson Park                      2.500000   650.00  2522.500000\n",
       "Lakeview                            1.900000      NaN  1849.750000\n",
       "Lincoln Park                        2.100000  1118.75  2571.500000\n",
       "Lincoln Square                      1.000000      NaN  1100.000000\n",
       "Logan Square                        2.000000   675.00  1742.800000\n",
       "Loop                                1.000000      NaN  1300.000000\n",
       "Marshall Square                     2.000000   508.00   950.000000\n",
       "Marshall Square Chicago Il          2.000000  1600.00  1800.000000\n",
       "Mckinley Park                       2.000000   700.00  1125.000000\n",
       "Mckinley Park, Chicago, Il          3.000000      NaN  1750.000000\n",
       "Midway Area                         2.000000      NaN   675.000000\n",
       "Old Town                            1.000000      NaN  1685.000000\n",
       "Pilsen                              2.600000  1319.50  1605.000000\n",
       "Portage Park                        2.666667      NaN  1445.000000\n",
       "Prime Brighton Park  60632          2.000000   850.00   975.000000\n",
       "River North                         1.600000  1300.00  2145.800000\n",
       "River North - 100 W. Chestnut       1.000000      NaN  1525.000000\n",
       "Rogers Park                         3.000000  1010.00  1435.000000\n",
       "Roscoe Village                      4.000000  2400.00  4495.000000\n",
       "Sauganash                           3.000000  1450.00  1700.000000\n",
       "South Douglas Park West Pilsen      2.000000   900.00  1095.000000\n",
       "South Loop                          1.000000   900.00  1497.500000\n",
       "South Loop Mccormick Square         2.000000   855.00  2100.000000\n",
       "Streeterville                       1.000000      NaN  1745.000000\n",
       "Uptown                              2.000000      NaN  1262.000000\n",
       "West Lawn, Chicago                  2.000000  1000.00  1050.000000\n",
       "West Loop                           2.000000  1650.00  2438.571429\n",
       "Wicker Park                         2.000000  1300.00  1840.666667\n",
       "Wrigleyville                        3.000000      NaN  3395.000000"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#group by neighborhood\n",
    "ch_apts.groupby('Neighborhood').mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Neighborhood\n",
       "6948 S. Talman - Chicago Lawn     750.0\n",
       "Auburn Gresham                    750.0\n",
       "Chicago Lakeview Area             998.0\n",
       "Uptown                            999.0\n",
       "Jefferson Park                   1050.0\n",
       "Pilsen                           1100.0\n",
       "Lincoln Square                   1100.0\n",
       "Edgewater                        1133.0\n",
       "Wicker Park                      1195.0\n",
       "Gold Coast - 1330 N. Dearborn    1260.0\n",
       "Loop                             1300.0\n",
       "Fulton                           1350.0\n",
       "Humboldt Park                    1350.0\n",
       "South Loop                       1497.5\n",
       "River North - 100 W. Chestnut    1525.0\n",
       "Gold Coast                       1543.0\n",
       "Lakeview                         1564.5\n",
       "River North                      1642.5\n",
       "Old Town                         1685.0\n",
       "Streeterville                    1745.0\n",
       "Logan Square                     1750.0\n",
       "West Loop                        1800.0\n",
       "Chicago                          1850.0\n",
       "Lincoln Park                     1900.0\n",
       "Name: Price, dtype: float64"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#sort price to find cheapest\n",
    "one.groupby('Neighborhood').mean()['Price'].sort_values()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "sLu8ltkzXlus"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,10))\n",
    "params = {'legend.fontsize': 'x-large',\n",
    "          'figure.figsize': (15, 5),\n",
    "         'axes.labelsize': 'x-large',\n",
    "         'axes.titlesize':'x-large',\n",
    "         'xtick.labelsize':'x-large',\n",
    "         'ytick.labelsize':'x-large'}\n",
    "pylab.rcParams.update(params)\n",
    "\n",
    "sns.boxplot(x='Neighborhood', y='Price', data=one)\n",
    "plt.xlabel(\"Neighborhood\");\n",
    "plt.xticks(rotation=75)\n",
    "plt.ylabel(\"Price USD\");\n",
    "plt.title(\"Prices by Neighborhood of One Bedrooms - Boxplots\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "MMaWO5vgXlnc"
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "14HUxGXDXllp"
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "-siXGg8RXlf6"
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "colab": {
   "collapsed_sections": [],
   "name": "Welcome To Colaboratory",
   "provenance": []
  },
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}