crisp-dm-process-on-seatle-airbnb-data.ipynb

{"cells":[{"metadata":{},"cell_type":"markdown","source":"# **CRISP-DM OPERATION ON AIRBNB DATASET**\n\nTHIS NOTEBOOK SEEKS TO PERFORM CRISP-DM OPERATION ON AIRBNB DATA TO DEMONSTRATE AND SHOW HOW DATASCIENCE TECHNIQUES CAN BE SUED TO GAI NINSIGHTS INTO DATA AND ARRIVE AT A LOGICAL CONCLUSION"},{"metadata":{},"cell_type":"markdown","source":"\nCRISP-DM (Cross-Industry Standard Process for Data Mining)\n\n* Business Understanding\n\n* Data Understanding\n\n* Data Preparation\n\n* Modeling\n\n* Evaluation\n\n* Deployment"},{"metadata":{},"cell_type":"markdown","source":"## **BUSINESS UNDERSTANDING**\n\n*Airbnb, Inc. is a vacation rental online marketplace company that offers arrangement for lodging, primarily homestays, or tourism.\nThe Airbnb revenue model runs on the listings and the stays. Airbnb offers a platform where these listings and bookings are made and this is where Airbnb earns from*.\n\nTwo major sources of revenue of AirBnB\n\n**Commission from hosts:**\nEverytime someone chooses a host’s property and makes payment, Airbnb takes 10% of the payment amount as commission. This is one of the components of Airbnb fee structure.\n\n**Transaction fee from travelers:**\nWhen travelers make payment for stay they are charged a 3% fee for transaction. This amount adds to the Airbnb revenue.\n\nref:https://appinventiv.com/blog/airbnbs-business-model-and-revenue-source/#:~:text=Airbnb%20offers%20a%20platform%20where,the%20payment%20amount%20as%20commission\n\n\n\n### **So How can new host have a good start on Airbnb?**\n\nThe number of time someone chooses host's property and pays, the more income/revenue to the host \n\n1. What type of property type are most people interested in?\n\n2. What are the top 10 characteristics of listing that influence the price of listings?\n\n3. When is the best time to host a listing for booking?\n\n\n\n\n\n\n\n\n## **DATA UNDERSTANDING**\n\n\n* **listings**: including full descriptions and average review score\n\n* **calendar**: including listing id and the price and availability for that day\n\n* **reviews** : including unique id for each reviewer and detailed comments\n"},{"metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true},"cell_type":"code","source":"# This Python 3 environment comes with many helpful analytics libraries installed\n# It is defined by the kaggle/python Docker image: https://github.com/kaggle/docker-python\n# For example, here's several helpful packages to load\n\nimport numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\nfrom sklearn.linear_model import LinearRegression\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.metrics import r2_score, mean_squared_error\nfrom sklearn.preprocessing import MinMaxScaler\nfrom sklearn.utils import shuffle\n\n\nimport matplotlib.pyplot as plt\nimport seaborn as sns\n\n\nimport datetime as dt\n\n# Input data files are available in the read-only \"../input/\" directory\n# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n\nimport os\nfor dirname, _, filenames in os.walk('/kaggle/input'):\n    for filename in filenames:\n        print(os.path.join(dirname, filename))\n\n# You can write up to 20GB to the current directory (/kaggle/working/) that gets preserved as output when you create a version using \"Save & Run All\" \n# You can also write temporary files to /kaggle/temp/, but they won't be saved outside of the current session","execution_count":399,"outputs":[{"output_type":"stream","text":"/kaggle/input/seattle/calendar.csv\n/kaggle/input/seattle/listings.csv\n/kaggle/input/seattle/reviews.csv\n","name":"stdout"}]},{"metadata":{},"cell_type":"markdown","source":"## GATHER"},{"metadata":{"_uuid":"d629ff2d2480ee46fbb7e2d37f6b5fab8052498a","_cell_guid":"79c7e3d0-c299-4dcb-8224-4455121ee9b0","trusted":true},"cell_type":"code","source":"listing_df = pd.read_csv('/kaggle/input/seattle/listings.csv')\ncalender_df = pd.read_csv('/kaggle/input/seattle/calendar.csv')\nreviews_df = pd.read_csv('/kaggle/input/seattle/reviews.csv') ","execution_count":400,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"Now let's take a look at each data "},{"metadata":{},"cell_type":"markdown","source":"Listing Dataset"},{"metadata":{"trusted":true},"cell_type":"code","source":"listing_df.head()","execution_count":401,"outputs":[{"output_type":"execute_result","execution_count":401,"data":{"text/plain":"        id                           listing_url       scrape_id last_scraped  \\\n0   241032   https://www.airbnb.com/rooms/241032  20160104002432   2016-01-04   \n1   953595   https://www.airbnb.com/rooms/953595  20160104002432   2016-01-04   \n2  3308979  https://www.airbnb.com/rooms/3308979  20160104002432   2016-01-04   \n3  7421966  https://www.airbnb.com/rooms/7421966  20160104002432   2016-01-04   \n4   278830   https://www.airbnb.com/rooms/278830  20160104002432   2016-01-04   \n\n                                  name  \\\n0         Stylish Queen Anne Apartment   \n1   Bright & Airy Queen Anne Apartment   \n2  New Modern House-Amazing water view   \n3                   Queen Anne Chateau   \n4       Charming craftsman 3 bdm house   \n\n                                             summary  \\\n0                                                NaN   \n1  Chemically sensitive? We've removed the irrita...   \n2  New modern house built in 2013.  Spectacular s...   \n3  A charming apartment that sits atop Queen Anne...   \n4  Cozy family craftman house in beautiful neighb...   \n\n                                               space  \\\n0  Make your self at home in this charming one-be...   \n1  Beautiful, hypoallergenic apartment in an extr...   \n2  Our house is modern, light and fresh with a wa...   \n3                                                NaN   \n4  Cozy family craftman house in beautiful neighb...   \n\n                                         description experiences_offered  \\\n0  Make your self at home in this charming one-be...                none   \n1  Chemically sensitive? We've removed the irrita...                none   \n2  New modern house built in 2013.  Spectacular s...                none   \n3  A charming apartment that sits atop Queen Anne...                none   \n4  Cozy family craftman house in beautiful neighb...                none   \n\n                               neighborhood_overview  ... review_scores_value  \\\n0                                                NaN  ...                10.0   \n1  Queen Anne is a wonderful, truly functional vi...  ...                10.0   \n2  Upper Queen Anne is a charming neighborhood fu...  ...                10.0   \n3                                                NaN  ...                 NaN   \n4  We are in the beautiful neighborhood of Queen ...  ...                 9.0   \n\n  requires_license license jurisdiction_names instant_bookable  \\\n0                f     NaN         WASHINGTON                f   \n1                f     NaN         WASHINGTON                f   \n2                f     NaN         WASHINGTON                f   \n3                f     NaN         WASHINGTON                f   \n4                f     NaN         WASHINGTON                f   \n\n  cancellation_policy  require_guest_profile_picture  \\\n0            moderate                              f   \n1              strict                              t   \n2              strict                              f   \n3            flexible                              f   \n4              strict                              f   \n\n  require_guest_phone_verification calculated_host_listings_count  \\\n0                                f                              2   \n1                                t                              6   \n2                                f                              2   \n3                                f                              1   \n4                                f                              1   \n\n  reviews_per_month  \n0              4.07  \n1              1.48  \n2              1.15  \n3               NaN  \n4              0.89  \n\n[5 rows x 92 columns]","text/html":"<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>id</th>\n      <th>listing_url</th>\n      <th>scrape_id</th>\n      <th>last_scraped</th>\n      <th>name</th>\n      <th>summary</th>\n      <th>space</th>\n      <th>description</th>\n      <th>experiences_offered</th>\n      <th>neighborhood_overview</th>\n      <th>...</th>\n      <th>review_scores_value</th>\n      <th>requires_license</th>\n      <th>license</th>\n      <th>jurisdiction_names</th>\n      <th>instant_bookable</th>\n      <th>cancellation_policy</th>\n      <th>require_guest_profile_picture</th>\n      <th>require_guest_phone_verification</th>\n      <th>calculated_host_listings_count</th>\n      <th>reviews_per_month</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>241032</td>\n      <td>https://www.airbnb.com/rooms/241032</td>\n      <td>20160104002432</td>\n      <td>2016-01-04</td>\n      <td>Stylish Queen Anne Apartment</td>\n      <td>NaN</td>\n      <td>Make your self at home in this charming one-be...</td>\n      <td>Make your self at home in this charming one-be...</td>\n      <td>none</td>\n      <td>NaN</td>\n      <td>...</td>\n      <td>10.0</td>\n      <td>f</td>\n      <td>NaN</td>\n      <td>WASHINGTON</td>\n      <td>f</td>\n      <td>moderate</td>\n      <td>f</td>\n      <td>f</td>\n      <td>2</td>\n      <td>4.07</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>953595</td>\n      <td>https://www.airbnb.com/rooms/953595</td>\n      <td>20160104002432</td>\n      <td>2016-01-04</td>\n      <td>Bright &amp; Airy Queen Anne Apartment</td>\n      <td>Chemically sensitive? We've removed the irrita...</td>\n      <td>Beautiful, hypoallergenic apartment in an extr...</td>\n      <td>Chemically sensitive? We've removed the irrita...</td>\n      <td>none</td>\n      <td>Queen Anne is a wonderful, truly functional vi...</td>\n      <td>...</td>\n      <td>10.0</td>\n      <td>f</td>\n      <td>NaN</td>\n      <td>WASHINGTON</td>\n      <td>f</td>\n      <td>strict</td>\n      <td>t</td>\n      <td>t</td>\n      <td>6</td>\n      <td>1.48</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>3308979</td>\n      <td>https://www.airbnb.com/rooms/3308979</td>\n      <td>20160104002432</td>\n      <td>2016-01-04</td>\n      <td>New Modern House-Amazing water view</td>\n      <td>New modern house built in 2013.  Spectacular s...</td>\n      <td>Our house is modern, light and fresh with a wa...</td>\n      <td>New modern house built in 2013.  Spectacular s...</td>\n      <td>none</td>\n      <td>Upper Queen Anne is a charming neighborhood fu...</td>\n      <td>...</td>\n      <td>10.0</td>\n      <td>f</td>\n      <td>NaN</td>\n      <td>WASHINGTON</td>\n      <td>f</td>\n      <td>strict</td>\n      <td>f</td>\n      <td>f</td>\n      <td>2</td>\n      <td>1.15</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>7421966</td>\n      <td>https://www.airbnb.com/rooms/7421966</td>\n      <td>20160104002432</td>\n      <td>2016-01-04</td>\n      <td>Queen Anne Chateau</td>\n      <td>A charming apartment that sits atop Queen Anne...</td>\n      <td>NaN</td>\n      <td>A charming apartment that sits atop Queen Anne...</td>\n      <td>none</td>\n      <td>NaN</td>\n      <td>...</td>\n      <td>NaN</td>\n      <td>f</td>\n      <td>NaN</td>\n      <td>WASHINGTON</td>\n      <td>f</td>\n      <td>flexible</td>\n      <td>f</td>\n      <td>f</td>\n      <td>1</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>278830</td>\n      <td>https://www.airbnb.com/rooms/278830</td>\n      <td>20160104002432</td>\n      <td>2016-01-04</td>\n      <td>Charming craftsman 3 bdm house</td>\n      <td>Cozy family craftman house in beautiful neighb...</td>\n      <td>Cozy family craftman house in beautiful neighb...</td>\n      <td>Cozy family craftman house in beautiful neighb...</td>\n      <td>none</td>\n      <td>We are in the beautiful neighborhood of Queen ...</td>\n      <td>...</td>\n      <td>9.0</td>\n      <td>f</td>\n      <td>NaN</td>\n      <td>WASHINGTON</td>\n      <td>f</td>\n      <td>strict</td>\n      <td>f</td>\n      <td>f</td>\n      <td>1</td>\n      <td>0.89</td>\n    </tr>\n  </tbody>\n</table>\n<p>5 rows × 92 columns</p>\n</div>"},"metadata":{}}]},{"metadata":{},"cell_type":"markdown","source":"## ACCESS"},{"metadata":{"trusted":true},"cell_type":"code","source":"listing_df.columns","execution_count":402,"outputs":[{"output_type":"execute_result","execution_count":402,"data":{"text/plain":"Index(['id', 'listing_url', 'scrape_id', 'last_scraped', 'name', 'summary',\n       'space', 'description', 'experiences_offered', 'neighborhood_overview',\n       'notes', 'transit', 'thumbnail_url', 'medium_url', 'picture_url',\n       'xl_picture_url', 'host_id', 'host_url', 'host_name', 'host_since',\n       'host_location', 'host_about', 'host_response_time',\n       'host_response_rate', 'host_acceptance_rate', 'host_is_superhost',\n       'host_thumbnail_url', 'host_picture_url', 'host_neighbourhood',\n       'host_listings_count', 'host_total_listings_count',\n       'host_verifications', 'host_has_profile_pic', 'host_identity_verified',\n       'street', 'neighbourhood', 'neighbourhood_cleansed',\n       'neighbourhood_group_cleansed', 'city', 'state', 'zipcode', 'market',\n       'smart_location', 'country_code', 'country', 'latitude', 'longitude',\n       'is_location_exact', 'property_type', 'room_type', 'accommodates',\n       'bathrooms', 'bedrooms', 'beds', 'bed_type', 'amenities', 'square_feet',\n       'price', 'weekly_price', 'monthly_price', 'security_deposit',\n       'cleaning_fee', 'guests_included', 'extra_people', 'minimum_nights',\n       'maximum_nights', 'calendar_updated', 'has_availability',\n       'availability_30', 'availability_60', 'availability_90',\n       'availability_365', 'calendar_last_scraped', 'number_of_reviews',\n       'first_review', 'last_review', 'review_scores_rating',\n       'review_scores_accuracy', 'review_scores_cleanliness',\n       'review_scores_checkin', 'review_scores_communication',\n       'review_scores_location', 'review_scores_value', 'requires_license',\n       'license', 'jurisdiction_names', 'instant_bookable',\n       'cancellation_policy', 'require_guest_profile_picture',\n       'require_guest_phone_verification', 'calculated_host_listings_count',\n       'reviews_per_month'],\n      dtype='object')"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"# the shape of listing dataset : 3818 rows and 92 columns\nlisting_df.shape","execution_count":403,"outputs":[{"output_type":"execute_result","execution_count":403,"data":{"text/plain":"(3818, 92)"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"# check columns with not null values( these are the unique features that are required to every listing)\nlisting_df.columns[listing_df.isnull().sum() == 0]","execution_count":404,"outputs":[{"output_type":"execute_result","execution_count":404,"data":{"text/plain":"Index(['id', 'listing_url', 'scrape_id', 'last_scraped', 'name', 'description',\n       'experiences_offered', 'picture_url', 'host_id', 'host_url',\n       'host_verifications', 'street', 'neighbourhood_cleansed',\n       'neighbourhood_group_cleansed', 'city', 'state', 'market',\n       'smart_location', 'country_code', 'country', 'latitude', 'longitude',\n       'is_location_exact', 'room_type', 'accommodates', 'bed_type',\n       'amenities', 'price', 'guests_included', 'extra_people',\n       'minimum_nights', 'maximum_nights', 'calendar_updated',\n       'has_availability', 'availability_30', 'availability_60',\n       'availability_90', 'availability_365', 'calendar_last_scraped',\n       'number_of_reviews', 'requires_license', 'jurisdiction_names',\n       'instant_bookable', 'cancellation_policy',\n       'require_guest_profile_picture', 'require_guest_phone_verification',\n       'calculated_host_listings_count'],\n      dtype='object')"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"print(\"listing dataset has {} columns with non null values\".format(len(listing_df.columns[listing_df.isnull().sum() == 0])))","execution_count":405,"outputs":[{"output_type":"stream","text":"listing dataset has 47 columns with non null values\n","name":"stdout"}]},{"metadata":{"trusted":true},"cell_type":"code","source":"# check the dtype of the columns which are objects and floats\n\nno_object_columns=len(listing_df.select_dtypes(exclude ='float64').columns)\n\nno_float_columns=len(listing_df.select_dtypes(exclude ='object').columns)\n\n\nprint(\"there are {} number of float columns as well as {} number of object dtype columns\"\\\n      .format(no_float_columns,no_object_columns))","execution_count":406,"outputs":[{"output_type":"stream","text":"there are 30 number of float columns as well as 75 number of object dtype columns\n","name":"stdout"}]},{"metadata":{},"cell_type":"markdown","source":"Questions to answer on this dataset?\n\n* Which features contribute to higher or positive reviews. This can give us an idea as to what people realy like and what host should consider before listing?"},{"metadata":{},"cell_type":"markdown","source":"There are so many columns in this ataset but we only want to consider the features of a listings"},{"metadata":{"trusted":true},"cell_type":"code","source":"# features to consider\n\nfeatures = ['property_type', 'room_type', 'accommodates',\n       'bathrooms', 'bedrooms', 'beds', 'bed_type', 'amenities','guests_included', 'minimum_nights',\n       'maximum_nights', 'has_availability',\n       'availability_30', 'availability_60', 'availability_90',\n       'availability_365']\n\nlabel = ['review_scores_rating']","execution_count":407,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"listing_df[['review_scores_rating','review_scores_accuracy']].describe().reset_index()","execution_count":408,"outputs":[{"output_type":"execute_result","execution_count":408,"data":{"text/plain":"   index  review_scores_rating  review_scores_accuracy\n0  count           3171.000000             3160.000000\n1   mean             94.539262                9.636392\n2    std              6.606083                0.698031\n3    min             20.000000                2.000000\n4    25%             93.000000                9.000000\n5    50%             96.000000               10.000000\n6    75%             99.000000               10.000000\n7    max            100.000000               10.000000","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>index</th>\n      <th>review_scores_rating</th>\n      <th>review_scores_accuracy</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>count</td>\n      <td>3171.000000</td>\n      <td>3160.000000</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>mean</td>\n      <td>94.539262</td>\n      <td>9.636392</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>std</td>\n      <td>6.606083</td>\n      <td>0.698031</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>min</td>\n      <td>20.000000</td>\n      <td>2.000000</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>25%</td>\n      <td>93.000000</td>\n      <td>9.000000</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>50%</td>\n      <td>96.000000</td>\n      <td>10.000000</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>75%</td>\n      <td>99.000000</td>\n      <td>10.000000</td>\n    </tr>\n    <tr>\n      <th>7</th>\n      <td>max</td>\n      <td>100.000000</td>\n      <td>10.000000</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}]},{"metadata":{},"cell_type":"markdown","source":"THe minimum rating here is 20 and looks like most listings got good ratings from 25th to 75th percentile.\n\nthe review score rating reflect with the review score accuracy\n\nso we can use review score rating as a label for finding features in a listings that had very good rating\n"},{"metadata":{},"cell_type":"markdown","source":"Our next question we want to ask on thi dataset is that, What type of listing generate highested income\n\nTo get this, we have to get all listings that have been rated. Which means a host has lent it to a traveler and has paid for it.\n\nThen query the price for that listing and get the listings with highest income generated\n\nNote that air bnb charges 10% from the host for listing and 3% transaction fee from the traveler. But in this analysis we would not be adding that.\n\n**Our focus now is to get listings that people or travelers really booked and how much they paid for it and get the highest**\n\n"},{"metadata":{"trusted":true},"cell_type":"code","source":"# we would be using the listing dataset together with the reviews dataset\n\n# first select listing id's from the reviews dataset that had a review( meaning a traveler booked the listing)\n\n\n# get booked listings or listings that has been reviewed\nreviwed_listings = listing_df[listing_df.id.isin(reviews_df.listing_id)]\n\n\n# how many listings were actually reviewed\nreviwed_listings.shape[0]","execution_count":409,"outputs":[{"output_type":"execute_result","execution_count":409,"data":{"text/plain":"3191"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"# confirm the number lets see listings that werent reviewed and check their review scoure\n\nnon_reviwed_listings = listing_df[~listing_df.id.isin(reviews_df.listing_id)]\n\nnon_reviwed_listings.review_scores_rating.unique()[0]","execution_count":410,"outputs":[{"output_type":"execute_result","execution_count":410,"data":{"text/plain":"nan"},"metadata":{}}]},{"metadata":{},"cell_type":"markdown","source":"Non reviewed listings has no review scoure\n\nNow lets focus on reviewed listings"},{"metadata":{"trusted":true},"cell_type":"code","source":"# check how many unique values we have for each column\n\nreviwed_listings.describe()\nfor col in reviwed_listings.columns:\n    unique = len(reviwed_listings[col].unique())\n    print(col, \"unique({})\".format(unique) )","execution_count":411,"outputs":[{"output_type":"stream","text":"id unique(3191)\nlisting_url unique(3191)\nscrape_id unique(1)\nlast_scraped unique(1)\nname unique(3173)\nsummary unique(2888)\nspace unique(2756)\ndescription unique(3128)\nexperiences_offered unique(1)\nneighborhood_overview unique(2209)\nnotes unique(1817)\ntransit unique(2282)\nthumbnail_url unique(2931)\nmedium_url unique(2931)\npicture_url unique(3191)\nxl_picture_url unique(2931)\nhost_id unique(2303)\nhost_url unique(2303)\nhost_name unique(1289)\nhost_since unique(1268)\nhost_location unique(101)\nhost_about unique(1795)\nhost_response_time unique(5)\nhost_response_rate unique(44)\nhost_acceptance_rate unique(3)\nhost_is_superhost unique(2)\nhost_thumbnail_url unique(2299)\nhost_picture_url unique(2299)\nhost_neighbourhood unique(96)\nhost_listings_count unique(27)\nhost_total_listings_count unique(27)\nhost_verifications unique(84)\nhost_has_profile_pic unique(2)\nhost_identity_verified unique(2)\nstreet unique(1310)\nneighbourhood unique(81)\nneighbourhood_cleansed unique(87)\nneighbourhood_group_cleansed unique(17)\ncity unique(6)\nstate unique(1)\nzipcode unique(29)\nmarket unique(1)\nsmart_location unique(6)\ncountry_code unique(1)\ncountry unique(1)\nlatitude unique(3191)\nlongitude unique(3191)\nis_location_exact unique(2)\nproperty_type unique(16)\nroom_type unique(3)\naccommodates unique(15)\nbathrooms unique(13)\nbedrooms unique(9)\nbeds unique(11)\nbed_type unique(5)\namenities unique(2750)\nsquare_feet unique(47)\nprice unique(261)\nweekly_price unique(383)\nmonthly_price unique(344)\nsecurity_deposit unique(45)\ncleaning_fee unique(116)\nguests_included unique(13)\nextra_people unique(44)\nminimum_nights unique(18)\nmaximum_nights unique(68)\ncalendar_updated unique(31)\nhas_availability unique(1)\navailability_30 unique(31)\navailability_60 unique(61)\navailability_90 unique(91)\navailability_365 unique(359)\ncalendar_last_scraped unique(1)\nnumber_of_reviews unique(194)\nfirst_review unique(984)\nlast_review unique(321)\nreview_scores_rating unique(43)\nreview_scores_accuracy unique(8)\nreview_scores_cleanliness unique(9)\nreview_scores_checkin unique(9)\nreview_scores_communication unique(9)\nreview_scores_location unique(7)\nreview_scores_value unique(9)\nrequires_license unique(1)\nlicense unique(1)\njurisdiction_names unique(1)\ninstant_bookable unique(2)\ncancellation_policy unique(3)\nrequire_guest_profile_picture unique(2)\nrequire_guest_phone_verification unique(2)\ncalculated_host_listings_count unique(18)\nreviews_per_month unique(654)\n","name":"stdout"}]},{"metadata":{"trusted":true},"cell_type":"code","source":"# get rid of columns with only one unique features as this will not help us in our analysis\n\nunique_columns = reviwed_listings.columns[reviwed_listings.nunique() > 1]\nreviwed_listings = reviwed_listings[unique_columns]\n\nreviwed_listings.columns","execution_count":412,"outputs":[{"output_type":"execute_result","execution_count":412,"data":{"text/plain":"Index(['id', 'listing_url', 'name', 'summary', 'space', 'description',\n       'neighborhood_overview', 'notes', 'transit', 'thumbnail_url',\n       'medium_url', 'picture_url', 'xl_picture_url', 'host_id', 'host_url',\n       'host_name', 'host_since', 'host_location', 'host_about',\n       'host_response_time', 'host_response_rate', 'host_acceptance_rate',\n       'host_is_superhost', 'host_thumbnail_url', 'host_picture_url',\n       'host_neighbourhood', 'host_listings_count',\n       'host_total_listings_count', 'host_verifications',\n       'host_has_profile_pic', 'host_identity_verified', 'street',\n       'neighbourhood', 'neighbourhood_cleansed',\n       'neighbourhood_group_cleansed', 'city', 'zipcode', 'smart_location',\n       'latitude', 'longitude', 'is_location_exact', 'property_type',\n       'room_type', 'accommodates', 'bathrooms', 'bedrooms', 'beds',\n       'bed_type', 'amenities', 'square_feet', 'price', 'weekly_price',\n       'monthly_price', 'security_deposit', 'cleaning_fee', 'guests_included',\n       'extra_people', 'minimum_nights', 'maximum_nights', 'calendar_updated',\n       'availability_30', 'availability_60', 'availability_90',\n       'availability_365', 'number_of_reviews', 'first_review', 'last_review',\n       'review_scores_rating', 'review_scores_accuracy',\n       'review_scores_cleanliness', 'review_scores_checkin',\n       'review_scores_communication', 'review_scores_location',\n       'review_scores_value', 'instant_bookable', 'cancellation_policy',\n       'require_guest_profile_picture', 'require_guest_phone_verification',\n       'calculated_host_listings_count', 'reviews_per_month'],\n      dtype='object')"},"metadata":{}}]},{"metadata":{},"cell_type":"markdown","source":"We will not be considering all the columns in this dataset\n\nWe just want to pick the main features of a listing and see how it relates to review and pricing"},{"metadata":{"trusted":true},"cell_type":"code","source":"feature_columns = ['city', 'zipcode', 'smart_location',\n       'latitude', 'longitude', 'is_location_exact', 'property_type',\n       'room_type', 'accommodates', 'bathrooms', 'bedrooms', 'beds',\n       'bed_type', 'amenities', 'square_feet', 'price', 'weekly_price',\n       'monthly_price', 'security_deposit', 'cleaning_fee', 'guests_included',\n       'extra_people', 'minimum_nights', 'maximum_nights', 'calendar_updated',\n       'availability_30', 'availability_60', 'availability_90',\n       'availability_365', 'number_of_reviews', 'first_review', 'last_review',\n       'review_scores_rating', 'review_scores_accuracy' ]\n\nreviwed_listings = reviwed_listings[feature_columns]","execution_count":413,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"Let see the correlation of these features"},{"metadata":{},"cell_type":"markdown","source":"## VISUALIZE"},{"metadata":{"trusted":true},"cell_type":"code","source":"f, ax = plt.subplots(figsize=(10, 8))\n\nsns.heatmap(reviwed_listings.corr(), annot=True, fmt=\".1f\");","execution_count":414,"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 720x576 with 2 Axes>","image/png":"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\n"},"metadata":{"needs_background":"light"}}]},{"metadata":{},"cell_type":"markdown","source":"Numerical Features with strong correlation:\n* bedrooms\n* bathrooms\n* accomodation\n* beds\n* review_score_rating\n* review_score_accuracy\n* square_feet\n* guest_included\n\n"},{"metadata":{"trusted":true},"cell_type":"code","source":"num_features = ['accommodates', 'bathrooms', 'bedrooms', 'beds', 'square_feet',\n                'guests_included', 'availability_30', 'availability_60', 'availability_90',\n               'availability_365','review_scores_rating', 'review_scores_accuracy']\n\n\nnumerics = ['int16', 'int32', 'int64', 'float16', 'float32', 'float64']\n\n# select numeric columns we are interested in \nnumberic_df = reviwed_listings[num_features]\n\n# select categorical date\ncategorical_df = reviwed_listings[reviwed_listings.select_dtypes(exclude=numerics).columns ]\n\n# add them together\nnew_listing_df = pd.concat([categorical_df,numberic_df], axis=1)\n\nnew_listing_df.head()","execution_count":415,"outputs":[{"output_type":"execute_result","execution_count":415,"data":{"text/plain":"      city zipcode smart_location is_location_exact property_type  \\\n0  Seattle   98119    Seattle, WA                 t     Apartment   \n1  Seattle   98119    Seattle, WA                 t     Apartment   \n2  Seattle   98119    Seattle, WA                 t         House   \n4  Seattle   98119    Seattle, WA                 t         House   \n5  Seattle   98119    Seattle, WA                 t         House   \n\n         room_type  bed_type  \\\n0  Entire home/apt  Real Bed   \n1  Entire home/apt  Real Bed   \n2  Entire home/apt  Real Bed   \n4  Entire home/apt  Real Bed   \n5     Private room  Real Bed   \n\n                                           amenities    price weekly_price  \\\n0  {TV,\"Cable TV\",Internet,\"Wireless Internet\",\"A...   $85.00          NaN   \n1  {TV,Internet,\"Wireless Internet\",Kitchen,\"Free...  $150.00    $1,000.00   \n2  {TV,\"Cable TV\",Internet,\"Wireless Internet\",\"A...  $975.00          NaN   \n4  {TV,\"Cable TV\",Internet,\"Wireless Internet\",Ki...  $450.00          NaN   \n5  {\"Wireless Internet\",\"Free Parking on Premises...  $120.00      $800.00   \n\n   ... bedrooms beds square_feet guests_included availability_30  \\\n0  ...      1.0  1.0         NaN               2              14   \n1  ...      1.0  1.0         NaN               1              13   \n2  ...      5.0  7.0         NaN              10               1   \n4  ...      3.0  3.0         NaN               6              30   \n5  ...      1.0  1.0         NaN               1               0   \n\n  availability_60 availability_90  availability_365  review_scores_rating  \\\n0              41              71               346                  95.0   \n1              13              16               291                  96.0   \n2               6              17               220                  97.0   \n4              60              90               365                  92.0   \n5               0              27               302                  95.0   \n\n   review_scores_accuracy  \n0                    10.0  \n1                    10.0  \n2                    10.0  \n4                     9.0  \n5                    10.0  \n\n[5 rows x 29 columns]","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>city</th>\n      <th>zipcode</th>\n      <th>smart_location</th>\n      <th>is_location_exact</th>\n      <th>property_type</th>\n      <th>room_type</th>\n      <th>bed_type</th>\n      <th>amenities</th>\n      <th>price</th>\n      <th>weekly_price</th>\n      <th>...</th>\n      <th>bedrooms</th>\n      <th>beds</th>\n      <th>square_feet</th>\n      <th>guests_included</th>\n      <th>availability_30</th>\n      <th>availability_60</th>\n      <th>availability_90</th>\n      <th>availability_365</th>\n      <th>review_scores_rating</th>\n      <th>review_scores_accuracy</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>Seattle</td>\n      <td>98119</td>\n      <td>Seattle, WA</td>\n      <td>t</td>\n      <td>Apartment</td>\n      <td>Entire home/apt</td>\n      <td>Real Bed</td>\n      <td>{TV,\"Cable TV\",Internet,\"Wireless Internet\",\"A...</td>\n      <td>$85.00</td>\n      <td>NaN</td>\n      <td>...</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>NaN</td>\n      <td>2</td>\n      <td>14</td>\n      <td>41</td>\n      <td>71</td>\n      <td>346</td>\n      <td>95.0</td>\n      <td>10.0</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>Seattle</td>\n      <td>98119</td>\n      <td>Seattle, WA</td>\n      <td>t</td>\n      <td>Apartment</td>\n      <td>Entire home/apt</td>\n      <td>Real Bed</td>\n      <td>{TV,Internet,\"Wireless Internet\",Kitchen,\"Free...</td>\n      <td>$150.00</td>\n      <td>$1,000.00</td>\n      <td>...</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>NaN</td>\n      <td>1</td>\n      <td>13</td>\n      <td>13</td>\n      <td>16</td>\n      <td>291</td>\n      <td>96.0</td>\n      <td>10.0</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>Seattle</td>\n      <td>98119</td>\n      <td>Seattle, WA</td>\n      <td>t</td>\n      <td>House</td>\n      <td>Entire home/apt</td>\n      <td>Real Bed</td>\n      <td>{TV,\"Cable TV\",Internet,\"Wireless Internet\",\"A...</td>\n      <td>$975.00</td>\n      <td>NaN</td>\n      <td>...</td>\n      <td>5.0</td>\n      <td>7.0</td>\n      <td>NaN</td>\n      <td>10</td>\n      <td>1</td>\n      <td>6</td>\n      <td>17</td>\n      <td>220</td>\n      <td>97.0</td>\n      <td>10.0</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>Seattle</td>\n      <td>98119</td>\n      <td>Seattle, WA</td>\n      <td>t</td>\n      <td>House</td>\n      <td>Entire home/apt</td>\n      <td>Real Bed</td>\n      <td>{TV,\"Cable TV\",Internet,\"Wireless Internet\",Ki...</td>\n      <td>$450.00</td>\n      <td>NaN</td>\n      <td>...</td>\n      <td>3.0</td>\n      <td>3.0</td>\n      <td>NaN</td>\n      <td>6</td>\n      <td>30</td>\n      <td>60</td>\n      <td>90</td>\n      <td>365</td>\n      <td>92.0</td>\n      <td>9.0</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>Seattle</td>\n      <td>98119</td>\n      <td>Seattle, WA</td>\n      <td>t</td>\n      <td>House</td>\n      <td>Private room</td>\n      <td>Real Bed</td>\n      <td>{\"Wireless Internet\",\"Free Parking on Premises...</td>\n      <td>$120.00</td>\n      <td>$800.00</td>\n      <td>...</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>NaN</td>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n      <td>27</td>\n      <td>302</td>\n      <td>95.0</td>\n      <td>10.0</td>\n    </tr>\n  </tbody>\n</table>\n<p>5 rows × 29 columns</p>\n</div>"},"metadata":{}}]},{"metadata":{},"cell_type":"markdown","source":"Lets now get more insight into the data\n\n"},{"metadata":{},"cell_type":"markdown","source":"## ANALYZE"},{"metadata":{"trusted":true},"cell_type":"code","source":"plt_data = new_listing_df.groupby(['accommodates', 'bathrooms', 'bedrooms', 'beds'])['review_scores_rating'].sum().reset_index()\nplt_data","execution_count":416,"outputs":[{"output_type":"execute_result","execution_count":416,"data":{"text/plain":"     accommodates  bathrooms  bedrooms  beds  review_scores_rating\n0               1        0.5       1.0   1.0                 883.0\n1               1        1.0       0.0   1.0                  80.0\n2               1        1.0       1.0   1.0               12357.0\n3               1        1.5       1.0   1.0                1321.0\n4               1        2.0       1.0   1.0                 929.0\n..            ...        ...       ...   ...                   ...\n289            15        4.0       4.0   7.0                  97.0\n290            16        2.0       6.0   9.0                  97.0\n291            16        3.5       4.0  10.0                  95.0\n292            16        3.5       6.0  15.0                  98.0\n293            16        4.0       7.0  10.0                 100.0\n\n[294 rows x 5 columns]","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>accommodates</th>\n      <th>bathrooms</th>\n      <th>bedrooms</th>\n      <th>beds</th>\n      <th>review_scores_rating</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>1</td>\n      <td>0.5</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>883.0</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>1</td>\n      <td>1.0</td>\n      <td>0.0</td>\n      <td>1.0</td>\n      <td>80.0</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>1</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>12357.0</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>1</td>\n      <td>1.5</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1321.0</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>1</td>\n      <td>2.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>929.0</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>289</th>\n      <td>15</td>\n      <td>4.0</td>\n      <td>4.0</td>\n      <td>7.0</td>\n      <td>97.0</td>\n    </tr>\n    <tr>\n      <th>290</th>\n      <td>16</td>\n      <td>2.0</td>\n      <td>6.0</td>\n      <td>9.0</td>\n      <td>97.0</td>\n    </tr>\n    <tr>\n      <th>291</th>\n      <td>16</td>\n      <td>3.5</td>\n      <td>4.0</td>\n      <td>10.0</td>\n      <td>95.0</td>\n    </tr>\n    <tr>\n      <th>292</th>\n      <td>16</td>\n      <td>3.5</td>\n      <td>6.0</td>\n      <td>15.0</td>\n      <td>98.0</td>\n    </tr>\n    <tr>\n      <th>293</th>\n      <td>16</td>\n      <td>4.0</td>\n      <td>7.0</td>\n      <td>10.0</td>\n      <td>100.0</td>\n    </tr>\n  </tbody>\n</table>\n<p>294 rows × 5 columns</p>\n</div>"},"metadata":{}}]},{"metadata":{},"cell_type":"markdown","source":"## VISUALIZE"},{"metadata":{"trusted":true},"cell_type":"code","source":"f, ax = plt.subplots(figsize=(8, 6))\nsns.lineplot(  y=\"review_scores_rating\", x= \"accommodates\", data=plt_data);","execution_count":417,"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 576x432 with 1 Axes>","image/png":"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\n"},"metadata":{"needs_background":"light"}}]},{"metadata":{},"cell_type":"markdown","source":"The lower the number people allowed for accomodation, the higher the review score\n\nWe can also see that there are nun values in the data but "},{"metadata":{"trusted":true},"cell_type":"code","source":"f, ax = plt.subplots(figsize=(8, 6))\nsns.lineplot(  y=\"review_scores_rating\", x= \"beds\", data=plt_data);","execution_count":418,"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 576x432 with 1 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\n"},"metadata":{"needs_background":"light"}}]},{"metadata":{},"cell_type":"markdown","source":"The same is true for this too. the lower the listing bed number, the higher the review score\n\nLet's take a look at the bedrooms"},{"metadata":{"trusted":true},"cell_type":"code","source":"\nf, ax = plt.subplots(figsize=(8, 6))\nsns.lineplot(  y=\"review_scores_rating\", x= \"bedrooms\", data=plt_data);\n","execution_count":419,"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 576x432 with 1 Axes>","image/png":"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\n"},"metadata":{"needs_background":"light"}}]},{"metadata":{},"cell_type":"markdown","source":"Same here. Looks like Most people are interested with listings with fewer bedrooms, beds, bathrooms and accomodation number.\n\nThis shows that most people book homes for only themselves or just two or 3 people.\n\n"},{"metadata":{},"cell_type":"markdown","source":"Now lets see which property type had the highest sum of review score\n\n"},{"metadata":{},"cell_type":"markdown","source":"## ANALYSE"},{"metadata":{"trusted":true},"cell_type":"code","source":"prop_data = new_listing_df.groupby(['property_type'], sort=True)['review_scores_rating'].sum().reset_index()\nprop_data","execution_count":420,"outputs":[{"output_type":"execute_result","execution_count":420,"data":{"text/plain":"      property_type  review_scores_rating\n0         Apartment              134200.0\n1   Bed & Breakfast                2489.0\n2              Boat                 478.0\n3          Bungalow                 879.0\n4             Cabin                2021.0\n5         Camper/RV                 957.0\n6            Chalet                 167.0\n7       Condominium                6577.0\n8              Dorm                 180.0\n9             House              138457.0\n10             Loft                3150.0\n11            Other                1829.0\n12             Tent                 378.0\n13        Townhouse                7730.0\n14        Treehouse                 192.0\n15             Yurt                 100.0","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>property_type</th>\n      <th>review_scores_rating</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>Apartment</td>\n      <td>134200.0</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>Bed &amp; Breakfast</td>\n      <td>2489.0</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>Boat</td>\n      <td>478.0</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>Bungalow</td>\n      <td>879.0</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>Cabin</td>\n      <td>2021.0</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>Camper/RV</td>\n      <td>957.0</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>Chalet</td>\n      <td>167.0</td>\n    </tr>\n    <tr>\n      <th>7</th>\n      <td>Condominium</td>\n      <td>6577.0</td>\n    </tr>\n    <tr>\n      <th>8</th>\n      <td>Dorm</td>\n      <td>180.0</td>\n    </tr>\n    <tr>\n      <th>9</th>\n      <td>House</td>\n      <td>138457.0</td>\n    </tr>\n    <tr>\n      <th>10</th>\n      <td>Loft</td>\n      <td>3150.0</td>\n    </tr>\n    <tr>\n      <th>11</th>\n      <td>Other</td>\n      <td>1829.0</td>\n    </tr>\n    <tr>\n      <th>12</th>\n      <td>Tent</td>\n      <td>378.0</td>\n    </tr>\n    <tr>\n      <th>13</th>\n      <td>Townhouse</td>\n      <td>7730.0</td>\n    </tr>\n    <tr>\n      <th>14</th>\n      <td>Treehouse</td>\n      <td>192.0</td>\n    </tr>\n    <tr>\n      <th>15</th>\n      <td>Yurt</td>\n      <td>100.0</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}]},{"metadata":{},"cell_type":"markdown","source":"## VISUALIZE"},{"metadata":{"trusted":true},"cell_type":"code","source":"f, ax = plt.subplots(figsize=(10, 8))\nsns.barplot(data=prop_data, x=\"review_scores_rating\", y=\"property_type\", orient=\"h\");\n\nplt.title('What Property Type are Most Travelers Interested In?')\nplt.xlabel('People')\nplt.ylabel('Property Type')\n# Hide the right and top spines\nax.spines['right'].set_visible(False)\nax.spines['top'].set_visible(False)\n","execution_count":421,"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 720x576 with 1 Axes>","image/png":"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\n"},"metadata":{"needs_background":"light"}}]},{"metadata":{},"cell_type":"markdown","source":"House and Apartment were the property types that a higher sum of review score\n\nThis is telling us that people are interested in both house and apartment property type"},{"metadata":{},"cell_type":"markdown","source":"Next we want to find out what choice listing generated a lot or income or that most people paid for "},{"metadata":{"trusted":true},"cell_type":"code","source":"new_listing_df.price = new_listing_df.price.replace('[\\$,]', '', regex=True).astype(float)","execution_count":422,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## ANALYZE"},{"metadata":{"trusted":true},"cell_type":"code","source":"\nprice_df = new_listing_df.groupby(['property_type'],\n                       sort=True)['price'].sum().reset_index()\nprice_df","execution_count":423,"outputs":[{"output_type":"execute_result","execution_count":423,"data":{"text/plain":"      property_type     price\n0         Apartment  178342.0\n1   Bed & Breakfast    2448.0\n2              Boat    1785.0\n3          Bungalow     884.0\n4             Cabin    2198.0\n5         Camper/RV     826.0\n6            Chalet     197.0\n7       Condominium   10273.0\n8              Dorm      79.0\n9             House  191345.0\n10             Loft    4678.0\n11            Other    1870.0\n12             Tent     220.0\n13        Townhouse   10078.0\n14        Treehouse     248.0\n15             Yurt     100.0","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>property_type</th>\n      <th>price</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>Apartment</td>\n      <td>178342.0</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>Bed &amp; Breakfast</td>\n      <td>2448.0</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>Boat</td>\n      <td>1785.0</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>Bungalow</td>\n      <td>884.0</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>Cabin</td>\n      <td>2198.0</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>Camper/RV</td>\n      <td>826.0</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>Chalet</td>\n      <td>197.0</td>\n    </tr>\n    <tr>\n      <th>7</th>\n      <td>Condominium</td>\n      <td>10273.0</td>\n    </tr>\n    <tr>\n      <th>8</th>\n      <td>Dorm</td>\n      <td>79.0</td>\n    </tr>\n    <tr>\n      <th>9</th>\n      <td>House</td>\n      <td>191345.0</td>\n    </tr>\n    <tr>\n      <th>10</th>\n      <td>Loft</td>\n      <td>4678.0</td>\n    </tr>\n    <tr>\n      <th>11</th>\n      <td>Other</td>\n      <td>1870.0</td>\n    </tr>\n    <tr>\n      <th>12</th>\n      <td>Tent</td>\n      <td>220.0</td>\n    </tr>\n    <tr>\n      <th>13</th>\n      <td>Townhouse</td>\n      <td>10078.0</td>\n    </tr>\n    <tr>\n      <th>14</th>\n      <td>Treehouse</td>\n      <td>248.0</td>\n    </tr>\n    <tr>\n      <th>15</th>\n      <td>Yurt</td>\n      <td>100.0</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}]},{"metadata":{},"cell_type":"markdown","source":"## VISUALIZE"},{"metadata":{"trusted":true},"cell_type":"code","source":"\nf, ax = plt.subplots(figsize=(8, 6))\nsns.barplot(data=price_df, x=\"price\", y=\"property_type\", orient=\"h\");","execution_count":424,"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 576x432 with 1 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\n"},"metadata":{"needs_background":"light"}}]},{"metadata":{},"cell_type":"markdown","source":"The interest drives income as we can see from the chart"},{"metadata":{"trusted":true},"cell_type":"code","source":"# lets take a look at the distribution of price\n\nnew_listing_df.price.hist(bins=10)","execution_count":425,"outputs":[{"output_type":"execute_result","execution_count":425,"data":{"text/plain":"<matplotlib.axes._subplots.AxesSubplot at 0x7f94ac19bd90>"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"<Figure size 432x288 with 1 Axes>","image/png":"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\n"},"metadata":{"needs_background":"light"}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"# add log filter to the price and visualize\n\ndef plot_loghist(x, bins):\n    '''\n    INPUT:\n         x: the array list or data to plot\n         \n         bins: an integer value indicating the number of bins for the histogram\n    \n    OUTPUT:\n          Return a logged scaled histogram  \n    '''\n    \n    hist, bins = np.histogram(x, bins=bins)\n    logbins = np.logspace(np.log10(bins[0]),np.log10(bins[-1]),len(bins))\n    plt.hist(x, bins=logbins)\n    plt.xscale('log')\n\nplot_loghist(new_listing_df.price, 10)","execution_count":426,"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 432x288 with 1 Axes>","image/png":"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\n"},"metadata":{"needs_background":"light"}}]},{"metadata":{},"cell_type":"markdown","source":"the distribution looks right skewed"},{"metadata":{},"cell_type":"markdown","source":"## ANALYZE"},{"metadata":{"trusted":true},"cell_type":"code","source":"# the mean price for all listings\n\nnew_listing_df.price.sort_values(ascending=True).reset_index().mean()['price']","execution_count":427,"outputs":[{"output_type":"execute_result","execution_count":427,"data":{"text/plain":"127.09840175493575"},"metadata":{}}]},{"metadata":{},"cell_type":"markdown","source":"\n\nChecking out Calender dataset"},{"metadata":{},"cell_type":"markdown","source":"## ASSESS"},{"metadata":{"trusted":true},"cell_type":"code","source":"calender_df.head()","execution_count":428,"outputs":[{"output_type":"execute_result","execution_count":428,"data":{"text/plain":"   listing_id        date available   price\n0      241032  2016-01-04         t  $85.00\n1      241032  2016-01-05         t  $85.00\n2      241032  2016-01-06         f     NaN\n3      241032  2016-01-07         f     NaN\n4      241032  2016-01-08         f     NaN","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>listing_id</th>\n      <th>date</th>\n      <th>available</th>\n      <th>price</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>241032</td>\n      <td>2016-01-04</td>\n      <td>t</td>\n      <td>$85.00</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>241032</td>\n      <td>2016-01-05</td>\n      <td>t</td>\n      <td>$85.00</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>241032</td>\n      <td>2016-01-06</td>\n      <td>f</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>241032</td>\n      <td>2016-01-07</td>\n      <td>f</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>241032</td>\n      <td>2016-01-08</td>\n      <td>f</td>\n      <td>NaN</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"# the shape of calender dataset : 1393570 rows and 4 columns\ncalender_df.shape","execution_count":429,"outputs":[{"output_type":"execute_result","execution_count":429,"data":{"text/plain":"(1393570, 4)"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"# check columns with not null values\ncalender_df.columns[calender_df.isnull().sum() == 0]","execution_count":430,"outputs":[{"output_type":"execute_result","execution_count":430,"data":{"text/plain":"Index(['listing_id', 'date', 'available'], dtype='object')"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"# check the dtypes\n\ncalender_df.dtypes","execution_count":431,"outputs":[{"output_type":"execute_result","execution_count":431,"data":{"text/plain":"listing_id     int64\ndate          object\navailable     object\nprice         object\ndtype: object"},"metadata":{}}]},{"metadata":{},"cell_type":"markdown","source":"Questions to ask on this dataset\n\nwhat does the *f and t* in the available column  stands for and how does it affect other columns?\n\nwhich dates or times are have higest prices?\n\nwhat is the trend in pricing?"},{"metadata":{"trusted":true},"cell_type":"code","source":"# perhaps t stands for true and f for false \ncalender_df['available'].unique()","execution_count":432,"outputs":[{"output_type":"execute_result","execution_count":432,"data":{"text/plain":"array(['t', 'f'], dtype=object)"},"metadata":{}}]},{"metadata":{},"cell_type":"markdown","source":"how does available column relate to price column\n\nas we have seen, we know that the available column does not containy any null values wereas the price columns does have some null values"},{"metadata":{"trusted":true},"cell_type":"code","source":"# select rows with f[false] availability values and check their label for price\n\ncalender_df[calender_df['available'] == 'f']['price'].unique()","execution_count":433,"outputs":[{"output_type":"execute_result","execution_count":433,"data":{"text/plain":"array([nan], dtype=object)"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"# select rows with t[true] availability values and check their label for price\ncalender_df[calender_df['available'] == 't']['price'].unique()","execution_count":434,"outputs":[{"output_type":"execute_result","execution_count":434,"data":{"text/plain":"array(['$85.00', '$125.00', '$154.00', '$164.00', '$165.00', '$150.00',\n       '$145.00', '$144.00', '$148.00', '$155.00', '$149.00', '$156.00',\n       '$166.00', '$152.00', '$147.00', '$146.00', '$151.00', '$158.00',\n       '$168.00', '$169.00', '$192.00', '$175.00', '$162.00', '$171.00',\n       '$173.00', '$153.00', '$177.00', '$183.00', '$181.00', '$170.00',\n       '$179.00', '$167.00', '$184.00', '$186.00', '$172.00', '$180.00',\n       '$190.00', '$178.00', '$196.00', '$197.00', '$202.00', '$198.00',\n       '$205.00', '$214.00', '$218.00', '$211.00', '$193.00', '$204.00',\n       '$189.00', '$187.00', '$194.00', '$185.00', '$206.00', '$191.00',\n       '$207.00', '$208.00', '$188.00', '$200.00', '$209.00', '$210.00',\n       '$195.00', '$201.00', '$199.00', '$203.00', '$182.00', '$163.00',\n       '$159.00', '$157.00', '$142.00', '$136.00', '$134.00', '$137.00',\n       '$143.00', '$135.00', '$141.00', '$130.00', '$138.00', '$133.00',\n       '$129.00', '$127.00', '$126.00', '$131.00', '$132.00', '$220.00',\n       '$222.00', '$223.00', '$232.00', '$217.00', '$229.00', '$294.00',\n       '$358.00', '$439.00', '$400.00', '$975.00', '$750.00', '$500.00',\n       '$650.00', '$675.00', '$1,250.00', '$1,450.00', '$1,650.00',\n       '$100.00', '$600.00', '$450.00', '$475.00', '$120.00', '$140.00',\n       '$80.00', '$42.00', '$49.00', '$60.00', '$48.00', '$47.00',\n       '$52.00', '$51.00', '$50.00', '$53.00', '$61.00', '$54.00',\n       '$62.00', '$55.00', '$90.00', '$139.00', '$95.00', '$69.00',\n       '$71.00', '$74.00', '$81.00', '$84.00', '$76.00', '$82.00',\n       '$86.00', '$83.00', '$89.00', '$88.00', '$72.00', '$99.00',\n       '$245.00', '$98.00', '$103.00', '$104.00', '$112.00', '$122.00',\n       '$115.00', '$118.00', '$117.00', '$124.00', '$119.00', '$250.00',\n       '$399.00', '$549.00', '$468.00', '$419.00', '$420.00', '$455.00',\n       '$514.00', '$547.00', '$571.00', '$627.00', '$665.00', '$654.00',\n       '$590.00', '$581.00', '$579.00', '$589.00', '$629.00', '$640.00',\n       '$611.00', '$584.00', '$570.00', '$551.00', '$530.00', '$594.00',\n       '$614.00', '$604.00', '$602.00', '$612.00', '$649.00', '$655.00',\n       '$638.00', '$625.00', '$616.00', '$613.00', '$633.00', '$656.00',\n       '$642.00', '$636.00', '$644.00', '$630.00', '$621.00', '$800.00',\n       '$461.00', '$109.00', '$56.00', '$57.00', '$58.00', '$59.00',\n       '$63.00', '$64.00', '$65.00', '$67.00', '$75.00', '$66.00',\n       '$700.00', '$110.00', '$310.00', '$312.00', '$315.00', '$321.00',\n       '$550.00', '$43.00', '$45.00', '$44.00', '$46.00', '$280.00',\n       '$300.00', '$325.00', '$350.00', '$375.00', '$161.00', '$174.00',\n       '$176.00', '$226.00', '$213.00', '$212.00', '$221.00', '$225.00',\n       '$216.00', '$227.00', '$231.00', '$236.00', '$240.00', '$251.00',\n       '$254.00', '$255.00', '$246.00', '$248.00', '$230.00', '$235.00',\n       '$238.00', '$215.00', '$237.00', '$228.00', '$242.00', '$224.00',\n       '$241.00', '$244.00', '$233.00', '$243.00', '$234.00', '$247.00',\n       '$239.00', '$219.00', '$160.00', '$128.00', '$257.00', '$259.00',\n       '$261.00', '$272.00', '$252.00', '$320.00', '$402.00', '$445.00',\n       '$501.00', '$452.00', '$249.00', '$395.00', '$108.00', '$285.00',\n       '$113.00', '$348.00', '$91.00', '$92.00', '$97.00', '$93.00',\n       '$94.00', '$96.00', '$102.00', '$105.00', '$111.00', '$106.00',\n       '$114.00', '$121.00', '$116.00', '$123.00', '$1,240.00', '$349.00',\n       '$449.00', '$20.00', '$70.00', '$68.00', '$73.00', '$79.00',\n       '$77.00', '$78.00', '$334.00', '$341.00', '$369.00', '$385.00',\n       '$430.00', '$441.00', '$398.00', '$357.00', '$364.00', '$362.00',\n       '$371.00', '$438.00', '$378.00', '$401.00', '$444.00', '$403.00',\n       '$373.00', '$367.00', '$384.00', '$409.00', '$448.00', '$456.00',\n       '$414.00', '$470.00', '$386.00', '$428.00', '$467.00', '$425.00',\n       '$392.00', '$404.00', '$432.00', '$480.00', '$391.00', '$405.00',\n       '$477.00', '$483.00', '$412.00', '$485.00', '$493.00', '$442.00',\n       '$423.00', '$496.00', '$502.00', '$464.00', '$433.00', '$427.00',\n       '$474.00', '$525.00', '$536.00', '$465.00', '$437.00', '$473.00',\n       '$494.00', '$531.00', '$592.00', '$607.00', '$523.00', '$546.00',\n       '$572.00', '$595.00', '$634.00', '$693.00', '$709.00', '$598.00',\n       '$624.00', '$657.00', '$695.00', '$666.00', '$619.00', '$609.00',\n       '$631.00', '$670.00', '$735.00', '$745.00', '$669.00', '$683.00',\n       '$751.00', '$759.00', '$685.00', '$698.00', '$780.00', '$794.00',\n       '$652.00', '$674.00', '$743.00', '$662.00', '$622.00', '$668.00',\n       '$724.00', '$716.00', '$722.00', '$686.00', '$637.00', '$626.00',\n       '$643.00', '$737.00', '$744.00', '$663.00', '$620.00', '$608.00',\n       '$639.00', '$593.00', '$574.00', '$39.00', '$31.00', '$30.00',\n       '$33.00', '$40.00', '$38.00', '$41.00', '$25.00', '$282.00',\n       '$339.00', '$390.00', '$355.00', '$107.00', '$275.00', '$35.00',\n       '$34.00', '$273.00', '$293.00', '$260.00', '$302.00', '$266.00',\n       '$267.00', '$291.00', '$271.00', '$258.00', '$269.00', '$301.00',\n       '$308.00', '$278.00', '$276.00', '$309.00', '$253.00', '$279.00',\n       '$313.00', '$264.00', '$286.00', '$289.00', '$268.00', '$331.00',\n       '$270.00', '$299.00', '$329.00', '$297.00', '$274.00', '$332.00',\n       '$288.00', '$306.00', '$340.00', '$346.00', '$296.00', '$314.00',\n       '$324.00', '$303.00', '$376.00', '$290.00', '$330.00', '$345.00',\n       '$424.00', '$365.00', '$382.00', '$416.00', '$443.00', '$489.00',\n       '$422.00', '$436.00', '$459.00', '$486.00', '$466.00', '$426.00',\n       '$515.00', '$522.00', '$478.00', '$526.00', '$532.00', '$479.00',\n       '$543.00', '$553.00', '$87.00', '$101.00', '$37.00', '$265.00',\n       '$322.00', '$307.00', '$338.00', '$311.00', '$298.00', '$323.00',\n       '$327.00', '$363.00', '$342.00', '$353.00', '$383.00', '$354.00',\n       '$397.00', '$368.00', '$360.00', '$374.00', '$359.00', '$356.00',\n       '$379.00', '$408.00', '$361.00', '$407.00', '$413.00', '$388.00',\n       '$411.00', '$389.00', '$415.00', '$406.00', '$410.00', '$396.00',\n       '$344.00', '$351.00', '$381.00', '$366.00', '$352.00', '$316.00',\n       '$347.00', '$317.00', '$284.00', '$319.00', '$287.00', '$305.00',\n       '$292.00', '$256.00', '$380.00', '$277.00', '$482.00', '$658.00',\n       '$708.00', '$262.00', '$435.00', '$393.00', '$328.00', '$535.00',\n       '$446.00', '$472.00', '$899.00', '$999.00', '$1,099.00',\n       '$1,199.00', '$749.00', '$295.00', '$335.00', '$499.00', '$680.00',\n       '$333.00', '$421.00', '$575.00', '$326.00', '$318.00', '$370.00',\n       '$372.00', '$377.00', '$417.00', '$431.00', '$463.00', '$429.00',\n       '$454.00', '$440.00', '$281.00', '$336.00', '$394.00', '$387.00',\n       '$537.00', '$520.00', '$512.00', '$498.00', '$506.00', '$659.00',\n       '$676.00', '$610.00', '$490.00', '$564.00', '$491.00', '$651.00',\n       '$552.00', '$460.00', '$775.00', '$29.00', '$36.00', '$32.00',\n       '$565.00', '$28.00', '$263.00', '$538.00', '$487.00', '$484.00',\n       '$453.00', '$457.00', '$488.00', '$557.00', '$283.00', '$337.00',\n       '$343.00', '$447.00', '$27.00', '$22.00', '$23.00', '$26.00',\n       '$495.00', '$418.00', '$12.00', '$469.00', '$462.00', '$505.00',\n       '$509.00', '$507.00', '$511.00', '$476.00', '$434.00', '$516.00',\n       '$576.00', '$573.00', '$540.00', '$544.00', '$578.00', '$541.00',\n       '$542.00', '$585.00', '$569.00', '$568.00', '$939.00', '$304.00',\n       '$508.00', '$510.00', '$562.00', '$825.00', '$723.00', '$727.00',\n       '$733.00', '$628.00', '$599.00', '$10.00', '$900.00', '$1,000.00',\n       '$24.00', '$504.00', '$548.00', '$513.00', '$539.00', '$517.00',\n       '$673.00', '$711.00', '$788.00', '$901.00', '$817.00', '$545.00',\n       '$451.00', '$481.00', '$527.00', '$519.00', '$560.00', '$563.00',\n       '$646.00', '$618.00', '$623.00', '$596.00', '$567.00', '$566.00',\n       '$534.00', '$503.00', '$603.00', '$784.00', '$850.00', '$950.00',\n       '$524.00', '$471.00', '$533.00', '$583.00', '$554.00'],\n      dtype=object)"},"metadata":{}}]},{"metadata":{},"cell_type":"markdown","source":"we see that listings with availability set to t[True] are the once with only a price specified. All the rest with availability set to f[False] have Nan values in the price column.\n\nThe obviously indicate to us the date for people to book and the price to pay for the accomodation"},{"metadata":{},"cell_type":"markdown","source":"What is the seasonality in the pricing\n\n\n"},{"metadata":{},"cell_type":"markdown","source":"## ANALYZE"},{"metadata":{"trusted":true},"cell_type":"code","source":"# get data for listings which are available for booking\navailable_for_listing = calender_df[calender_df['available'] == 't']\n\n\n# convert date object to datetime for plot\navailable_for_listing['date'] = available_for_listing['date'].apply(pd.to_datetime)\n\n\n# convert price column to int\n\navailable_for_listing['price']=available_for_listing['price'].apply(lambda x: float(str(x).replace('$','').replace(',','') ))","execution_count":435,"outputs":[{"output_type":"stream","text":"/opt/conda/lib/python3.7/site-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \nA value is trying to be set on a copy of a slice from a DataFrame.\nTry using .loc[row_indexer,col_indexer] = value instead\n\nSee the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n  \n/opt/conda/lib/python3.7/site-packages/ipykernel_launcher.py:11: SettingWithCopyWarning: \nA value is trying to be set on a copy of a slice from a DataFrame.\nTry using .loc[row_indexer,col_indexer] = value instead\n\nSee the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n  # This is added back by InteractiveShellApp.init_path()\n","name":"stderr"}]},{"metadata":{"trusted":true},"cell_type":"code","source":"available_for_listing.head()","execution_count":436,"outputs":[{"output_type":"execute_result","execution_count":436,"data":{"text/plain":"    listing_id       date available  price\n0       241032 2016-01-04         t   85.0\n1       241032 2016-01-05         t   85.0\n9       241032 2016-01-13         t   85.0\n10      241032 2016-01-14         t   85.0\n14      241032 2016-01-18         t   85.0","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>listing_id</th>\n      <th>date</th>\n      <th>available</th>\n      <th>price</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>241032</td>\n      <td>2016-01-04</td>\n      <td>t</td>\n      <td>85.0</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>241032</td>\n      <td>2016-01-05</td>\n      <td>t</td>\n      <td>85.0</td>\n    </tr>\n    <tr>\n      <th>9</th>\n      <td>241032</td>\n      <td>2016-01-13</td>\n      <td>t</td>\n      <td>85.0</td>\n    </tr>\n    <tr>\n      <th>10</th>\n      <td>241032</td>\n      <td>2016-01-14</td>\n      <td>t</td>\n      <td>85.0</td>\n    </tr>\n    <tr>\n      <th>14</th>\n      <td>241032</td>\n      <td>2016-01-18</td>\n      <td>t</td>\n      <td>85.0</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}]},{"metadata":{},"cell_type":"markdown","source":"## VISUALIZE"},{"metadata":{"trusted":true},"cell_type":"code","source":"#Plot the responses for different events and regions\nplt.title('Plot of price against time')\nsns.lineplot(data= available_for_listing, x=\"date\", y=\"price\");","execution_count":437,"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 432x288 with 1 Axes>","image/png":"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\n"},"metadata":{"needs_background":"light"}}]},{"metadata":{},"cell_type":"markdown","source":"We see there is a trend in the price of listings for booking for the years 2016 to 2017.\n\nBut there is a lot of noise in the data so lets clean or smothen it\n\nNow lets aggregate and smothen out the line on the chart"},{"metadata":{},"cell_type":"markdown","source":"## ANALYZE"},{"metadata":{"trusted":true},"cell_type":"code","source":"# aggregate all price in a month \ngrouper = pd.Grouper(key='date', freq='M')\nresult = available_for_listing.groupby(grouper)['price'].sum().reset_index()\n\nresult","execution_count":438,"outputs":[{"output_type":"execute_result","execution_count":438,"data":{"text/plain":"         date       price\n0  2016-01-31   7201591.0\n1  2016-02-29   9113355.0\n2  2016-03-31  10798161.0\n3  2016-04-30  10272371.0\n4  2016-05-31  11159008.0\n5  2016-06-30  11391415.0\n6  2016-07-31  11288732.0\n7  2016-08-31  11502179.0\n8  2016-09-30  11065949.0\n9  2016-10-31  11296639.0\n10 2016-11-30  11096625.0\n11 2016-12-31  11949282.0\n12 2017-01-31    779957.0","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>date</th>\n      <th>price</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>2016-01-31</td>\n      <td>7201591.0</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>2016-02-29</td>\n      <td>9113355.0</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>2016-03-31</td>\n      <td>10798161.0</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>2016-04-30</td>\n      <td>10272371.0</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>2016-05-31</td>\n      <td>11159008.0</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>2016-06-30</td>\n      <td>11391415.0</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>2016-07-31</td>\n      <td>11288732.0</td>\n    </tr>\n    <tr>\n      <th>7</th>\n      <td>2016-08-31</td>\n      <td>11502179.0</td>\n    </tr>\n    <tr>\n      <th>8</th>\n      <td>2016-09-30</td>\n      <td>11065949.0</td>\n    </tr>\n    <tr>\n      <th>9</th>\n      <td>2016-10-31</td>\n      <td>11296639.0</td>\n    </tr>\n    <tr>\n      <th>10</th>\n      <td>2016-11-30</td>\n      <td>11096625.0</td>\n    </tr>\n    <tr>\n      <th>11</th>\n      <td>2016-12-31</td>\n      <td>11949282.0</td>\n    </tr>\n    <tr>\n      <th>12</th>\n      <td>2017-01-31</td>\n      <td>779957.0</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}]},{"metadata":{},"cell_type":"markdown","source":"## VISUALIZE"},{"metadata":{"trusted":true},"cell_type":"code","source":"plt.title('Monthly Plot of price against time')\nsns.lineplot(data= result, x=\"date\", y=\"price\");","execution_count":439,"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 432x288 with 1 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\n"},"metadata":{"needs_background":"light"}}]},{"metadata":{},"cell_type":"markdown","source":"This looks better.\nAs we can see, prices of listing begins to rise from january to may and barely levels then starts to climb from september and peaked in november/ december \nthen fell very low january 2017.\n\nThe peak in november/ december indicates that most host put their property for booking because a lot of people travel during this time\n"},{"metadata":{},"cell_type":"markdown","source":"## ANALYZE"},{"metadata":{"trusted":true},"cell_type":"code","source":"# let's see if this is true\ntravel_date=[]\ntavel_price=[]\nfor year in result.date.dt.year.unique():\n\n    year_value= result[result.date.dt.year == year]\n    max_value = year_value.price.max()\n    year_date =result[result.price == max_value].date.dt.date.values[0]\n    travel_date.append(year_date)\n    tavel_price.append(max_value)\n    \n    print(year, year_date, max_value)\n    ","execution_count":440,"outputs":[{"output_type":"stream","text":"2016 2016-12-31 11949282.0\n2017 2017-01-31 779957.0\n","name":"stdout"}]},{"metadata":{},"cell_type":"markdown","source":"December and january saw the total highest price that host put on their listings for the year 2016"},{"metadata":{},"cell_type":"markdown","source":"Review dataset"},{"metadata":{"trusted":true},"cell_type":"code","source":"reviews_df.head()","execution_count":441,"outputs":[{"output_type":"execute_result","execution_count":441,"data":{"text/plain":"   listing_id        id        date  reviewer_id reviewer_name  \\\n0     7202016  38917982  2015-07-19     28943674        Bianca   \n1     7202016  39087409  2015-07-20     32440555         Frank   \n2     7202016  39820030  2015-07-26     37722850           Ian   \n3     7202016  40813543  2015-08-02     33671805        George   \n4     7202016  41986501  2015-08-10     34959538          Ming   \n\n                                            comments  \n0  Cute and cozy place. Perfect location to every...  \n1  Kelly has a great room in a very central locat...  \n2  Very spacious apartment, and in a great neighb...  \n3  Close to Seattle Center and all it has to offe...  \n4  Kelly was a great host and very accommodating ...  ","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>listing_id</th>\n      <th>id</th>\n      <th>date</th>\n      <th>reviewer_id</th>\n      <th>reviewer_name</th>\n      <th>comments</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>7202016</td>\n      <td>38917982</td>\n      <td>2015-07-19</td>\n      <td>28943674</td>\n      <td>Bianca</td>\n      <td>Cute and cozy place. Perfect location to every...</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>7202016</td>\n      <td>39087409</td>\n      <td>2015-07-20</td>\n      <td>32440555</td>\n      <td>Frank</td>\n      <td>Kelly has a great room in a very central locat...</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>7202016</td>\n      <td>39820030</td>\n      <td>2015-07-26</td>\n      <td>37722850</td>\n      <td>Ian</td>\n      <td>Very spacious apartment, and in a great neighb...</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>7202016</td>\n      <td>40813543</td>\n      <td>2015-08-02</td>\n      <td>33671805</td>\n      <td>George</td>\n      <td>Close to Seattle Center and all it has to offe...</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>7202016</td>\n      <td>41986501</td>\n      <td>2015-08-10</td>\n      <td>34959538</td>\n      <td>Ming</td>\n      <td>Kelly was a great host and very accommodating ...</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"# the shape of reviews dataset : 84849 rows and 6 columns\nreviews_df.shape","execution_count":442,"outputs":[{"output_type":"execute_result","execution_count":442,"data":{"text/plain":"(84849, 6)"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"# check columns with not null values\nreviews_df.columns[reviews_df.isnull().sum() == 0]","execution_count":443,"outputs":[{"output_type":"execute_result","execution_count":443,"data":{"text/plain":"Index(['listing_id', 'id', 'date', 'reviewer_id', 'reviewer_name'], dtype='object')"},"metadata":{}}]},{"metadata":{},"cell_type":"markdown","source":"Questions to ask about the reviews data \n\n\nwhen do most people review listings, this can give us an indication of when people do travel a lot\n\n"},{"metadata":{},"cell_type":"markdown","source":"## VISUALIZE"},{"metadata":{"trusted":true},"cell_type":"code","source":"reviews_df.date= pd.to_datetime(reviews_df.date)\ngrouper = pd.Grouper(key='date', freq='M')\n\nreview_new_df = reviews_df.groupby(grouper)['id'].count().reset_index()\n\n# plot avg listings prices over time.\nplt.figure(figsize=(15, 8))\nplt.plot(review_new_df.date, review_new_df.id, color='b', linewidth=1.9)\nplt.title(\"What is the parten of travel from 2010 to 2016?\")\nplt.xlabel('date')\nplt.ylabel('People')\n# Hide the right and top spines\nax.spines['right'].set_visible(False)\nax.spines['top'].set_visible(False)\n","execution_count":444,"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 1080x576 with 1 Axes>","image/png":"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\n"},"metadata":{"needs_background":"light"}}]},{"metadata":{},"cell_type":"markdown","source":"THe number of people who review thats to climb from june there but not so sure\n\nwe have to take a deeper look into that"},{"metadata":{},"cell_type":"markdown","source":"## ANALYZE"},{"metadata":{"trusted":true},"cell_type":"code","source":"review_new_df.date.dt.year.unique()","execution_count":445,"outputs":[{"output_type":"execute_result","execution_count":445,"data":{"text/plain":"array([2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016])"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"# get the dates each year with the highest number of reviews\n\ntravel_date=[]\ntavel_value=[]\nfor year in review_new_df.date.dt.year.unique():\n\n    \n    year_value= review_new_df[review_new_df.date.dt.year == year]\n    max_value = year_value.id.max()\n    year_date =review_new_df[review_new_df.id == max_value].date.dt.date.values[0]\n    travel_date.append(year_date)\n    tavel_value.append(max_value)\n    \n    print(year, year_date, max_value)\n    \n","execution_count":446,"outputs":[{"output_type":"stream","text":"2009 2009-10-31 6\n2010 2010-09-30 53\n2011 2011-08-31 215\n2012 2012-08-31 463\n2013 2013-08-31 1070\n2014 2014-08-31 3268\n2015 2015-08-31 7963\n2016 2016-01-31 223\n","name":"stdout"}]},{"metadata":{},"cell_type":"markdown","source":"## VISUALIZE"},{"metadata":{"trusted":true},"cell_type":"code","source":"f, ax = plt.subplots(figsize=(10, 8))\nsns.barplot( x=travel_date, y=tavel_value);\n\nplt.title(\"When do most people travel?\")\nplt.xlabel('date')\nplt.ylabel('People')\n# Hide the right and top spines\nax.spines['right'].set_visible(False)\nax.spines['top'].set_visible(False)\n","execution_count":447,"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 720x576 with 1 Axes>","image/png":"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\n"},"metadata":{"needs_background":"light"}}]},{"metadata":{},"cell_type":"markdown","source":"This really looks good, as we have found that september seems to recieve more reviews as this indicates when most people travel during the year.\n\nSO our question is answered\n\n**When do most people travel?** During the month of September"},{"metadata":{},"cell_type":"markdown","source":"# DATA PREPERATION"},{"metadata":{},"cell_type":"markdown","source":"\n**PROCESSES INVOLVED**\n\n* removing or imputing null values\n* checking and removing features with high correlation\n* choosing which features to use in our model\n* feature engineering\n* converting categorical variables to numberical(on-hot-encoding)\n"},{"metadata":{},"cell_type":"markdown","source":"## ASSESS"},{"metadata":{"trusted":true},"cell_type":"code","source":"# count the percent number of nulls in each column\n\n\nfor col in new_listing_df.columns:\n    percen_null = new_listing_df[col].isnull().sum()/ new_listing_df.shape[0]\n    print(col, \"percent_null({})\".format(percen_null) )\n","execution_count":448,"outputs":[{"output_type":"stream","text":"city percent_null(0.0)\nzipcode percent_null(0.001880288310874334)\nsmart_location percent_null(0.0)\nis_location_exact percent_null(0.0)\nproperty_type percent_null(0.0)\nroom_type percent_null(0.0)\nbed_type percent_null(0.0)\namenities percent_null(0.0)\nprice percent_null(0.0)\nweekly_price percent_null(0.4359135067376998)\nmonthly_price percent_null(0.5734879348166719)\nsecurity_deposit percent_null(0.4935756816045127)\ncleaning_fee percent_null(0.24067690379191475)\nextra_people percent_null(0.0)\ncalendar_updated percent_null(0.0)\nfirst_review percent_null(0.0)\nlast_review percent_null(0.0)\naccommodates percent_null(0.0)\nbathrooms percent_null(0.003760576621748668)\nbedrooms percent_null(0.001880288310874334)\nbeds percent_null(0.0)\nsquare_feet percent_null(0.9711689125665935)\nguests_included percent_null(0.0)\navailability_30 percent_null(0.0)\navailability_60 percent_null(0.0)\navailability_90 percent_null(0.0)\navailability_365 percent_null(0.0)\nreview_scores_rating percent_null(0.006267627702914447)\nreview_scores_accuracy percent_null(0.009714822939517392)\n","name":"stdout"}]},{"metadata":{},"cell_type":"markdown","source":"## CLEAN"},{"metadata":{"trusted":true},"cell_type":"code","source":"# remove square_feet  column as this has almost all its rows null\nnew_listing_df=new_listing_df.drop(columns=['square_feet'])","execution_count":449,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# drop columns that will not be needed\ndrop_column_list=['city','zipcode','smart_location','is_location_exact']\n\nnew_listing_df=new_listing_df.drop(columns=drop_column_list)\nnew_listing_df.head()","execution_count":450,"outputs":[{"output_type":"execute_result","execution_count":450,"data":{"text/plain":"  property_type        room_type  bed_type  \\\n0     Apartment  Entire home/apt  Real Bed   \n1     Apartment  Entire home/apt  Real Bed   \n2         House  Entire home/apt  Real Bed   \n4         House  Entire home/apt  Real Bed   \n5         House     Private room  Real Bed   \n\n                                           amenities  price weekly_price  \\\n0  {TV,\"Cable TV\",Internet,\"Wireless Internet\",\"A...   85.0          NaN   \n1  {TV,Internet,\"Wireless Internet\",Kitchen,\"Free...  150.0    $1,000.00   \n2  {TV,\"Cable TV\",Internet,\"Wireless Internet\",\"A...  975.0          NaN   \n4  {TV,\"Cable TV\",Internet,\"Wireless Internet\",Ki...  450.0          NaN   \n5  {\"Wireless Internet\",\"Free Parking on Premises...  120.0      $800.00   \n\n  monthly_price security_deposit cleaning_fee extra_people  ... bathrooms  \\\n0           NaN              NaN          NaN        $5.00  ...       1.0   \n1     $3,000.00          $100.00       $40.00        $0.00  ...       1.0   \n2           NaN        $1,000.00      $300.00       $25.00  ...       4.5   \n4           NaN          $700.00      $125.00       $15.00  ...       2.0   \n5           NaN              NaN       $40.00       $30.00  ...       1.0   \n\n  bedrooms beds  guests_included  availability_30  availability_60  \\\n0      1.0  1.0                2               14               41   \n1      1.0  1.0                1               13               13   \n2      5.0  7.0               10                1                6   \n4      3.0  3.0                6               30               60   \n5      1.0  1.0                1                0                0   \n\n   availability_90  availability_365  review_scores_rating  \\\n0               71               346                  95.0   \n1               16               291                  96.0   \n2               17               220                  97.0   \n4               90               365                  92.0   \n5               27               302                  95.0   \n\n   review_scores_accuracy  \n0                    10.0  \n1                    10.0  \n2                    10.0  \n4                     9.0  \n5                    10.0  \n\n[5 rows x 24 columns]","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>property_type</th>\n      <th>room_type</th>\n      <th>bed_type</th>\n      <th>amenities</th>\n      <th>price</th>\n      <th>weekly_price</th>\n      <th>monthly_price</th>\n      <th>security_deposit</th>\n      <th>cleaning_fee</th>\n      <th>extra_people</th>\n      <th>...</th>\n      <th>bathrooms</th>\n      <th>bedrooms</th>\n      <th>beds</th>\n      <th>guests_included</th>\n      <th>availability_30</th>\n      <th>availability_60</th>\n      <th>availability_90</th>\n      <th>availability_365</th>\n      <th>review_scores_rating</th>\n      <th>review_scores_accuracy</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>Apartment</td>\n      <td>Entire home/apt</td>\n      <td>Real Bed</td>\n      <td>{TV,\"Cable TV\",Internet,\"Wireless Internet\",\"A...</td>\n      <td>85.0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>$5.00</td>\n      <td>...</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>2</td>\n      <td>14</td>\n      <td>41</td>\n      <td>71</td>\n      <td>346</td>\n      <td>95.0</td>\n      <td>10.0</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>Apartment</td>\n      <td>Entire home/apt</td>\n      <td>Real Bed</td>\n      <td>{TV,Internet,\"Wireless Internet\",Kitchen,\"Free...</td>\n      <td>150.0</td>\n      <td>$1,000.00</td>\n      <td>$3,000.00</td>\n      <td>$100.00</td>\n      <td>$40.00</td>\n      <td>$0.00</td>\n      <td>...</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1</td>\n      <td>13</td>\n      <td>13</td>\n      <td>16</td>\n      <td>291</td>\n      <td>96.0</td>\n      <td>10.0</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>House</td>\n      <td>Entire home/apt</td>\n      <td>Real Bed</td>\n      <td>{TV,\"Cable TV\",Internet,\"Wireless Internet\",\"A...</td>\n      <td>975.0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>$1,000.00</td>\n      <td>$300.00</td>\n      <td>$25.00</td>\n      <td>...</td>\n      <td>4.5</td>\n      <td>5.0</td>\n      <td>7.0</td>\n      <td>10</td>\n      <td>1</td>\n      <td>6</td>\n      <td>17</td>\n      <td>220</td>\n      <td>97.0</td>\n      <td>10.0</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>House</td>\n      <td>Entire home/apt</td>\n      <td>Real Bed</td>\n      <td>{TV,\"Cable TV\",Internet,\"Wireless Internet\",Ki...</td>\n      <td>450.0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>$700.00</td>\n      <td>$125.00</td>\n      <td>$15.00</td>\n      <td>...</td>\n      <td>2.0</td>\n      <td>3.0</td>\n      <td>3.0</td>\n      <td>6</td>\n      <td>30</td>\n      <td>60</td>\n      <td>90</td>\n      <td>365</td>\n      <td>92.0</td>\n      <td>9.0</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>House</td>\n      <td>Private room</td>\n      <td>Real Bed</td>\n      <td>{\"Wireless Internet\",\"Free Parking on Premises...</td>\n      <td>120.0</td>\n      <td>$800.00</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>$40.00</td>\n      <td>$30.00</td>\n      <td>...</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n      <td>27</td>\n      <td>302</td>\n      <td>95.0</td>\n      <td>10.0</td>\n    </tr>\n  </tbody>\n</table>\n<p>5 rows × 24 columns</p>\n</div>"},"metadata":{}}]},{"metadata":{},"cell_type":"markdown","source":"## VISUALIZE\n\nwe want to use see which central tendency measure is best for filling null values in bedroom and bathroom column"},{"metadata":{"trusted":true},"cell_type":"code","source":"\nsns.boxplot(x=new_listing_df.bedrooms,orient=\"h\")","execution_count":451,"outputs":[{"output_type":"execute_result","execution_count":451,"data":{"text/plain":"<matplotlib.axes._subplots.AxesSubplot at 0x7f94c82154d0>"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"<Figure size 432x288 with 1 Axes>","image/png":"iVBORw0KGgoAAAANSUhEUgAAAWAAAAEGCAYAAABbzE8LAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjEsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+j8jraAAAMzElEQVR4nO3dbWyd913G8euKXdS0rKvmVJXlDMwwKtLWaQ9R0dRpsroWMjJtMPEiVkoDUjsqbWlaXiCYkNgkkBBCiDYvCG3aKSEhEXuCDYV0qbZugCgs6R5C1wJm2lR3GU1ThTZNus7JjxfnNsQmtk+cc851TvL9SFZyTs65758t65u///a57aoSAKD3VqUHAIDLFQEGgBACDAAhBBgAQggwAIQMX8iD16xZU+Pj410aBQAuTYcPH36hqq5beP8FBXh8fFyHDh3q3FQAcBmw/b3z3c8WBACEEGAACCHAABBCgAEghAADQAgBBoAQAgwAIQQYAEIIMACEEGAACCHAABBCgAEghAADQAgBBoAQAgwAIQQYAEIIMACEEGAACCHAABByQb8T7nJw55136sSJExobG0uP0raJiQlt2bIlPQaAC0SAFzh69KhOvnJKP/jhYHxohk69mB4BwAoNRmV6bWhYp3/2F9NTtGX1M/vTIwBYIfaAASCEAANACAEGgBACDAAhBBgAQggwAIQQYAAIIcAAEEKAASCEAANACAEGgBACDAAhBBgAQggwAIQQYAAIIcAAEEKAASCEAANACAEGgBACDAAhBBgAQggwAIQQYAAIIcAAEEKAASCEAANACAEGgBACDAAhBBgAQggwAIQQYAAIIcAAEEKAASCEAANACAEGgBACDAAhBBgAQggwAIQQYAAIIcAAEEKAASCkJwHetm2btm3b1otToY/xeQDMN9yLk0xPT/fiNOhzfB4A87EFAQAhBBgAQggwAIQQYAAIIcAAEEKAASCEAANACAEGgBACDAAhBBgAQggwAIQQYAAIIcAAEEKAASCEAANACAEGgBACDAAhBBgAQggwAIQQYAAIIcAAEEKAASCEAANACAEGgBACDAAhBBgAQggwAIQQYAAIIcAAEEKAASCEAANACAEGgBACDAAhBBgAQggwAIQQYAAIIcAAEEKAASCEAAOLmJyc/N+3fjc1NaXJyUndfvvt6VHasmfPHk1OTmrfvn3pUZZ1/Phx3XPPPTp+/HjHj02AgUvA0aNHJUkzMzPhSdrz0EMPSZK2b98enmR5O3fu1JEjR7Rr166OH5sAA+excNXbz6vgqampebf7fRW8Z8+eebf7eRV8/PhxHThwQFWlAwcOdHwVPNzRoy3iueee0+nTp7V169ZenO6inD59Wqr0FO1b9epLmp5+eSA+ttPT01q9enV6jEvO3Op3Tr+vgudWv3O2b9+ujRs3hqZZ2s6dO3X27FlJ0pkzZ7Rr1y7dd999HTv+sitg2x+2fcj2oWPHjnXsxADQ7x577DHNzs5KkmZnZ3Xw4MGOHn/ZFXBVPSjpQUlat27ditaGY2NjkqT7779/JU/vqQ0bNujkq6+lx2jb2Suv0cSbrh+Ij+0grNKBc916663av3+/ZmdnNTw8rNtuu62jx2cPGBhwo6Oj826vXbs2NEl77rrrrnm377777tAky9u8ebNWrWplcmhoSHfccUdHj0+AgfN4/PHHl7zdT/bu3Tvv9u7du0OTtGfTpk3zbvfr/q8kjYyMaP369bKt9evXa2RkpKPHJ8DAJWBuFdzvq985c6vgfl79ztm8ebNuvPHGjq9+pR79FAQwiPp51bvQwlVwv9u0adP/Wwn3q5GRET3wwANdOTYrYAAIIcAAEEKAASCEAANACAEGgBACDAAhBBgAQggwAIQQYAAIIcAAEEKAASCEAANACAEGgBACDAAhBBgAQggwAIQQYAAIIcAAEEKAASCEAANACAEGgBACDAAhBBgAQggwAIQQYAAIIcAAEEKAASCEAANACAEGgBACDAAhBBgAQggwAIQQYAAIIcAAEEKAASCEAANACAEGgBACDAAhw704ycTERC9Ogz7H5wEwX08CvGXLll6cBn2OzwNgPrYgACCEAANACAEGgBACDAAhBBgAQggwAIQQYAAIIcAAEEKAASCEAANACAEGgBACDAAhBBgAQggwAIQQYAAIIcAAEEKAASCEAANACAEGgBACDAAhBBgAQggwAIQQYAAIIcAAEEKAASCEAANACAEGgBACDAAhBBgAQggwAIQQYAAIIcAAEEKAASCEAANACAEGgBACDAAhBBgAQggwAIQQYAAIIcAAEDKcHqAvnZnV6mf2p6doy9CpFyVdnx4DwAoQ4AVGR0d14sQJjY0NStSu18TERHoIACtAgBfYsWNHegQAlwn2gAEghAADQAgBBoAQAgwAIQQYAEIIMACEEGAACCHAABBCgAEghAADQAgBBoAQAgwAIQQYAEIIMACEEGAACCHAABBCgAEghAADQAgBBoAQAgwAIa6q9h9sH5P0vRWea42kF1b43F4bpFmlwZp3kGaVBmveQZpVGqx5L3bWn6yq6xbeeUEBvhi2D1XVup6c7CIN0qzSYM07SLNKgzXvIM0qDda83ZqVLQgACCHAABDSywA/2MNzXaxBmlUarHkHaVZpsOYdpFmlwZq3K7P2bA8YADAfWxAAEEKAASCk6wG2vd72v9metv3b3T7fxbD9iO3nbf9repbl2H6j7S/bftr2U7a3pmdaiu0rbf+L7W82834iPdNybA/Z/rrtv03Pshzb37V9xPY3bB9Kz7MU29fa/rTtZ5rP33elZ1qM7Ruaj+nc20u27+3Y8bu5B2x7SNK/S7pN0oykr0maqqpvd+2kF8H2eySdlLSrqt6SnmcptkcljVbVk7ZfJ+mwpF/q44+tJV1dVSdtXyHpHyRtraonwqMtyvZvSlon6Zqqen96nqXY/q6kdVXV9y9ssL1T0t9X1Q7bPybpqqo6kZ5rOU3PnpP0c1W10hekzdPtFfBNkqar6jtV9ZqkfZI+2OVzrlhVfVXSi+k52lFVR6vqyebvL0t6WtJYdqrFVcvJ5uYVzVvffgfY9lpJGyTtSM9yKbF9jaT3SHpYkqrqtUGIb+O9kv6zU/GVuh/gMUnPnnN7Rn0ciUFle1zS2yX9c3aSpTVf0n9D0vOSDlZVP8/7p5J+S9LZ9CBtKklftH3Y9ofTwyzhTZKOSfpks72zw/bV6aHatFHS3k4esNsB9nnu69tVzyCy/eOSPiPp3qp6KT3PUqrqTFW9TdJaSTfZ7sttHtvvl/R8VR1Oz3IBbq6qd0h6n6SPNNtp/WhY0jsk/VlVvV3SK5L6+ntDktRslXxA0qc6edxuB3hG0hvPub1W0ve7fM7LRrOX+hlJe6rqs+l52tV8yfm4pPXhURZzs6QPNPuq+yTdYnt3dqSlVdX3mz+fl/Q5tbb/+tGMpJlzvvr5tFpB7nfvk/RkVf1XJw/a7QB/TdLP2P6p5n+QjZI+3+VzXhaab2o9LOnpqvqT9DzLsX2d7Wubv6+WdKukZ7JTnV9V/U5Vra2qcbU+Z79UVbeHx1qU7aubb8Sq+XL+5yX15U/yVNUPJD1r+4bmrvdK6stvHC8wpQ5vP0itLwe6pqpmbX9U0qOShiQ9UlVPdfOcF8P2XkmTktbYnpH0e1X1cHaqRd0s6VclHWn2VSXpY1W1PzjTUkYl7Wy+k7xK0l9VVd//eNeAuF7S51r/J2tY0l9W1YHsSEvaImlPsyj7jqRfD8+zJNtXqfWTXL/R8WPzUmQAyOCVcAAQQoABIIQAA0AIAQaAEAIMACEEGD1he3ylV5m7mOcC/YwAY2DZ7urPsQPdRoDRS8O2d9r+VnM92Ktsv9P2V5qLyDzaXGZTzf3ftP1Pkj4ydwDbv2b7U7a/oNbFZ95g+6+bYz5h+63N4xa7/+PNDF9srqH7Idt/1FxL90Dz8m7Z/kPb326e/8e9/1DhckCA0Us3SHqwqt4q6SW1wrpN0q9U1TslPSLpD5rHflLSPVV1vot1v0vS5qq6RdInJH29OebHJO1qHrPY/ZL002pdavKDknZL+nJV3SjptKQNtt8g6Zclvbl5/u935L0HFiDA6KVnq+ofm7/vlvQLkt4i6WDzcurflbTW9uslXVtVX2ke+xcLjnOwquau2/zuuX+vqi9JGmmev9j9kvR3VfUjSUfUeon83Mt2j0gaV+s/h1cl7bD9IUmnOvHOAwuxh4ZeWvi695clPbVwldtctGep18i/cu7DFznPUpdC/aEkVdVZ2z+q/3s9/llJw801TG5S60IxGyV9VNItS8wDrAgrYPTST5zz+7+mJD0h6bq5+2xfYfvNzeUq/9v2u5vHblrimF+d+3fbk5JeaK6LvNj9y2qusfz65sJG90p6W/vvItA+VsDopaclbbb955L+Q63930clPdBsDwyr9ZsonlLrClmP2D7VPGYxH1frtyt8S62tgs3L3N+O10n6G9tXqrWSvu8Cngu0jauhAUAIWxAAEEKAASCEAANACAEGgBACDAAhBBgAQggwAIT8Dym34mP3Xt+hAAAAAElFTkSuQmCC\n"},"metadata":{"needs_background":"light"}}]},{"metadata":{},"cell_type":"markdown","source":"For bedroom, we see that there are a few listings with very high number of bedrooms. this can be an outlier and hence using the mean to fill missing values would not help in our analysis.\n\nthe bedrooms data is left skewed and we see a great number falls between 1 and 2.\n\nso  the mode is the best pick for filling missing values"},{"metadata":{"trusted":true},"cell_type":"code","source":"sns.boxplot(x=new_listing_df.bathrooms,orient=\"v\")","execution_count":452,"outputs":[{"output_type":"execute_result","execution_count":452,"data":{"text/plain":"<matplotlib.axes._subplots.AxesSubplot at 0x7f94b4d5ced0>"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"<Figure size 432x288 with 1 Axes>","image/png":"iVBORw0KGgoAAAANSUhEUgAAAXgAAADrCAYAAABjGI3/AAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjEsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+j8jraAAAPqklEQVR4nO3df4xc1XnG8eexDQXboBAzacIPZ4m2pSKogTKiJEiRMQlxYpfUIkmNDGlIxQpVpUnTH0phK0y1oLaKoqYoClqSOER1QAnGEjESIZKxUFJEO8tvYpC2dCEEEgbqlNi0kMVv/5hZs2vv7tzZ3bN37vH3I428986dOe9fj1+dOfdcR4QAAPlZUnYBAIA0CHgAyBQBDwCZIuABIFMEPABkioAHgEwtK7uAyU488cTo6+sruwwAqIyRkZGXI6I23Xs9FfB9fX1qNBpllwEAlWH72ZneY4oGADJFwANApgh4AMgUAQ8AmUoa8Lb/wvaTtp+wfZvtY1KOB6QwOjqq9evXa3R0tOxSgK4kC3jbJ0v6c0n1iDhT0lJJm1KNB6QyNDSk/fv3a2hoqOxSgK6knqJZJulY28skLZf0QuLxgAU1OjqqsbExSdLY2BhdPColWcBHxM8kfUnSc5JelPQ/EXFvqvGAFA7t2uniUSUpp2hOkPRxSadJOknSCtuXTXPdgO2G7Uaz2UxVDjAnE937TMdAL0s5RfMhSf8VEc2I+LWkOyV94NCLImI4IuoRUa/Vpr3bFijNoVtnsJUGqiRlwD8n6Tzby21b0oWS9iQcD1hwg4ODsx4DvSzlHPyDku6Q9JCkx9tjDacaD0ihv7//YNfe19en/v7+cgsCupB0FU1EXBcRvxMRZ0bE5RHxesrxgBQGBwe1YsUKundUTk/tJgn0ov7+ft19991llwF0ja0KACBTBDwAZIqAB4BMEfAAkCkCHgAyRcADQKYIeADIFAEPAJki4AEgUwQ8AGSKgAeATBHwAJApAh4AMkXAA0CmCHgAyFTKh26fbvuRSa9XbX8+1XgAgKmSPfAjIp6WdJYk2V4q6WeSdqQaDwAw1WJN0Vwo6T8j4tlFGg8AjniLFfCbJN023Ru2B2w3bDeazeYilQMA+Use8LaPlnSxpO9N935EDEdEPSLqtVotdTkAcMRYjA7+o5IeiohfLMJYAIC2xQj4SzXD9AwAIJ2kAW97uaQPS7oz5TgAgMMlWyYpSRHxmqRVKccAAEyPO1kBIFMEPABkioAHgEwR8ACQKQIeADJFwANApgh4AMgUAQ8AmSLgASBTBDwAZIqAB4BMEfAAkCkCHgAyRcADQKYIeADIFAEPAJlK/USnt9m+w/ZTtvfYfn/K8QAAb0n6RCdJX5F0T0R8wvbRkpYnHg8A0JYs4G0fL+mDkj4jSRHxhqQ3Uo0HAJgq5RTNeyQ1JW21/bDtr9tecehFtgdsN2w3ms1mwnIA4MiSMuCXSfo9SV+LiLMl7Zf0xUMviojhiKhHRL1WqyUsBwCOLCkD/nlJz0fEg+3jO9QKfADAIkgW8BHxc0k/tX16+9SFkn6SajwAwFSpV9FcLWlbewXNM5KuSDweAKAtacBHxCOS6inHAABMjztZASBTBDwAZIqAB4BMEfAAkCkCHgAyRcADQKYIeADIFAEPAJki4AEgUwQ8AGSKgAeATBHwAJApAh4AMkXAA0CmCHgAyFTSgLc9Zvtx24/YbqQcC0hldHRU69ev1+joaNmlAF1ZjA7+gog4KyJ48AcqaWhoSPv379fQ0FDZpQBdYYoGmMXo6KjGxsYkSWNjY3TxqJTUAR+S7rU9Ynsg8VjAgju0a6eLR5Wkfuj2+RHxgu13SPqh7aci4v7JF7SDf0CSVq9enbgcoDsT3ftMx0AvK9TB2/6c7ePd8g3bD9m+qNPnIuKF9r8vSdoh6dxprhmOiHpE1Gu1Wrf1A0n19fXNegz0sqJTNJ+NiFclXSSpJukKSf8w2wdsr7B93MTf7c8+MY9agUU3ODg46zHQy4oGvNv/fkzS1oh4dNK5mfympB/ZflTSv0u6OyLumVuZQDn6+/sPdu19fX3q7+8vtyCgC0UDfsT2vWoF/A/anfmB2T4QEc9ExPvar/dGxA3zLRYow+DgoFasWEH3jspxRHS+yF4i6SxJz0TEL22vknRyRDy2kMXU6/VoNLgfCgCKsj0y031GhVbRRMQB2+OSPmh78mcWNOABAAunUMDb/qak35X0pN6amglJdyaqCwAwT0Xn4M9rL2X844i4ov36bNLKgB7RaDS0du1ajYyMlF0K0JWiAf+A7TOSVgL0qC1btujAgQO67rrryi4F6ErRgL9VrZB/2vZj7R0imX9H9hqNhvbt2ydJ2rdvH108KqXoKppRSV+Q9LgmLY+MiGcXshhW0aDXbNiw4WDAS9LKlSu1c+fOEisCppr3KhpJz0XEXQtYE1AJk8N9umOglxUN+Kdsf0fS9yW9PnEyIlhFg6ytXLnysA4eqIqic/DHqhXsF0n6g/ZrQ6qigF6xZcuWKcfXX399OYUAc1D0RqcrUhcC9KJ6vX6wi1+5cqXOOeecsksCCiu6XfAptnfYfsn2L2xvt31K6uKAXrBlyxYtWbKE7h2VU3QOfquk70j6ZPv4sva5D6coCugl9Xpdu3btKrsMoGtF5+BrEbE1Isbbr2+ptS88AKBHFQ34l21fZntp+3WZpFdSFgYAmJ/CT3SS9ClJP2+/PtE+BwDoUYUCPiKei4iLI6LWfv1h0btY2x3/w7a5/Q+VtG3bNq1Zs0a333572aUAXVmMVTSfk7Rn7iUC5brlllskSTfffHPJlQDdKTpFs1XSXZJOknSyWne0bu30ofZ/AuslfX2uBQJl2rZt25RjunhUSepVNP8s6W/U4fmtQK+a6N4n0MWjSpKtorG9QdJLETHr/qq2B2w3bDeazWbBcgAAncxlFc2LKraK5nxJF9sek3S7pLW2//XQiyJiuP20qHqtxtJ6AFgoHQPe9lJJN05aRfOOIqtoIuJvI+KUiOiTtEnSroi4bGHKBhbHlVdeOeX4qquuKqkSoHsdAz4i3pRUs330ItQD9JTNmzdPOd60aVNJlQDdKzpFMybpx7b/zvYXJl5FB4mI3RHB9sKopIkunu4dVVN0s7EX2q8lko5LVw7QezZv3nxYJw9UQdH94NknFQAqplDA2/5tSX8lqW/yZyJibZqyAADzVXSK5nuSblbrjtQ305UD9J41a9Yc/Hv37t2l1QF0q2jAj0fE15JWAgBYULOuorH9dttvl/R9239q+10T59rngaxN7t6nOwZ6WacOfkRSSHL7+K8nvReS3pOiKADA/M0a8BFxmiTZPiYi/m/ye7aPSVkYAGB+it7o9G8FzwEAesSsHbztd6q1//uxts/WW1M1x0tanrg2AMA8dJqD/4ikz0g6RdKXJ53/laRrEtUE9Izdu3ezTBKV1WkO/lZJt9q+JCK2L1JNAIAFUHSrgu2210t6r6RjJp3/+1SFAb2Crh1VVfSh2zdL+iNJV6s1D/9JSe9OWBcAYJ6KrqL5QER8WtLe9sZj75d0arqyAADzVXSrgv9t//ua7ZPUeh7raWlKAnoLP7KiqooG/E7bb5P0T2rd3Sq1Nh6bUftGqPsl/UZ7nDsi4rq5FgoA6E7RKZovqfWQ7cslPaBW0N/Q4TOvS1obEe+TdJakdbbPm2uhQBnYiwZVVrSDv1Wtte//0j6+VNK3JX1qpg9EREja1z48qv2KuZUJAOhW0YA/vd2JT7jP9qOdPmR7qVpTOv2SvhoRD05zzYCkAUlavXp1wXIAAJ0UnaJ5ePL0iu3fl/TjTh+KiDcj4iy17oQ91/aZ01wzHBH1iKjXarWidQMAOui0F83jak2rHCXp07afax+/W9JPig4SEb+0vVvSOklPzLlaAEBhnaZoNsz1i23XJP26He7HSvqQpH+c6/cBZWAvGlRZp71onp3Hd79LrX1slqo1FfTdiNg5j+8DAHSh6I+sXYuIxySdner7gcVC146qKvojKwCgYgh4AMgUAQ8AmUo2Bw/kglU0qCo6eADIFAEPzILNxlBlBDwAZIqAB4BMEfAAkCkCHgAyRcADszh0WSTLJFElBDwAZIobnYAO6NpRVXTwAJApAh4AMpVsisb2qZK+Lemdkg5IGo6Ir6QaD0iFvWhQVSnn4Mcl/WVEPGT7OEkjtn8YEYWf5QoAmLtkUzQR8WJEPNT++1eS9kg6OdV4QArsRYMqW5Q5eNt9aj2+78HFGA8AsAgBb3ulpO2SPh8Rr07z/oDthu1Gs9lMXQ4AHDGSBrzto9QK920Rced010TEcETUI6Jeq9VSlgMAR5RkAW/bkr4haU9EfDnVOACA6aXs4M+XdLmktbYfab8+lnA8YMGxFw2qLNkyyYj4kSSn+n4AwOzYiwbogK4dVcVWBQCQKQIeADLFFA3QAXvRoKro4AEgUwQ8MAv2okGVEfAAkCkCHgAyRcADQKYIeADIFAEPzIK9aFBlBDwAZIobnYAO6NpRVXTwAJApAh4AMkXAA0CmUj6y75u2X7L9RKoxAAAzS9nBf0vSuoTfDwCYRbKAj4j7Jf13qu8HAMyOZZKT3HTTTbrnnnvKLqMnvPbaa4qIsstAD7Kt5cuXl11GT1i3bp2uvvrqssuYUek/stoesN2w3Wg2m2WXAwDZcMouzXafpJ0RcWaR6+v1ejQajWT1AEBubI9ERH2690rv4AEAaaRcJnmbpAcknW77edt/kmosAMDhkv3IGhGXpvpuAEBnTNEAQKYIeADIFAEPAJniRiegg40bN2rv3r1atWqVtm/fXnY5QGF08EAHe/fulSS98sorJVcCdIeAB2axcePGKceXXHJJSZUA3SPggVlMdO8T6OJRJQQ8AGSKgAeATBHwwCxOOOGEKcerVq0qqRKgewQ8MIsdO3ZMOWaZJKqEgAc6mOji6d5RNdzoBHRwaBcPVAUdPABkioAHgEwR8EAHu3bt0po1a3TfffeVXQrQlaQBb3ud7adtj9r+YsqxgFRuvPFGSdINN9xQciVAd1I+sm+ppK9K+qikMyRdavuMVOMBKezatUvj4+OSpPHxcbp4VErKDv5cSaMR8UxEvCHpdkkfTzgesOAmuvcJdPGokpQBf7Kkn046fr59bgrbA7YbthvNZjNhOUD3Jrr3mY6BXpYy4D3NuTjsRMRwRNQjol6r1RKWA3Rv2bJlsx4DvSxlwD8v6dRJx6dIeiHheMCCu+aaa6YcX3vttSVVAnQvZcD/h6Tfsn2a7aMlbZJ0V8LxgAW3du3ag137smXLdMEFF5RcEVBcsoCPiHFJfybpB5L2SPpuRDyZajwglYkunu4dVeOIw6bFS1Ov16PRaJRdBgBUhu2RiKhP9x53sgJApgh4AMgUAQ8AmSLgASBTPfUjq+2mpGfLrgOYxomSXi67CGAa746Iae8S7amAB3qV7cZMKxWAXsUUDQBkioAHgEwR8EAxw2UXAHSLOXgAyBQdPABkioAHgEwR8ACQKQIeADJFwANApv4fZ49iU+Z/JeUAAAAASUVORK5CYII=\n"},"metadata":{"needs_background":"light"}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"plt.hist(new_listing_df.bathrooms)\nplt.ylabel('count');\nplt.xlabel('bathrooms');\n","execution_count":453,"outputs":[{"output_type":"stream","text":"/opt/conda/lib/python3.7/site-packages/numpy/lib/histograms.py:839: RuntimeWarning: invalid value encountered in greater_equal\n  keep = (tmp_a >= first_edge)\n/opt/conda/lib/python3.7/site-packages/numpy/lib/histograms.py:840: RuntimeWarning: invalid value encountered in less_equal\n  keep &= (tmp_a <= last_edge)\n","name":"stderr"},{"output_type":"display_data","data":{"text/plain":"<Figure size 432x288 with 1 Axes>","image/png":"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\n"},"metadata":{"needs_background":"light"}}]},{"metadata":{},"cell_type":"markdown","source":"from the plots for bathrooms column, we can see that the most recurring value is 1 and that very few listings had high number of bathrooms. therefore the mode is also a good pick for filling the missing values"},{"metadata":{},"cell_type":"markdown","source":"## CLEAN"},{"metadata":{"trusted":true},"cell_type":"code","source":"# bathrooms ( replace null values with mode )\n# bedrooms  (replace null values with mode )\n\nfill_mode = lambda col: col.fillna(col.mode())\ntry:\n    new_listing_df[['bathrooms','bedrooms']].apply(fill_mode, axis=0)\nexcept:\n    print('That broke...')\n","execution_count":454,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"new_listing_df.head()","execution_count":455,"outputs":[{"output_type":"execute_result","execution_count":455,"data":{"text/plain":"  property_type        room_type  bed_type  \\\n0     Apartment  Entire home/apt  Real Bed   \n1     Apartment  Entire home/apt  Real Bed   \n2         House  Entire home/apt  Real Bed   \n4         House  Entire home/apt  Real Bed   \n5         House     Private room  Real Bed   \n\n                                           amenities  price weekly_price  \\\n0  {TV,\"Cable TV\",Internet,\"Wireless Internet\",\"A...   85.0          NaN   \n1  {TV,Internet,\"Wireless Internet\",Kitchen,\"Free...  150.0    $1,000.00   \n2  {TV,\"Cable TV\",Internet,\"Wireless Internet\",\"A...  975.0          NaN   \n4  {TV,\"Cable TV\",Internet,\"Wireless Internet\",Ki...  450.0          NaN   \n5  {\"Wireless Internet\",\"Free Parking on Premises...  120.0      $800.00   \n\n  monthly_price security_deposit cleaning_fee extra_people  ... bathrooms  \\\n0           NaN              NaN          NaN        $5.00  ...       1.0   \n1     $3,000.00          $100.00       $40.00        $0.00  ...       1.0   \n2           NaN        $1,000.00      $300.00       $25.00  ...       4.5   \n4           NaN          $700.00      $125.00       $15.00  ...       2.0   \n5           NaN              NaN       $40.00       $30.00  ...       1.0   \n\n  bedrooms beds  guests_included  availability_30  availability_60  \\\n0      1.0  1.0                2               14               41   \n1      1.0  1.0                1               13               13   \n2      5.0  7.0               10                1                6   \n4      3.0  3.0                6               30               60   \n5      1.0  1.0                1                0                0   \n\n   availability_90  availability_365  review_scores_rating  \\\n0               71               346                  95.0   \n1               16               291                  96.0   \n2               17               220                  97.0   \n4               90               365                  92.0   \n5               27               302                  95.0   \n\n   review_scores_accuracy  \n0                    10.0  \n1                    10.0  \n2                    10.0  \n4                     9.0  \n5                    10.0  \n\n[5 rows x 24 columns]","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>property_type</th>\n      <th>room_type</th>\n      <th>bed_type</th>\n      <th>amenities</th>\n      <th>price</th>\n      <th>weekly_price</th>\n      <th>monthly_price</th>\n      <th>security_deposit</th>\n      <th>cleaning_fee</th>\n      <th>extra_people</th>\n      <th>...</th>\n      <th>bathrooms</th>\n      <th>bedrooms</th>\n      <th>beds</th>\n      <th>guests_included</th>\n      <th>availability_30</th>\n      <th>availability_60</th>\n      <th>availability_90</th>\n      <th>availability_365</th>\n      <th>review_scores_rating</th>\n      <th>review_scores_accuracy</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>Apartment</td>\n      <td>Entire home/apt</td>\n      <td>Real Bed</td>\n      <td>{TV,\"Cable TV\",Internet,\"Wireless Internet\",\"A...</td>\n      <td>85.0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>$5.00</td>\n      <td>...</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>2</td>\n      <td>14</td>\n      <td>41</td>\n      <td>71</td>\n      <td>346</td>\n      <td>95.0</td>\n      <td>10.0</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>Apartment</td>\n      <td>Entire home/apt</td>\n      <td>Real Bed</td>\n      <td>{TV,Internet,\"Wireless Internet\",Kitchen,\"Free...</td>\n      <td>150.0</td>\n      <td>$1,000.00</td>\n      <td>$3,000.00</td>\n      <td>$100.00</td>\n      <td>$40.00</td>\n      <td>$0.00</td>\n      <td>...</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1</td>\n      <td>13</td>\n      <td>13</td>\n      <td>16</td>\n      <td>291</td>\n      <td>96.0</td>\n      <td>10.0</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>House</td>\n      <td>Entire home/apt</td>\n      <td>Real Bed</td>\n      <td>{TV,\"Cable TV\",Internet,\"Wireless Internet\",\"A...</td>\n      <td>975.0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>$1,000.00</td>\n      <td>$300.00</td>\n      <td>$25.00</td>\n      <td>...</td>\n      <td>4.5</td>\n      <td>5.0</td>\n      <td>7.0</td>\n      <td>10</td>\n      <td>1</td>\n      <td>6</td>\n      <td>17</td>\n      <td>220</td>\n      <td>97.0</td>\n      <td>10.0</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>House</td>\n      <td>Entire home/apt</td>\n      <td>Real Bed</td>\n      <td>{TV,\"Cable TV\",Internet,\"Wireless Internet\",Ki...</td>\n      <td>450.0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>$700.00</td>\n      <td>$125.00</td>\n      <td>$15.00</td>\n      <td>...</td>\n      <td>2.0</td>\n      <td>3.0</td>\n      <td>3.0</td>\n      <td>6</td>\n      <td>30</td>\n      <td>60</td>\n      <td>90</td>\n      <td>365</td>\n      <td>92.0</td>\n      <td>9.0</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>House</td>\n      <td>Private room</td>\n      <td>Real Bed</td>\n      <td>{\"Wireless Internet\",\"Free Parking on Premises...</td>\n      <td>120.0</td>\n      <td>$800.00</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>$40.00</td>\n      <td>$30.00</td>\n      <td>...</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n      <td>27</td>\n      <td>302</td>\n      <td>95.0</td>\n      <td>10.0</td>\n    </tr>\n  </tbody>\n</table>\n<p>5 rows × 24 columns</p>\n</div>"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"# remove dollar sign from prices\ndollar_column = ['weekly_price','monthly_price','security_deposit','cleaning_fee','extra_people']\n\nremove_dollar = lambda col: col.replace('[\\$,]', '', regex=True).astype(float)\nnew_listing_df[dollar_column] = new_listing_df[dollar_column].apply(remove_dollar)","execution_count":456,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## VISUALIZE"},{"metadata":{},"cell_type":"markdown","source":"We want to consider the distribution of the dollar columns and decide which  central tendency measure to fill na values"},{"metadata":{"trusted":true},"cell_type":"code","source":"sns.boxplot(x=new_listing_df.weekly_price)","execution_count":457,"outputs":[{"output_type":"execute_result","execution_count":457,"data":{"text/plain":"<matplotlib.axes._subplots.AxesSubplot at 0x7f94b5ca9810>"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"<Figure size 432x288 with 1 Axes>","image/png":"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\n"},"metadata":{"needs_background":"light"}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"sns.boxplot(x=new_listing_df.monthly_price)","execution_count":458,"outputs":[{"output_type":"execute_result","execution_count":458,"data":{"text/plain":"<matplotlib.axes._subplots.AxesSubplot at 0x7f94b5d5b810>"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"<Figure size 432x288 with 1 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\n"},"metadata":{"needs_background":"light"}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"sns.boxplot(x=new_listing_df.security_deposit)","execution_count":459,"outputs":[{"output_type":"execute_result","execution_count":459,"data":{"text/plain":"<matplotlib.axes._subplots.AxesSubplot 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\n"},"metadata":{"needs_background":"light"}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"sns.boxplot(x=new_listing_df.extra_people)","execution_count":461,"outputs":[{"output_type":"execute_result","execution_count":461,"data":{"text/plain":"<matplotlib.axes._subplots.AxesSubplot at 0x7f94b5d3c910>"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"<Figure size 432x288 with 1 Axes>","image/png":"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\n"},"metadata":{"needs_background":"light"}}]},{"metadata":{},"cell_type":"markdown","source":"from the distribution all price columns are right skewed.\n\nall of them contains outliers, that is, very few of them have large values of price.\n\nhence using the mean would not help our analysis\n\nwe can use the mode to fill null values"},{"metadata":{"trusted":true},"cell_type":"code","source":"# fill price columns with mean\nfill_mean = lambda col: col.fillna(col.mode())\nnew_listing_df[dollar_column] = new_listing_df[dollar_column].apply(fill_mean)","execution_count":462,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"new_listing_df.head()","execution_count":463,"outputs":[{"output_type":"execute_result","execution_count":463,"data":{"text/plain":"  property_type        room_type  bed_type  \\\n0     Apartment  Entire home/apt  Real Bed   \n1     Apartment  Entire home/apt  Real Bed   \n2         House  Entire home/apt  Real Bed   \n4         House  Entire home/apt  Real Bed   \n5         House     Private room  Real Bed   \n\n                                           amenities  price  weekly_price  \\\n0  {TV,\"Cable TV\",Internet,\"Wireless Internet\",\"A...   85.0         500.0   \n1  {TV,Internet,\"Wireless Internet\",Kitchen,\"Free...  150.0        1000.0   \n2  {TV,\"Cable TV\",Internet,\"Wireless Internet\",\"A...  975.0           NaN   \n4  {TV,\"Cable TV\",Internet,\"Wireless Internet\",Ki...  450.0           NaN   \n5  {\"Wireless Internet\",\"Free Parking on Premises...  120.0         800.0   \n\n   monthly_price  security_deposit  cleaning_fee  extra_people  ... bathrooms  \\\n0         2500.0             100.0          50.0           5.0  ...       1.0   \n1         3000.0             100.0          40.0           0.0  ...       1.0   \n2            NaN            1000.0         300.0          25.0  ...       4.5   \n4            NaN             700.0         125.0          15.0  ...       2.0   \n5            NaN               NaN          40.0          30.0  ...       1.0   \n\n  bedrooms beds  guests_included  availability_30  availability_60  \\\n0      1.0  1.0                2               14               41   \n1      1.0  1.0                1               13               13   \n2      5.0  7.0               10                1                6   \n4      3.0  3.0                6               30               60   \n5      1.0  1.0                1                0                0   \n\n   availability_90  availability_365  review_scores_rating  \\\n0               71               346                  95.0   \n1               16               291                  96.0   \n2               17               220                  97.0   \n4               90               365                  92.0   \n5               27               302                  95.0   \n\n   review_scores_accuracy  \n0                    10.0  \n1                    10.0  \n2                    10.0  \n4                     9.0  \n5                    10.0  \n\n[5 rows x 24 columns]","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>property_type</th>\n      <th>room_type</th>\n      <th>bed_type</th>\n      <th>amenities</th>\n      <th>price</th>\n      <th>weekly_price</th>\n      <th>monthly_price</th>\n      <th>security_deposit</th>\n      <th>cleaning_fee</th>\n      <th>extra_people</th>\n      <th>...</th>\n      <th>bathrooms</th>\n      <th>bedrooms</th>\n      <th>beds</th>\n      <th>guests_included</th>\n      <th>availability_30</th>\n      <th>availability_60</th>\n      <th>availability_90</th>\n      <th>availability_365</th>\n      <th>review_scores_rating</th>\n      <th>review_scores_accuracy</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>Apartment</td>\n      <td>Entire home/apt</td>\n      <td>Real Bed</td>\n      <td>{TV,\"Cable TV\",Internet,\"Wireless Internet\",\"A...</td>\n      <td>85.0</td>\n      <td>500.0</td>\n      <td>2500.0</td>\n      <td>100.0</td>\n      <td>50.0</td>\n      <td>5.0</td>\n      <td>...</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>2</td>\n      <td>14</td>\n      <td>41</td>\n      <td>71</td>\n      <td>346</td>\n      <td>95.0</td>\n      <td>10.0</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>Apartment</td>\n      <td>Entire home/apt</td>\n      <td>Real Bed</td>\n      <td>{TV,Internet,\"Wireless Internet\",Kitchen,\"Free...</td>\n      <td>150.0</td>\n      <td>1000.0</td>\n      <td>3000.0</td>\n      <td>100.0</td>\n      <td>40.0</td>\n      <td>0.0</td>\n      <td>...</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1</td>\n      <td>13</td>\n      <td>13</td>\n      <td>16</td>\n      <td>291</td>\n      <td>96.0</td>\n      <td>10.0</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>House</td>\n      <td>Entire home/apt</td>\n      <td>Real Bed</td>\n      <td>{TV,\"Cable TV\",Internet,\"Wireless Internet\",\"A...</td>\n      <td>975.0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>1000.0</td>\n      <td>300.0</td>\n      <td>25.0</td>\n      <td>...</td>\n      <td>4.5</td>\n      <td>5.0</td>\n      <td>7.0</td>\n      <td>10</td>\n      <td>1</td>\n      <td>6</td>\n      <td>17</td>\n      <td>220</td>\n      <td>97.0</td>\n      <td>10.0</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>House</td>\n      <td>Entire home/apt</td>\n      <td>Real Bed</td>\n      <td>{TV,\"Cable TV\",Internet,\"Wireless Internet\",Ki...</td>\n      <td>450.0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>700.0</td>\n      <td>125.0</td>\n      <td>15.0</td>\n      <td>...</td>\n      <td>2.0</td>\n      <td>3.0</td>\n      <td>3.0</td>\n      <td>6</td>\n      <td>30</td>\n      <td>60</td>\n      <td>90</td>\n      <td>365</td>\n      <td>92.0</td>\n      <td>9.0</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>House</td>\n      <td>Private room</td>\n      <td>Real Bed</td>\n      <td>{\"Wireless Internet\",\"Free Parking on Premises...</td>\n      <td>120.0</td>\n      <td>800.0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>40.0</td>\n      <td>30.0</td>\n      <td>...</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n      <td>27</td>\n      <td>302</td>\n      <td>95.0</td>\n      <td>10.0</td>\n    </tr>\n  </tbody>\n</table>\n<p>5 rows × 24 columns</p>\n</div>"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"# check how each dollar column correlates with price\n\nsns.pairplot(new_listing_df[dollar_column +['price']])","execution_count":464,"outputs":[{"output_type":"execute_result","execution_count":464,"data":{"text/plain":"<seaborn.axisgrid.PairGrid at 0x7f94ac7eb110>"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"<Figure size 1080x1080 with 42 Axes>","image/png":"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\n"},"metadata":{"needs_background":"light"}}]},{"metadata":{},"cell_type":"markdown","source":"weekly and monthly price are positively correlate with price"},{"metadata":{},"cell_type":"markdown","source":"## CLEAN"},{"metadata":{"trusted":true},"cell_type":"code","source":"# remove all other price columns as they have positive correlation with price\n# this would ensure that our model fits the right column and remove any data leakage\nnew_listing_df=new_listing_df.drop(columns=['weekly_price','monthly_price','security_deposit','extra_people','cleaning_fee'])","execution_count":465,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"Get categorical columns and convert them"},{"metadata":{"trusted":true},"cell_type":"code","source":"# select categorical date\nnumerics = ['int16', 'int32', 'int64', 'float16', 'float32', 'float64']\ncategorical_columns = new_listing_df.select_dtypes(exclude=numerics).columns\ncategorical_columns","execution_count":466,"outputs":[{"output_type":"execute_result","execution_count":466,"data":{"text/plain":"Index(['property_type', 'room_type', 'bed_type', 'amenities',\n       'calendar_updated', 'first_review', 'last_review'],\n      dtype='object')"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"# drop date columns\nnew_listing_df=new_listing_df.drop(columns=['calendar_updated','first_review','last_review',\n                                            'availability_30', 'availability_60', 'availability_90','availability_365'])","execution_count":467,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"def create_dummy_df(df, cat_cols, dummy_na):\n    '''\n    INPUT:\n    df - pandas dataframe with categorical variables you want to dummy\n    cat_cols - list of strings that are associated with names of the categorical columns\n    dummy_na - Bool holding whether you want to dummy NA vals of categorical columns or not\n    \n    OUTPUT:\n    df - a new dataframe that has the following characteristics:\n            1. contains all columns that were not specified as categorical\n            2. removes all the original columns in cat_cols\n            3. dummy columns for each of the categorical columns in cat_cols\n            4. if dummy_na is True - it also contains dummy columns for the NaN values\n            5. Use a prefix of the column name with an underscore (_) for separating \n    '''\n    \n    for col in  cat_cols:\n        try:\n            # for each cat add dummy var, drop original column\n            df = pd.concat([df.drop(col, axis=1), pd.get_dummies(df[col], prefix=col, prefix_sep='_', drop_first=True, dummy_na=dummy_na)], axis=1)\n        except:\n            continue\n    return df","execution_count":468,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"\ncol_list= ['is_location_exact', 'property_type', 'room_type', 'bed_type']\ndf_new = create_dummy_df(new_listing_df,col_list, dummy_na=False) \n\nprint(df_new.shape)","execution_count":469,"outputs":[{"output_type":"stream","text":"(3191, 30)\n","name":"stdout"}]},{"metadata":{},"cell_type":"markdown","source":"create categorical variable for the amenity column\n"},{"metadata":{"trusted":true},"cell_type":"code","source":"# create categorical columns for amenities\n# convert amenities into list for each row\n\ndef get_amen_unique(df):\n    '''\n    INPUT: \n         df - a dataframe holding a amenities columns wiht values\n\n\n    OUTPUT:\n          list_amenities - a list of unique amenities in the amenities column of the dataframe\n\n    '''\n    list_amenities =[]\n    for row in df_new.amenities.iteritems():\n        item = row[1].replace('{', '').replace('}', '').replace('\"','')\n        for amen in item.split(','):\n            list_amenities.append(amen)\n            \n    return set(list_amenities)\n        \n\n    \nunique_amen=get_amen_unique(df_new)","execution_count":470,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"\ndef amen_categorical(df,col_list):\n    '''\n    INPUT: \n         df - the dataframe containing amenities column to convert to categorical\n         col_list - the list of unique amenities in the amenities column of the dataframe\n\n    OUTPUT:\n\n            df - a new dataframe with categorical one-hot-encoded columns from the amenities column \n\n    '''\n    #create columns for each amen type\n\n    for new_col in unique_amen:\n        if new_col != '':\n            df['amen_'+ new_col] = None\n\n            for row in df.amenities.iteritems():\n                item = row[1].replace('{', '').replace('}', '').replace('\"','')\n                amenities =[amen for amen in item.split(',') ]\n                index =row[0]\n                if new_col in amenities:\n                    df.at[index, 'amen_'+ new_col] = 1\n\n                else:\n                    df.at[index, 'amen_'+ new_col] = 0\n    # remove original amenities column\n    df = df.drop(columns=['amenities'])\n    return df                ","execution_count":471,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"df_new=amen_categorical(df_new,unique_amen)","execution_count":472,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# drop amenities column\ndf_new=df_new.drop(columns=['review_scores_rating', 'review_scores_accuracy'])\nprint(df_new.shape)","execution_count":473,"outputs":[{"output_type":"stream","text":"(3191, 68)\n","name":"stdout"}]},{"metadata":{"trusted":true},"cell_type":"code","source":"df_new.head()","execution_count":474,"outputs":[{"output_type":"execute_result","execution_count":474,"data":{"text/plain":"   price  accommodates  bathrooms  bedrooms  beds  guests_included  \\\n0   85.0             4        1.0       1.0   1.0                2   \n1  150.0             4        1.0       1.0   1.0                1   \n2  975.0            11        4.5       5.0   7.0               10   \n4  450.0             6        2.0       3.0   3.0                6   \n5  120.0             2        1.0       1.0   1.0                1   \n\n   property_type_Bed & Breakfast  property_type_Boat  property_type_Bungalow  \\\n0                              0                   0                       0   \n1                              0                   0                       0   \n2                              0                   0                       0   \n4                              0                   0                       0   \n5                              0                   0                       0   \n\n   property_type_Cabin  ...  amen_Lock on Bedroom Door  \\\n0                    0  ...                          0   \n1                    0  ...                          0   \n2                    0  ...                          0   \n4                    0  ...                          0   \n5                    0  ...                          0   \n\n   amen_Buzzer/Wireless Intercom  amen_Air Conditioning  amen_Washer / Dryer  \\\n0                              0                      1                    0   \n1                              1                      0                    0   \n2                              0                      1                    0   \n4                              0                      0                    0   \n5                              0                      0                    0   \n\n   amen_Carbon Monoxide Detector  amen_Smoke Detector  amen_Pool  \\\n0                              0                    0          0   \n1                              1                    1          0   \n2                              1                    1          0   \n4                              1                    1          0   \n5                              0                    1          0   \n\n   amen_Free Parking on Premises  amen_Fire Extinguisher  \\\n0                              0                       0   \n1                              1                       1   \n2                              1                       0   \n4                              0                       1   \n5                              1                       0   \n\n   amen_Wireless Internet  \n0                       1  \n1                       1  \n2                       1  \n4                       1  \n5                       1  \n\n[5 rows x 68 columns]","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>price</th>\n      <th>accommodates</th>\n      <th>bathrooms</th>\n      <th>bedrooms</th>\n      <th>beds</th>\n      <th>guests_included</th>\n      <th>property_type_Bed &amp; Breakfast</th>\n      <th>property_type_Boat</th>\n      <th>property_type_Bungalow</th>\n      <th>property_type_Cabin</th>\n      <th>...</th>\n      <th>amen_Lock on Bedroom Door</th>\n      <th>amen_Buzzer/Wireless Intercom</th>\n      <th>amen_Air Conditioning</th>\n      <th>amen_Washer / Dryer</th>\n      <th>amen_Carbon Monoxide Detector</th>\n      <th>amen_Smoke Detector</th>\n      <th>amen_Pool</th>\n      <th>amen_Free Parking on Premises</th>\n      <th>amen_Fire Extinguisher</th>\n      <th>amen_Wireless Internet</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>85.0</td>\n      <td>4</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>2</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>...</td>\n      <td>0</td>\n      <td>0</td>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>150.0</td>\n      <td>4</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>...</td>\n      <td>0</td>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n      <td>1</td>\n      <td>1</td>\n      <td>0</td>\n      <td>1</td>\n      <td>1</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>975.0</td>\n      <td>11</td>\n      <td>4.5</td>\n      <td>5.0</td>\n      <td>7.0</td>\n      <td>10</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>...</td>\n      <td>0</td>\n      <td>0</td>\n      <td>1</td>\n      <td>0</td>\n      <td>1</td>\n      <td>1</td>\n      <td>0</td>\n      <td>1</td>\n      <td>0</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>450.0</td>\n      <td>6</td>\n      <td>2.0</td>\n      <td>3.0</td>\n      <td>3.0</td>\n      <td>6</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>...</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>1</td>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n      <td>1</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>120.0</td>\n      <td>2</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>...</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>1</td>\n      <td>0</td>\n      <td>1</td>\n      <td>0</td>\n      <td>1</td>\n    </tr>\n  </tbody>\n</table>\n<p>5 rows × 68 columns</p>\n</div>"},"metadata":{}}]},{"metadata":{},"cell_type":"markdown","source":"# MODELLING"},{"metadata":{},"cell_type":"markdown","source":"We need to know what characteristics or features that influence the pricing of listings.\n\nThese characteristics ranges from amenities, bed types, e.t.c from the dataset\n\nTo know this, we want to use a model on our features to fit the price column\n\nThen evaluate the model to find out what the model thinks influences price the more\n\nThis can then answer the question, What are the top 10 characteristics of listing that influence the price of listings ?"},{"metadata":{},"cell_type":"markdown","source":"**PROCEDURE**\n\n* We choose our predictor which is the price column\n\n* Split data into training and test sets\n\n* We fit our data using a LinearRegression model\n\n* We use an r2_score for accessing our model\n\n* track the training and validation score\n\n\n"},{"metadata":{"trusted":true},"cell_type":"code","source":"def clean_fit_linear_mod(df, response_col,test_size=.3, rand_state=42):\n    '''\n    INPUT:\n    df - a dataframe holding all the variables of interest\n    response_col - a string holding the name of the column \n    test_size - a float between [0,1] about what proportion of data should be in the test dataset\n    rand_state - an int that is provided as the random state for splitting the data into training and test \n    \n    OUTPUT:\n    test_score - float - r2 score on the test data\n    train_score - float - r2 score on the test data\n    lm_model - model object from sklearn\n    X_train, X_test, y_train, y_test - output from sklearn train test split used for optimal model\n\n    '''\n    #Drop the rows with missing response values\n    df  = df.dropna(subset=[response_col], axis=0)\n\n    #Drop columns with all NaN values\n    df = df.dropna(how='all', axis=1)\n\n\n    # Mean function\n    fill_mean = lambda col: col.fillna(col.mean())\n    # Fill the mean\n    df = df.apply(fill_mean, axis=0)\n  \n\n    # shuffle data\n    df = shuffle(df)\n    \n    #Split into explanatory and response variables\n    X = df.drop(response_col, axis=1)\n    y = df[response_col]\n\n    \n\n    #Split into train and test\n    X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=test_size, random_state=rand_state)\n\n    lm_model = LinearRegression(normalize=True) # Instantiate\n    lm_model.fit(X_train, y_train) #Fit\n\n    #Predict using your model\n    y_test_preds = lm_model.predict(X_test)\n    y_train_preds = lm_model.predict(X_train)\n\n    #Score using your model\n    test_score = r2_score(y_test, y_test_preds)\n    train_score = r2_score(y_train, y_train_preds)\n\n    return test_score, train_score, lm_model, X_train, X_test, y_train, y_test\n\n\n#Test your function with the above dataset\ntest_score, train_score, lm_model, X_train, X_test, y_train, y_test = clean_fit_linear_mod(df_new, 'price')","execution_count":475,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#Print training and testing score\nprint(\"The rsquared on the training data was {}.  The rsquared on the test data was {}.\".format(train_score, test_score))","execution_count":476,"outputs":[{"output_type":"stream","text":"The rsquared on the training data was 0.5642311508572392.  The rsquared on the test data was -9.376029582275818e+24.\n","name":"stdout"}]},{"metadata":{},"cell_type":"markdown","source":"# EVALUATION"},{"metadata":{},"cell_type":"markdown","source":"Here, we want to evaluate our model on what it thinks makes pricing of listing go either directions.\n\nBy evaluating the model coefficient, we can how much each feature in our model effect pricing  \n"},{"metadata":{"trusted":true},"cell_type":"code","source":"def coef_weights(coefficients, X_train):\n    '''\n    INPUT:\n    coefficients - the coefficients of the linear model \n    X_train - the training data, so the column names can be used\n    OUTPUT:\n    coefs_df - a dataframe holding the coefficient, estimate, and abs(estimate)\n    \n    Provides a dataframe that can be used to understand the most influential coefficients\n    in a linear model by providing the coefficient estimates along with the name of the \n    variable attached to the coefficient.\n    '''\n    coefs_df = pd.DataFrame()\n    coefs_df['est_int'] = X_train.columns\n    coefs_df['coefs'] = lm_model.coef_\n    coefs_df['abs_coefs'] = np.abs(lm_model.coef_)\n    coefs_df = coefs_df.sort_values('abs_coefs', ascending=False)\n    return coefs_df\n\n#Use the function\ncoef_df = coef_weights(lm_model.coef_, X_train)\n\n#A quick look at the top results\ncoef_df.head(10)","execution_count":477,"outputs":[{"output_type":"execute_result","execution_count":477,"data":{"text/plain":"                    est_int         coefs     abs_coefs\n10     property_type_Chalet  6.293695e+15  6.293695e+15\n6        property_type_Boat  1.932959e+02  1.932959e+02\n18  property_type_Treehouse  1.280064e+02  1.280064e+02\n12       property_type_Dorm -1.201058e+02  1.201058e+02\n21    room_type_Shared room -7.215421e+01  7.215421e+01\n20   room_type_Private room -4.584673e+01  4.584673e+01\n47             amen_Doorman  4.579015e+01  4.579015e+01\n1                 bathrooms  3.109176e+01  3.109176e+01\n2                  bedrooms  3.081877e+01  3.081877e+01\n14       property_type_Loft  2.478709e+01  2.478709e+01","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>est_int</th>\n      <th>coefs</th>\n      <th>abs_coefs</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>10</th>\n      <td>property_type_Chalet</td>\n      <td>6.293695e+15</td>\n      <td>6.293695e+15</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>property_type_Boat</td>\n      <td>1.932959e+02</td>\n      <td>1.932959e+02</td>\n    </tr>\n    <tr>\n      <th>18</th>\n      <td>property_type_Treehouse</td>\n      <td>1.280064e+02</td>\n      <td>1.280064e+02</td>\n    </tr>\n    <tr>\n      <th>12</th>\n      <td>property_type_Dorm</td>\n      <td>-1.201058e+02</td>\n      <td>1.201058e+02</td>\n    </tr>\n    <tr>\n      <th>21</th>\n      <td>room_type_Shared room</td>\n      <td>-7.215421e+01</td>\n      <td>7.215421e+01</td>\n    </tr>\n    <tr>\n      <th>20</th>\n      <td>room_type_Private room</td>\n      <td>-4.584673e+01</td>\n      <td>4.584673e+01</td>\n    </tr>\n    <tr>\n      <th>47</th>\n      <td>amen_Doorman</td>\n      <td>4.579015e+01</td>\n      <td>4.579015e+01</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>bathrooms</td>\n      <td>3.109176e+01</td>\n      <td>3.109176e+01</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>bedrooms</td>\n      <td>3.081877e+01</td>\n      <td>3.081877e+01</td>\n    </tr>\n    <tr>\n      <th>14</th>\n      <td>property_type_Loft</td>\n      <td>2.478709e+01</td>\n      <td>2.478709e+01</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}]},{"metadata":{},"cell_type":"markdown","source":"## VISUALIZE"},{"metadata":{"trusted":true},"cell_type":"code","source":"f, ax = plt.subplots(figsize=(10, 8))\n\n# which property type influenced price the most\nproperty_type = coef_df[coef_df.est_int.str.startswith('property_type')]\nproperty_type['est_int']= property_type['est_int'].str.replace('property_type_','')\nsns.barplot(data=property_type, x=\"abs_coefs\", y=\"est_int\", orient=\"h\");\n\nplt.title('What Property Type Had a high Influence on the Price of a Listing?')\nplt.xlabel('Absolute_Coefficienct')\nplt.ylabel('Property Type')\n# Hide the right and top spines\nax.spines['right'].set_visible(False)\nax.spines['top'].set_visible(False)","execution_count":478,"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 720x576 with 1 Axes>","image/png":"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\n"},"metadata":{"needs_background":"light"}}]},{"metadata":{},"cell_type":"markdown","source":"As we can see Boat has a very high influence on the price compared with other listing property type"},{"metadata":{"trusted":true},"cell_type":"code","source":"def show_values_on_bars(axs):\n    '''\n    INPUT:\n         ax- the axis of the plot to show values on top of the bar plot\n    OUTPUT:\n          bar plot with text on bar \n    '''\n    def _show_on_single_plot(ax):        \n        for p in ax.patches:\n            _x = p.get_x() + p.get_width() / 2\n            _y = p.get_y() + p.get_height()\n            value = '{:.2f}'.format(p.get_height())\n            ax.text(_x, _y, value, ha=\"center\") \n\n    if isinstance(axs, np.ndarray):\n        for idx, ax in np.ndenumerate(axs):\n            _show_on_single_plot(ax)\n    else:\n        _show_on_single_plot(axs)","execution_count":479,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"\nf, ax = plt.subplots(figsize=(8, 6))\n\n# which room type influenced price the most\nroom_type = coef_df[coef_df.est_int.str.startswith('room_type')]\nroom_type['est_int']= room_type['est_int'].str.replace('room_type_','')\n\ng=sns.barplot(data=room_type, x=\"est_int\", y=\"abs_coefs\");\nplt.title('What Room Type Had a high Influence on the Price of a Listing?')\nplt.xlabel('Room Type')\nplt.ylabel('Absolute_Coefficienct')\n# Hide the right and top spines\nax.spines['right'].set_visible(False)\nax.spines['top'].set_visible(False)\n\nshow_values_on_bars(ax)","execution_count":480,"outputs":[{"output_type":"stream","text":"/opt/conda/lib/python3.7/site-packages/ipykernel_launcher.py:5: SettingWithCopyWarning: \nA value is trying to be set on a copy of a slice from a DataFrame.\nTry using .loc[row_indexer,col_indexer] = value instead\n\nSee the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n  \"\"\"\n","name":"stderr"},{"output_type":"display_data","data":{"text/plain":"<Figure size 576x432 with 1 Axes>","image/png":"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\n"},"metadata":{"needs_background":"light"}}]},{"metadata":{},"cell_type":"markdown","source":"Shared room has high influence on the price"},{"metadata":{"trusted":true},"cell_type":"code","source":"# which amenitiy had a high influence on the price\n\nf, ax = plt.subplots(figsize=(14, 10))\namenity_type = coef_df[coef_df.est_int.str.startswith('amen')]\namenity_type['est_int']= amenity_type['est_int'].str.replace('amen_','')\n\nsns.barplot(data=amenity_type, x=\"abs_coefs\", y=\"est_int\", orient=\"h\");\nplt.title('What amenitiy Type Had a high Influence on the Price of a Listing?')\nplt.xlabel('Absolute_Coefficienct')\nplt.ylabel('Amenity Type')\n# Hide the right and top spines\nax.spines['right'].set_visible(False)\nax.spines['top'].set_visible(False)\n","execution_count":481,"outputs":[{"output_type":"stream","text":"/opt/conda/lib/python3.7/site-packages/ipykernel_launcher.py:5: SettingWithCopyWarning: \nA value is trying to be set on a copy of a slice from a DataFrame.\nTry using .loc[row_indexer,col_indexer] = value instead\n\nSee the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n  \"\"\"\n","name":"stderr"},{"output_type":"display_data","data":{"text/plain":"<Figure size 1008x720 with 1 Axes>","image/png":"iVBORw0KGgoAAAANSUhEUgAAA7YAAAJdCAYAAAAGDuttAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjEsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+j8jraAAAgAElEQVR4nOzdeZgdVZ3/8feHNYFg2FeBAILIGqFRWQVFXABBRBFxiYNEGBkHBfmhIMu4gTg6KiIGlSAgIIKyDovDFnYayMKOsioohCUQCIGEz++POi2Vm3t7S3c6nf68nqefrnvqnFPfqnvTT773nFMl20REREREREQMVosMdAARERERERER8yKJbURERERERAxqSWwjIiIiIiJiUEtiGxEREREREYNaEtuIiIiIiIgY1JLYRkRERERExKCWxDYiYpCRZElvG+g4+puk6ZLW7WT/PZJ2nI8hLZAk7Sjpb33U13hJ3+lkf6fvSUPdfvucSvqOpKmS/iFpVDnWYv1xrMFG0qOSdh6A465VPh+LzsdjriLpekkvSfrvfjzOKZK+1Yt28/2aRAxlSWwjIgaQpG9Iuqyh7KEWZZ/qg+MNyH96e8P2CNsPQ/OEy/bGtq/tSZ/lP6jTy89rkl6vvf7fPgy/sxjmSvgkHSvpzPlx/HlRf0/6Uk/OX9KawKHARrZX7etYBpOuvojog/4t6eXy7+Pvkn7UKkmz/Xj5fMzur3iaGAtMBd5i+9B56aizL4hsH2j7293oY46/r315TSQdJOk+SS9KukHS+vPaZ8TCJoltRMTAuh7YtuM/i5JWBRYHtmgoe1upG/Og/Ad1hO0RwPeAczte2/7wQMcX3bI28Kztpwc6kCFi8/Lv5f3Ap4EDGisM4Gj52sC9tj1Ax5+flgP2ApYHJgI/GdhwIhY8SWwjIgbW7VSJ7OjyegfgGuCBhrK/2n6y1m7nMor7vKSfSxKApPUkXS3p2TJV8yxJy5Z9ZwBrAReXEZjDG4ORtJykSyQ9U/q+RNJba/uvLdNAbyp9XCxphXKcFyXdLmlUrf6Gkq6S9JykByR9srZvfIn90jKV8FZJ69X2W9LbJI0F9gMO7zhm2f+opJ0lrSrpFUkr1NpuWc5h8e68CSWO/24ou1jSIbVjfUPSveW6nCZpWK3ubpImSnqhXJvNunPcTuL5iaQnyjW9Q9L2tX3Dy7V7XtK9wFa97auF5bp6T8r2CuUadbzv35F0Q0NfTT+n3Th/SzqwsW0ZDbsKWL18FsY3aTvHqJkaRoMlvae8Ry9ImqTadPby+f62pBvL+V8pacXa/u1qbZ+QNKaULynph5Iel/RPVTMDhrc4t0UkHSXpMUlPS/qtpJFlX8e06s+XvqZKOrJFP03/XRSjJU2WNE3SuX3xWbV9PzAB2KQW5/6SHgeuVsOUcEnLl38nT5b38E+9iUHSNuXzNa383qaUjwc+Xzv/uWaiSNpV0l3lM/qEpGO7c65N+vnXyLikFVX9XXxB1d+1CeU9nevva5Nr0tXn63Plc/GspG/VP8u2v2f7PtuzgBuBVXpzLhELsyS2EREDyPZrwK1UySvl9wTghoayxtHa3agSms2BTwIfLOUCvg+sDrwDWBM4thzrs8DjwO5lhPIHTUJaBDiNaiRkLWAGcFJDnU8BnwXWANYDbi5tlgfuA44BkLQ0VRLyO2BlYF/gZEkb1/raFziOajTiL8B3m1yjccBZwA9K3Ls37P8HcG25Dh0+A5xj+/Um59jM6cC+khYpsa9INUJ1dq3OflTXeT1gA+CoUncL4DfAl4AVgF8CF0laspvHbuZ2qi82lqe6fufVkpNjSgzrlXg+Pw99NdPle1L8HHgZWLXE0CyOVp/T7pirre0/Ax8GniyfhTE96A9JawCXAt+huh6HAedLWqlW7dPAF6g+s0uUOkhaC/hf4GfASlTXdGJpcwLVZ2I01eyKNYCjW4QxpvzsBKwLjGDuf2PbAW+n+gweLekdjZ108e/ik8CHgHWAzcrx5umzKmkjYHvgrlrxe6n+zjR7X88AlgI2prqWP+5pDJKWp3q/flrq/gi4VNIK5b2vn/+fm8TwMvA5YFlgV+AgSXt2da5dOBT4G9VnYBXgm4C7+fcVWn++NgJOpvo7sxowkupzNAdJKwPfBsbP43lELHSS2EZEDLzreDOJ3Z4qsZ3QUHZdQ5vjbb9g+3GqEd7RALb/Yvsq2zNtP0P1H8H3djcQ28/aPt/2K7ZfokpqGtufZvuvtqdR/Uf/r7b/XEYSzgPeWertBjxq+zTbs2zfCZwP7F3r6wLbt5W2Z/HmKHVPnU6VzKJqCve+VP+x7hbbtwHTqBIJqJL3a23/s1btJNtP2H6O6rrsW8oPAH5p+1bbs22fDswE3tPJIe8sIz4vSHoBOKIhnjPLezHL9n8DS1IlOlAlLd+1/ZztJ6j+09/ZuXXWVzNdviflGn8cOKZ8Vu6leg8aNf2cdtO8tG3lM8Blti+z/Ybtq4B24CO1OqfZftD2DOD3tePuB/zZ9tm2Xy/XdKIkUX0Gvlrek5eoprm3WhO/H/Aj2w/bng58A/iU5pzOe5ztGbYnAZOokvue+KntJ8tn9eLaOfT2s/p86edXVF9idTjW9svlWv2LpNWovoA40Pbz5Xp1/A3rSQy7Ag/ZPqN8fs8G7gd2b1J3LravtT2lvNeTqb6o6vbfwxZep0o81y7nNaGHU6Fbfb72Bi62fUP5wvNoYI5+JS0BXAFcavtn83geEQudJLYREQPvemA7ScsBK9l+CLgJ2KaUbcLcI7b/qG2/QjXqg6SVJZ2j6kYvLwJnAivSTZKWkvTLMh3uxXLcZTXnDWPqyd6MJq9HlO21gXc3JHD7UY3wdXoevXAhsJGqO/Z+AJhWktWe+FdyXH43JsZP1LYfoxoVh+o8D204zzVr+5vZwvayHT/A8fWdkg5VdaOYaaW/kbz5Pq7eJJaWuuirme68JysBizXE8USTevPy/vbVZ6NubeATDe/VdlSJSlfHXRP4a5M+V6Iambyj1uflpbyZ1ZnzPXuM6lrWp5bO67m3at/bz+pyttezfZTtN2r7mr3nlD6fs/18k309iaHxWlFezzWS2Yykd0u6RtWyhGnAgfTg72ELJ1LNZLhS0sOSjuiqQYNW780c/65tvwI829B2R2AZ4Ks9PGbEkJDENiJi4N1MlWyMpVo7he0XgSdL2ZO2H+lmX9+n+pZ/M9tvoUrQ6usauxpZOJRqNO/dpX3HqHG31kY2eAK4rp7AlSl6B/Wir07jtv0q1ejHflTTpLs9WltzJrCHpM2pplf+qWH/mrXttajeH6jO87sN57lUGV3qMVVrYP8f1cjsciXxncab78FTTWLpbV+99QwwC3hrrWzNFnXnt5epEs0O9S9SngDOaHivlrZ9PF17gmr6d6OpVF/obFzrc6SrGy418yRVctdhLapr+c/m1TvV05sm9elntZPjPwEsr7K+fx5iaLxWUF2vv3czvt8BFwFr2h4JnMI8fvZtv2T7UNvrUo0cf01Sx0yPebmJ1VPU/j2pWqO9QkOd1YB/NHy5EBFFEtuIiAFWpqS1A1+jmoLc4YZS1pO7IS8DTAdeKOsJv96w/59U6/o6az+jtF+esl62ly4BNpD0WUmLl5+tmq0X7Iau4gb4LdVawo9SJak9YvtvVOtRzwDOb5xeCXxZ0lvLdfkmcG4pPxU4sIwOSdLSqm5as0xPYyiWoUp0ngEWk3Q08Jba/t8D31B1o6+3Av8xD331iqvHl1wAHFtG+TekWsu4IJhINbV3cUltzDn1/Uxgd0kflLSopGGqHvPy1uZdzeEsqpthfVLSYqpunjW6JBmnAj8u6x+RtIakVuuJzwa+KmkdSfW7c8/qxbl2599FXV9/Vpuy/RTVMoWTy+d0cUkdX5L1JIbLqP6GfLpc832Ajaj+tnTHMlQjx69KehfV+tZOlc9E/UcN+3dTdVM7AS8Cs8sP9Pz9qPsD1WdzmzLl+DjmTsJ/T/X3LSKaSGIbEbFguI7qZiL1u8pOKGU9SWyPA7agGpW7lCr5qPs+cFSZAnhYk/b/AwynGoW6hWpKZa+UtYa7UK01fJJqCt4JVGs8e+rXVFONX1Dt7qoNx7sReAO40/ajvQq6mo68Kc1HfH8HXAk8XH6+U47bTrVu8CTgeappimN6eXyo1tD9L/Ag1bTLV5lzyudxpfyREk9no9Nd9TUvDqaaafCPEsPZVGslB9q3qEZWn6e6Vr/r2FHWJO9B9cXEM1TX4ut04/9DZa3vR6hmNTxHlUB3rH39f1Tv+y1lCv+fab2O+TdU1+t6qvfwVTr/cqIzXf67aDiHvv6sduazVOtR7weeBg7paQy2n6Vaq38o1bTcw4HdbE/tZgz/DvyXpJeo1qz+vov6a1B9sVf/aRylX5/q/Z1ONdvmZL/5PO2u/r62ZPseqs/BOVSjty9RXbf6v6m9yv6IaEI9W+8eERGx4JJ0NfA727/qZfsdqEb1RtWn+0l6FPiim995NQBJJwCr2u7qLs0R0YUymv8CsH4PlqJEDGkZsY2IiIWCpK2oRqvP7apui/aLA/8J/Cpr2Lqm6hnFm5XppO8C9gf+ONBxRQxWknYvU/uXBn4ITAEeHdioIgaPJLYRETHoSTqdanrgIWUKdE/bv4NqdGQ1qunY0bVlqKa6v0w1xfO/qe5OHRG9swfVso0nqaY8f6qHjxKKGNIyFTkiIiIiIiIGtYzYRkRERERExKC22EAHEAHwoQ99yJdf3uubr0ZERERExNDQ9HnUGbGNBcLUqd29c39ERERERMScMmIbC4RZzzzHM784c6DDiIiIiIgIYKWDPjPQIfRIRmwjIiIiIiJiUMuI7SAmaTbVM84WB2YBpwP/k+cvRkRERETEUJLEdnCbYXs0gKSVgd8BI4Fj5qVTSYvZntUH8UVERERERPS7TEVeSNh+GhgLHKzKMEmnSZoi6S5JOwF0Uj5G0nmSLgauLK//JOliSY9IOljS10qbWyQtX9odIOl2SZMknS9pqVI+XtJPJd0k6WFJew/QpYmIiIiIiIVcEtuFiO2Hqd7TlYEvl7JNgX2B0yUN66QcYGvg87bfV15vAnwaeBfwXeAV2+8EbgY+V+pcYHsr25sD9wH710JaDdgO2A04vjFeSWMltUtqf3b6i31xCSIiIiIiYghKYrvw6Xiu03bAGQC27wceAzbopBzgKtvP1fq6xvZLtp8BpgEXl/IpwKiyvYmkCZKmAPsBG9fa/8n2G7bvBVZpDNT2ONtttttWGPGWeTnniIiIiIgYwpLYLkQkrQvMBp6mxYOLOykHeLnh9cza9hu112/w5vrs8cDBZQT4OGBYrU29fWfHjYiIiIiI6LUktgsJSSsBpwAn2TZwPdUIKpI2ANYCHuikvLeWAZ6StHhHvxEREREREfNT7oo8uA2XNJE3H/dzBvCjsu9k4JQyRXgWMMb2TEmtynsbw7eAW6mmNE+hSnQjIiIiIiLmG1WDexEDq62tze3t7QMdRkRERERELNiajshlKnJEREREREQMaklsIyIiIiIiYlDLGttYIMx65hmeOeWUgQ4jImLIWunAAwc6hIiIiF7LiG1EREREREQMakMqsZU0W9LE2s8RpfxaSW19fKxDJC01j338l6Sde1B/R0nTyrlNlvRnSSt3o91N5fcoSXe3qPOvayTpMknLdjeuiIiIiIiI/jTUpiLPsD16Ph3rEOBM4JXuNpC0qO3ZHa9tH92L406wvVvp7/vAl4FjOmtge5ueHMD2R3oRV0RERERERL8YUiO23SFpF0k3S7pT0nmSRkj6sKTf1+rsKOnisv0LSe2S7pF0XCn7CrA6cI2ka0rZvpKmSLpb0gm1vqaXkdlbga0bYhkvae+y/aik40pcUyRt2MV5iOqZss+X18dKOqy2/25JozpiaNJ+uKRzysjvucDw2r5HJa1YRnjvk3RqOf8rJQ0vdbYqbW+WdGKrkeCIiIiIiIh5NdQS2+ENU5H3qe+UtCJwFLCz7S2AduBrwFXAeyQtXaruA5xbto+03QZsBrxX0ma2fwo8CexkeydJqwMnAO8DRgNbSdqztF8auNv2u23f0EX8U0tcvwAOa1Fne0kTgceBnYHfdH1ZmjoIeMX2ZsB3gS1b1Fsf+LntjYEXgI+X8tOAA21vDcxu1lDS2PKlQPuz0+fKrSMiIiIiIrplqCW2M2yPrv2c27D/PcBGwI0lOfw8sLbtWcDlwO6SFgN2BS4sbT4p6U7gLmDj0r7RVsC1tp8pfZ0F7FD2zQbO72b8F5TfdwCjWtSZUM5tTark8gfd7LvRDlRTqbE9GZjcot4jtifW4yrrb5exfVMp/12zhrbH2W6z3bbCiBG9DDMiIiIiIoa6obbGtisCrrK9b5N951KtV30OuN32S5LWoRo53cr285LGA8Na9NvKq/V1tV2YWX7Ppnvv3UW8mTTPYs4vMprF2cg9iKkjruF0fr4RERERERF9aqiN2HblFmBbSW8DkLSUpA3KvmuBLYADeHMa8luAl4FpklYBPlzr6yWqNa4At1JNU15R0qLAvsB1/XkixXbAX8v2o1TxI2kLYJ0u2l4P7Ffqb0I11bpbbD8PvCTpPaXoU90POSIiIiIiomeG2ojt8DLFuMPlto/oeGH7GUljgLMlLVmKjwIetD1b0iXAGKopytieJOku4B7gYeDGWt/jgP+V9FRZZ/sN4Bqq0czLbF9I/+hYYytgGvDFUn4+8Lmy73bgwS76+QVwmqTJwETgth7GsT9wqqSXqb4UmNbD9hEREREREd0iuzuzTSN6RtII29PL9hHAarb/s1X9trY2t7e3z7f4IiIiIiJiUGq67HGojdjG/LNrGaVeDHiMaqQ7IiIiIiKizyWxjX5R7jjdeNfpiIiIiIiIPpfENhYIrz/zFP/4xXcHOoyIHln1oCMHOoSIiIiIIHdFjoiIiIiIiEEuiW0DSWtKukbSfZLukTTXDY8kHSbJklZs0cd4SXs3lE3vx5g/J+nuEu+9kg4r5ddKauuD/rvsR1KbpJ/O67EiIiIiIiJ6KlOR5zYLONT2nZKWAe6QdJXte6FKfIEPAI8PRHCSFrU9u/b6w8AhwC62n5Q0DPjs/I7LdjuQ2xpHRERERMR8lxHbBrafsn1n2X4JuA9Yo1blx8DhQK+ek6TKiWWEdYqkfUr5juU5uR31TirP1EXSo5KOlnQD8ImGLr8BHGb7yRLzq7ZPre3/hKTbJD0oafvS36IlhtslTZb0pdpxDy9xTZJ0fEPsi0g6XdJ3mpzXv+KXdKyk35SR3oclfaU31yoiIiIiIqI7MmLbCUmjgHcCt5bXHwX+bnuS1PTxSXUnSjqqSflewGhgc2BF4HZJ13cjnFdtb9ekfBPgjk7aLWb7XZI+AhwD7AzsD0yzvZWkJYEbJV0JbAjsCbzb9iuSlq/3A5wF3G27O3d52hDYCVgGeEDSL2y/Xq8gaSwwFmCN5Ud2o8uIiIiIiIi5JbFtQdII4HzgENsvSloKOBLYpZtdfN32H2r9dayx3Q44u0wn/qek64CtgBe76K+3j865oPy+AxhVtncBNqutAx4JrE+V9J5m+xUA28/V+vkl8PtuJrUAl9qeCcyU9DSwCvC3egXb44BxAJuvvUavRsAjIiIiIiIyFbkJSYtTJbVn2e5IDNcD1gEmSXoUeCtwp6RVJZ0maaKky7rTfYvyWcz5fgxr2P9yi3b3AFt2cryZ5fds3vwiQ8B/2B5dftaxfWUpb5Vg3gTsVNbwIulj5Zwntrix1Mzadv3YERERERERfSqJbQNVc4x/Ddxn+0cd5ban2F7Z9ijbo6hGH7ew/Q/bXygJ4ke6cYjrgX3KOteVgB2A24DHgI0kLSlpJPD+bob8feAHklYt8S/ZjTWtVwAHlQQeSRtIWhq4Evi3MjpNw1TkXwOXAedJWsz2H2uJcW4aFRERERERAyajaHPbluquwlMkTSxl37TdndHY7vgjsDUwiWp09HDb/wCQ9HtgMvAQcFd3OrN9maRVgD+XpNzAb7po9iuqacl3ljbPAHvavlzSaKBd0mtUiew3a8f6UUm6z5C0n+03unvSERERERER/UV2ljbGwNt87TV8xRH/PtBhRPTIqgcdOdAhRERERAw1TZd2ZsQ2FgiLr7RakoSIiIiIiOiVrLGNiIiIiIiIQS0jtrFAeP3px/j7SQcOdBgRLa1x8CkDHUJEREREtJAR24iIiIiIiBjUkthGRERERETEoJbEthOSjpR0j6TJkiZKencf9LmjpEualH9U0hHz2n+tv8UkTZX0/YbyayW1le1HJa3YV8fsJJam5xwREREREdEXssa2BUlbA7sBW9ieWRLAJfrreLYvAi7qwy53AR4APinpm85znSIiIiIiYiGVEdvWVgOm2p4JYHuq7SfhXyOd35N0s6R2SVtIukLSXyUdWOpI0omS7pY0RdI+jQeQtJWkuyStK2mMpJNK+XhJP5V0k6SHJe1dyheRdHIZRb5E0mUd+5rYF/gJ8Djwnq5OVtLXSqx3SzqklB0u6Stl+8eSri7b75d0ZtnepVyHOyWdJ2lEKf+QpPsl3QDs1d2LHhERERER0VNJbFu7ElhT0oMlmXxvw/4nbG8NTADGA3tTJZD/VfbvBYwGNgd2Bk6UtFpHY0nbAKcAe9h+uMnxVwO2oxo1Pr7W5yhgU+CLwNbNApc0HHg/cAlwNlWS25KkLYEvAO8u53CApHcC1wPbl2ptwAhJi5e4JpRR7KOAnW1vAbQDX5M0DDgV2L20X7XFcceWLwban53+amchRkREREREtJTEtgXb04EtgbHAM8C5ksbUqnRMG54C3Gr7JdvPAK9KWpYq+Tvb9mzb/wSuA7Yqbd4BjAN2t/14ixD+ZPsN2/cCq5Sy7YDzSvk/gGtatN0NuMb2K8D5wMckLdrJ6W4H/NH2y+W8L6BKSO8AtpS0DDATuJkqwd2eKqF/D7ARcKOkicDngbWBDYFHbD9UpkCf2eygtsfZbrPdtsKIYZ2EFxERERER0VrW2HbC9mzgWuBaSVOoErfxZffM8vuN2nbH68UAddL1U8Aw4J3Aky3q1PtUw++u7AtsK+nR8noFYCfgzy3qN+3X9uuljy8ANwGTSz/rAfeV31fZnmNEWNJoIGt6IyIiIiJivsiIbQuS3i5p/VrRaOCxHnRxPbCPpEUlrQTsANxW9r0A7Ap8T9KOPejzBuDjZa3tKsBcbSW9hWoEdi3bo2yPAr5M59ORrwf2lLSUpKWBj1GNyHbsO6z8ngAcCEwsI7G3UCXQbyvHXkrSBsD9wDqS1it9dDoVOiIiIiIiYl4ksW1tBHC6pHslTaaacntsD9r/kWqEcxJwNXB4mT4MQJmevDvw8x48Ruh84G/A3cAvgVuBaQ119gKu7rjpVXEh8FFJSzbr1PadVCPRt5U+f2X7rrJ7AtV635tLzK+WMsrU6zHA2eUa3QJsaPtVqincl5abR/XkC4GIiIiIiIgeUZ4CM7hIGmF7uqQVqBLRbesJ82DV1tbm9vb2gQ4jIiIiIiIWbE2XUWaN7eBzSbk51RLAtxeGpDYiIiIiImJeJLEdZGzvONAxRERERERELEiS2MYC4dWn/8IDP99joMOImMvbv3zhQIcQEREREV3IzaMiIiIiIiJiUEtiO4RImi1poqR7JE2S9DVJvf4MqHJ1ecRQqzrnNDw2KSIiIiIiok8lsR1aZtgebXtj4APAR4Bj5qG/jwCTbL/YSZ1fAIfPwzEiIiIiIiI6lcR2iLL9NNWzZg8uI6/DJJ0maYqkuyTtBCBpKUm/lzRZ0rmSbpXUVrrZj+oZuUhaWtKlZST4bkn7lDoTgJ0lZT13RERERET0iyQbQ5jth8tU5JWBz5SyTSVtCFwpaQPg34HnbW8maRNgYq2LbYEvle0PAU/a3hVA0sjS3xuS/gJsDtxRP76ksVTJNasvN7yfzjIiIiIiIhZ2GbGNjgccbwecAWD7fuAxYINSfk4pvxuYXGu7vO2XyvYUqpHZEyRtb3tard7TwOqNB7Y9znab7bblRizRl+cUERERERFDSBLbIUzSusBsqsRTrap10sWsjptP2X4Q2JIqwf2+pKNr9YYBM+Y94oiIiIiIiLklsR2iJK0EnAKcZNvA9VRrZilTkNcCHgBuAD5ZyjcCNq118wCwbtm3OvCK7TOBHwJb1OptANzTn+cTERERERFDV9bYDi3DJU0EFgdmUU09/lHZdzJwiqQpZd8Y2zMlnQycLmkycBfVVOSOacaXAjsCf6FKeE+U9AbwOnAQgKRVqO7G/NR8OL+IiIiIiBiCVA3WRTQnaVFgcduvSloP+D9gA9uvSVoN+K3tD3TS/qvAi7Z/3dlx2tra3N7e3qexR0RERETEQqfpUsmM2EZXlgKukbQ41YfoINuvAdh+StKpkt7SybNsX6DclCoiIiIiIqI/JLGNTpW7Hrd1sv/3XbQ/rc+DioiIiIiIqEliGwuEV575C3ecsvtAhxELsS0PvHigQ4iIiIiIfpK7IkdERERERMSglsR2ISJpesPrMZJOGqh4IiIiIiIi5ockttEvJGWae0REREREzBdJPoYISbsDRwFLAM8C+9n+p6RjgbWAdcvv/7H909LmW8B+wBPAVOAO2z8sj/35ObAS8ApwgO37JY0HngPeCdwp6SLgJyUEAzuUm1FFRERERET0mSS2C5fhkibWXi8PXFS2bwDeY9uSvggcDhxa9m0I7AQsAzwg6RfA5sDHqZLUxYA7gTtK/XHAgbYfkvRu4GTgfWXfBsDOtmdLuhj4su0bJY0AXq0HK2ksMBZg1eWH98kFiIiIiIiIoSeJ7cJlhu3RHS8kjeHNR/W8FThX0mpUo7aP1NpdansmMFPS08AqwHbAhbZnlL4uLr9HANsA50n/ejbykrW+zrM9u2zfCPxI0lnABbb/Vg/W9jiqJJmN1l7W83LiERERERExdGWN7dDxM+Ak25sCXwKG1fbNrG3PpvrCQzS3CPCC7dG1n3fU9r/csWH7eOCLwHDgFkkb9sF5REREREREzCGJ7dAxEvh72f58N+rfAOwuaVgZpd0VwPaLwCOSPgGgyubNOpC0nu0ptk8A2qmmPEdERERERPSpJLZDx7FU04cnUImPNKAAACAASURBVN0IqlO2b6danzsJuIAqMZ1Wdu8H7C9pEnAPsEeLbg6RdHepNwP433k6g4iIiIiIiCZkZ2ljNCdphO3pkpYCrgfG2r6zP4610drL+oxvbN8fXUcAsOWBFw90CBEREREx75oumczNo6Iz4yRtRLUe9/T+SmoBllrpbUk8IiIiIiKiV5LYRku2Pz3QMURERERERHQliW0sEKZPfYjrT911oMOIhdQOB1w60CFERERERD/KzaMiIiIiIiJiUEti2wlJP5Z0SO31FZJ+VXv935K+Jumjko7oYd/HSjqsL+Ot9f2opBW7qDNG0ur9cfyG44ySlCnNERERERHRb5LYdu4mYBsASYsAKwIb1/ZvA9xo+yLbxzc2lrQgT/UeA/Qose3l+YwCkthGRERERES/SWLbuRspiS1VQns38JKk5SQtCbwDuKuMfp4EIGm8pB9JugY4QdJ6ki6XdIekCZI2bDxIqzqSPtHxHFhJ15eyjSXdJmmipMmS1m8VfBktvU/SqZLukXSlpOGS9gbagLNKP8MlbSnpuhLDFZJWK31cK+l7kq4D/rO8PqHE8KCk7Uu9RSWdKOn2EteXShjHA9uX43x1Xt+QiIiIiIiIRgvyiOKAs/2kpFmS1qJKcG8G1gC2BqYBk22/Js31KKUNgJ1tz5b0f8CBth+S9G7gZOB9DfXHtahzNPBB23+XtGypeyDwE9tnSVoCWLSL01gf2Nf2AZJ+D3zc9pmSDgYOs90uaXHgZ8Aetp+RtA/wXeDfSh/L2n4vgKTdgcVsv0vSR4BjgJ2B/YFptrcqSf+Nkq4EjijH2a0xMEljgbEAqyw/rIvTiIiIiIiIaC6Jbdc6Rm23AX5EldhuQ5XY3tSizXklqR1R6p5XS36XrFfsos6NwPiSkF5Qym4GjpT0VuAC2w91Ef8jtieW7TuopgY3ejuwCXBViWFR4Kna/nMb6nfEUu9vF2CzMhoMMJIqqX6tVWC2x1El9Ww4aqS7OI+IiIiIiIimkth2rWOd7aZUU5GfAA4FXgR+06LNy+X3IsALtkd30n/LOrYPLCO4uwITJY22/TtJt5ayKyR90fbVnfQ/s7Y9GxjepI6Ae2xv3cX5NPY5mzc/QwL+w/YVc3Qs7dhJbBEREREREfMsa2y7diOwG/Cc7dm2nwOWpZqOfHNnDW2/CDwi6RMAqmze3TqS1rN9q+2jganAmpLWBR62/VPgImCzXp7XS8AyZfsBYCVJW5fjLi5p45Ytm7sCOKhMa0bSBpKWbjhOREREREREn0ti27UpVHdDvqWhbJrtqd1ovx+wv6RJwD3AHj2oc6KkKZLuBq4HJgH7AHdLmghsCPy2F+cEMB44pfSzKLA31c2uJgETefOmWd31K+Be4M4S7y+pRnMnA7PKDbBy86iIiIiIiOhzsrO0MQbehqNGetyR2w10GLGQ2uGASwc6hIiIiIjoG3PduReyxjYWECNWXD/JR0RERERE9EqmIkdERERERMSglhHbWCC8OPUhLv/1RwY6jBiEPrT/ZQMdQkREREQMsIzYRkRERERExKCWxDYiIiIiIiIGtSS23SBptqSJtZ9Rkm7q4z6P6KL+Nxtez9PxOzlOp/1Kmt4fx42IiIiIiOitrLHtnhm2RzeUzfWcV0mL2p49D3125pvA9zpe2O7pc2a7pb/6BZC0mO1Z/dV/REREREQMTRmx7aWOkUtJO0q6RtLvgCmSFpV0oqTbJU2W9KUe9DlS0gOS3l5eny3pAEnHA8PLyO5ZTY5/raQ/SLpf0lmSVPZ9pJTdIOmnki4p5cdKOqx23LsljWrodzVJ15dj3i1p+1r970qaJOkWSauUspUknV/O+3ZJ29aONU7SlcBve3m5IyIiIiIiWsqIbfcMlzSxbD9i+2MN+98FbGL7EUljgWm2t5K0JHCjpCttP9JJnwDft32upIOB8ZJ+Aixn+1QASQd3MsL7TmBj4EngRmBbSe3AL4EdSlxn9/CcPw1cYfu7khYFlirlSwO32D5S0g+AA4DvAD8Bfmz7BklrAVcA7yhttgS2sz2jfoByrcYCrLz8sB6GFxERERERUUli2z1dTRu+rZa47gJsJmnv8noksD7QmNg27dP2VZI+Afwc2Lyb8d1m+28AJVkeBUwHHq7FdTYlieym24HfSFoc+JPtjiT8NeCSsn0H8IGyvTOwURksBniLpGXK9kWNSS2A7XHAOIANRo10D2KLiIiIiIj4lyS2fePl2raA/7B9RW86krQI1UjnDGB54G/daDaztj2b6n1Vi7oAs5hzGvpcw6W2r5e0A7ArcIakE23/FnjddkcS2nEsSn9bNxmVhTmvT0RERERERJ/KGtu+dwVwUBnpRNIGkpbuQfuvAvcB+/LmiCnA67Xt7rgfWLdj7SywT23fo8AWJb4tgHUaG0taG3i6TIX+dUf9TlwJHFxr35MbY0VERERERPRaRmz73q+opgLfWW7i9AywZ5N6jWtsLwd+A3wReJftlyRdDxwFHEM1ZXeypDtt79dVELZnSPp34HJJU4HbarvPBz5Xjn878GCTLnYEvi7pdappzZ/r4pBfAX4uaTLV5+p64MCu4oyIiIiIiJhXenNWaSxsJI2wPb0k2D8HHrL944GOq5m2tja3t7cPdBgREREREbFga7rkMlORF24HlFHZe6huYvXLAY4nIiIiIiKiz2Uq8kKsjM4ukCO0ERERERERfSWJbSwQXpj6EBec9qGBDiMWEHt94fKBDiEiIiIiBpFMRY6IiIiIiIhBrd8SW0nT+6CPUZI+3RfxlP4elTRF0sTys02TOr+StFEfHm/Fst3t6yHpj5L2rL1+QNJRtdfnS9qrN3FEREREREQsbBb0EdtRQJ8ltsVOtkeXn5vqOyQtavuLtu/t42P21E3ANiWmFaget7N1bf/WpU6XJC3a59FFREREREQsQOZrYitpd0m3SrpL0p8lrVLKj5V0hqSrJT0k6YDS5Hhg+zK6+lVJwySdVkZd75K0U2k/RtKFki4vo5vH9CCm6ZL+S9KtwNaSrpXUVvbtIulmSXdKOk/SiFL+qKTjSvkUSRuW8hUkXVli+yVNbkVdznOP2uuzJH20odqNlMS2/L4EWEmVdYAZtv8had9y/LslndDqnGrlw8s1OkDS0pIulTSptN+ndm4nSLqt/Lyti/duRO09mSzp451du4iIiIiIiL42v0dsbwDeY/udwDnA4bV9mwG7UiViR0taHTgCmFBGV38MfBnA9qbAvsDpkoaV9u8C9gNGA5/oSE6buKYkyreW10sDd9t+t+0bOiqVqbtHATvb3gJoB75W62dqKf8FcFgpOwa4oZzfRcBaTY7/K+AL5RgjqRLXyxrq3AFsImmJsv9m4AHgHeX1jeX6nAC8r5zzVrXpy83OaQRwMfA726cCHwKetL257U2A+t16XrT9LuAk4H9KWav37lvANNub2t4MuLob145y/mMltUtqnzb9tSaXKiIiIiIiomvz+67IbwXOlbQasATwSG3fhbZnADMkXUOVqL7Q0H474GcAtu+X9BiwQdl3le1nASRdUOq2N4lhJ9tTa69nA+c3qfceYCOqJJIS7821/ReU33cAHetdd+jYtn2ppOcbO7V9naSfS1q51D3f9qyGOjMl3QNsUeL4AbAuVVL7TqppyFsB19p+ppzzWeX4f2pxThcCP7B9Vnk9BfhhGem9xPaEWt2za787HhfU6r3bGfhULfbnJe3WxbXrqDsOGAfwtlEj3bg/IiIiIiKiO+b3iO3PgJPKiOuXgGG1fY2JTbNEZ66pvT1s38yrtme3ONZVtfW4G9nev7Z/Zvk9mzm/IOjOcc+gGl3+AnBaizo3USWqy9h+HriFKrHdhmqqcmfXotk53Qh8WCXTtP0gsCVVgvt9SUe3OIeO7VbvnZj7nLu6dhEREREREX1mfie2I4G/l+3PN+zbo6yhXQHYEbgdeAlYplbneqqEEEkbUE31faDs+4Ck5SUNB/akSuTmxS3AtrU1pkuVY3amHt+HgeVa1BsPHAJg+54WdW6kSiAnldeTqUZv1wLuAW4F3itpRVU3iNoXuK6T2I4GngVOLvGtDrxi+0zgh1Sjwx32qf3uGGlt9d5dCRzc8ULScvTu2kVERERERPRKfya2S0n6W+3na8CxwHmSJgBTG+rfBlxKlRR92/aTVMncrHKDo69SJWWLSpoCnAuMsd0xcnoD1UjoRKrpvc2mIXdbmeI7Bjhb0uQS14ZdNDsO2EHSncAuwOMt+v4ncB+tR2uhGrFdl5JYlunKTwPttt+w/RTwDeAaquT3TtsXdhHfIcAwST8ANgVukzQROBL4Tq3ekmUN8n8CXy1lx9L8vfsOsFy5AdUkqqnevbl2ERERERERvSJ74Jc2SjoWmG77h71sPwZos31wV3UXBJKWopoCvIXtaQMdT52kR6muZeMXD/2qra3N7e3z9F1EREREREQs/JouyVzQn2O70JG0M3A/8LMFLamNiIiIiIgYjBaIEduIjNhGREREREQ3NB2xnd+P+4lo6rlnH+LM8R8c6DBigHxmzBUDHUJEREREDGKZihwRERERERGDWhLb6JSk2ZImlrsen1dufNXTPsZIOqk/4ouIiIiIiEhiG12ZYXu07U2A14ADBzqgiIiIiIiIuiS20RMTgLdJWl7SnyRNlnSLpM0AWpVHRERERET0pyS20S2SFgM+TPX83eOAu2xvBnwT+G2p1qq8VZ9jJbVLan/xpdf6L/iIiIiIiFioJbGNrgyXNBFoBx4Hfg1sB5wBYPtqYAVJIzspb8r2ONttttvesswS/XwaERERERGxsMrjfqIrM2yPrhdIavbsKNP8mVJ5UHJERERERPSrjNhGb1wP7AcgaUdgqu0XOymPiIiIiIjoNxmxjd44FjhN0mTgFeDzXZRHRERERET0myS20SnbI5qUPQfs0YPy8cD4fggvIiIiIiIC2VkCGQOvra3N7e3tAx1GREREREQs2Jrd1ydrbCMiIiIiImJwy1TkWCBMffYhTv3tBwc6jOhjB3zuioEOISIiIiKGgIzYRkRERERExKCWxLYXJH1MkiVtWCtbXdIfutl+VUnnSPqrpHslXSZpgz6Ia0dJl5Ttj0o6omzvKWmjWr3/krRzL4/xr34jIiIiIiIWBElse2df4AbgUx0Ftp+0vXdjRUmLNbwW8EfgWtvr2d4I+CawSl8GaPsi28eXl3sCG9X2HW37z33Qb0RERERExIBLYttDkkYA2wL7U0tsJY2SdHfZHiPpPEkXA1c2dLET8LrtUzoKbE+0PUGVEyXdLWmKpH1KfztKulbSHyTdL+mskiAj6UOl7AZgr1o8YySdJGkb4KPAiZImSlpP0nhJe5d675d0VznebyQtWcoflXScpDvLvg3r/Zbt8ZJ+KukmSQ/X+lxE0smS7pF0SRmRnivpj4iIiIiI6AtJbHtuT+By2w8Cz0naokW9rYHP235fQ/kmwB0t2uwFjAY2B3amSkZXK/veCRxCNfK6LrCtpGHAqcDuwPbAqo0d2r4JuAj4uu3Rtv/asa+0Hw/sY3tTqpuJHVRrPtX2FsAvgMNaxLwasB2wG9AxkrsXMArYFPhiuRYRERERERH9Ioltz+0LnFO2zymvm7nK9nM97Hs74Gzbs23/E7gO2Krsu83232y/AUykShw3BB6x/ZCrBxKf2cPjvb20f7C8Ph3Yobb/gvL7jnK8Zv5k+w3b9/LmdOrtgPNK+T+Aa5o1lDRWUruk9pdeeq2HoUdERERERFTyuJ8ekLQC8D5gE0kGFgUs6fAm1V9u0c09QKtpuU0fNlzMrG3P5s33zp206Upnx6sfs368zuJSw+9O2R4HjAMYtc7IeTmPiIiIiIgYwjJi2zN7A7+1vbbtUbbXBB6hGqHsrquBJSUd0FEgaStJ7wWuB/aRtKiklahGT2/rpK/7gXUkrVdetxo9fglYpkX7UZLeVl5/lmqUeF7dAHy8rLVdBdixD/qMiIiIiIhoKoltz+xLdUfjuvOBT3e3gzJl+GPAB8rjfu4BjgWeLH1PBiZRJcCHl6m8rfp6FRgLXFpuHvVYi6rnAF8vN4lar6H9F4DzJE0B3gBOadFHT5wP/A24G/glcCswrQ/6jYiIiIiImIuqPCuib0kaYXt6mb59G7BtZ0n6qHVG+sjj3jP/Aoz54oDPXTHQIURERETEwqXpssessY3+comkZYElgG93ltQCrLjC+kmCIiIiIiKiV5LYRr+wveNAxxAREREREUNDEttYIDz93EP85KwPDnQY0Uf+c7+MvkdERETE/JObR0VERERERMSglsQ2IiIiIiIiBrUhm9hKOlLSPZImS5oo6d1d1P+opCPK9p6SNurGMcZL2rtJ+Y6SLulhvCeWeE/sSbuGY04r59rxs3Nv+urkGGMkrd6XfUZERERERHRlSK6xlbQ1sBuwhe2ZklakuntvS7YvAi4qL/cELgHu7ddA5/QlYCXbM7tTWdJitmc1FE+wvVvfh/YvY6ieXftkPx4jIiIiIiJiDkN1xHY1YGpHkmh7qu0nASQ9WhJdJLVJurZsj5F0kqRtgI8CJ5ZRz/UkHSDpdkmTJJ0vaanasXaWNEHSg5LmSiolLS3pN6X9XZL2aFLnImBp4FZJ+0haW9L/ldHm/5O0Vqk3XtKPJF0DnNCdCyHpBEn/Xnt9rKRDy/bXS1yTJR1XykZJuk/SqWUE+UpJw8vIdBtwVrkuwyUdL+ne0v6H3YknIiIiIiKip4ZqYnslsGZJNk+W9N7uNrR9E9XI7ddtj7b9V+AC21vZ3hy4D9i/1mQU8F5gV+AUScMaujwSuNr2VsBOVAnz0g3H/CgwoxzvXOAk4Le2NwPOAn5aq74BsLPtQ5uEv33DVOT1gHOAfWp1PgmcJ2kXYH3gXcBoYEtJO5Q66wM/t70x8ALwcdt/ANqB/WyPBoYDHwM2LnF+pzEYSWMltUtqn/7ia03CjYiIiIiI6NqQTGxtTwe2BMYCzwDnShozD11uUkZlpwD7ARvX9v3e9hu2HwIeBjZsaLsLcISkicC1wDBgrS6OtzXwu7J9BrBdbd95tme3aDehJMcdP3+1fRewsqTVJW0OPG/78RLXLsBdwJ0l7vVLP4/Ynli276BK3hu9CLwK/ErSXsArjRVsj7PdZrttxFs6nQkeERERERHR0pBcYwtQkr9rgWtLQvp5YDwwizcT/sbR1VbGA3vanlQS5B3rh2o8dMNrUY14PtDNYzVT7/PlXrT/A7A3sCrVCG5HXN+3/ct6RUmjgPo639lUo7NzBmTPkvQu4P3Ap4CDgff1IraIiIiIiIhODckRW0lvl7R+rWg08FjZfpRqNBfg4y26eAlYpvZ6GeApSYtTjdjWfULSImXa77pAYwJ7BfAfklRie2c3TuEmqmSRcrwbutGmM+eU/vamSnI74vo3SSNKXGtIWrmLfv51XUq7kbYvAw6husYRERERERF9bqiO2I4AfiZpWaoR2r9QTUsGOA74taRvAre2aH8OcKqkr1Alg98qdR8DpjBn0vsAcB2wCnCg7VdLDtvh28D/AJNLcvso1R2bO/MV4DeSvk41lfoLXZ1wsX2Z8tzhO7b/YPseScsAf7f9FIDtKyW9A7i5xDsd+AzVCG0r46nWEc8APgxcWNYUC/hqN2OMiIiIiIjoEdmNM2Mj5r+2tja3t7cPdBgREREREbFgU7PCITkVOSIiIiIiIhYeSWwjIiIiIiJiUBuqa2xjAfPU8w/x3XM/ONBhRB84cp8rBjqEiIiIiBhiMmIbERERERERg9qgSmwlTZ/H9jtKuqSv4mlxjGslPSBpoqT7JI3tutUc7fs9xi6O3xH/ZEn3Szqp3D06IiIiIiJigTSoEttBZD/bo4FtgRMkLTGvHUqan9PG97O9GbAZMBO4cF47VCWft4iIiIiI6HODPtGQNFrSLWWE8Y+Slivlb5P0Z0mTJN0pab2GdltJukvSug3lwySdJmlK2b9TKR8j6QJJl0t6SNIPuhHeCOBlyrNfJe0i6eYSz3n6/+zdd5ydZZ338c/X0JIAQUhEYIVoaCJgkAE3EBAQ0ccCBMJGjA8GfYyshUUWXVZYYHHFwlqwspHFIIYioRhAKVKMBClDGJKAIFJsqBBKQgkBku/zx30NnBzOtGQmZybzfb9e85r7XPdVfvfJ/PPLVW5p/VL+njI7ehNwSE0sp0iaJuka4MeStpJ0XXnW6yRtWep1VD5d0g8k3SDpQUnvkHR2mUme3lXwtl8APg9sKemtpc9jJS0oP8fUxPqqckmjy1jfB+YCb+jGdxYREREREdEjAz6xBX4M/FuZYZwPnFzKZwDfs/1WYA/gr+0NJO0BnAkcZPvBuv4+BWB7J+Bw4BxJ65V7Y4FJwE7AJEkdJWozJM0D7gO+aHuZpJHAicD+tt8GtALHlr5/CHwA2At4fV1fu5Y4PwR8F/hxedYZwLdLnY7KAV4L7Ad8Frgc+CbwFmAnSWM7iP9ltpcBdwHbS9oVOBJ4O/CPwMcl7dJReeliuxLbLrb/UNu3pKmSWiW1Prv4ha5CiYiIiIiIaGhAJ7aSRgAb2f5VKToH2FvSBsAWti8FsP287edKnTcD04AP2P5jg27HA+eWdvcCfwC2Lfeus73I9vPAPcBWHYTWvpR3S+A4SVtRJXw7AHMktQEfKe23Bx6yfb9tAz+p62uW7SXlehxwXrk+t8TaWTnA5aXf+cDfbc+3vRy4GxjdQfz12l+CPB641Paztp8BLqFKxjsqB/iD7VsadWp7mu0W2y3DN1zl1doRERERETFIramv+1En9/4KrAfsAjzSw7ZLa66X0cX3Z/sxSXOpZjKXANfaPnyFwapZU3fSzbOdDdGN8vaYl7Ni/Mvpxr+/pCFUM9S/BTbrqFonXXQWf0RERERExCob0DO2thcBT0pqnx38v8CvbC8G/izpYABJ60oaVuo8BbwPOE3SPg26nQ1MLu22pZp1vW9l4itj7gI8ANwC7Clp6/Z7pf97gTfW7AE+vGFnlZuBD5brycBNXZSvEklrA18G/mR7HtV3c3CJfTgwAfh1J+URERERERF9bqDN2A6T9Oeaz9+gWtJ7ZkkiH6Ta6wlVkvs/kk4FXgQOa29k+++SPgD8QtJHbd9a0+f3S3/zgZeAKbaXSp1NSr7KDElLgHWB6bbvgOoAKuB8SeuWeifa/p2qVwJdKWkhVVK6Ywf9Hg2cLelzwGM1z9pR+cqaIWlpif+XwEEAtueWQ6duK/XOsn1nebZXlUsavYpxREREREREdEnV9suI5mppaXFra2uzw4iIiIiIiP6t4YzjgF6KHBEREREREZHENiIiIiIiIga0LEWOfuH1Y0Z48lfHNTuM6IavT7yq2SFERERExOCVpcgRERERERGx5kliO8BJer2kCyQ9IOkeST8vrxHqqP5oSQs6uHejpJZujvs9SW1lzCXluk3ScZLOr6s7UtJjNadBR0RERERE9JqB9rqfqKHqHUSXAufY/mApGwtsCvyuL8e2/aky3mjgCttjy+cNgQclDbP9XKk+EZhle2lfxhQREREREYNTZmwHtn2BF22f2V5gu832ryWtL+k6SXMlzZd0UE27tSSdI2mepJnlHcArkHSApN+U9hdJWr87AdleDMwGPlBT/EHg/MYtIiIiIiIiVk0S24FtR+CODu49D0yw/TaqBPjrZYYXYDtgmu2dgcXAJ2sbShoJnAjsX9q3Asf2IK7zqZJZJG0ObAvcUF9J0lRJrZJan1v8Qg+6j4iIiIiIeEUS2zWXgNMkzQN+CWxBtUQZ4E+255TrnwDj69r+I7ADMEdSG/ARYKsejH0FML4sS/4nYKbtZfWVbE+z3WK7ZdiG6/Sg+4iIiIiIiFdkj+3AdjfV/tVGJgOjgF1tvyjpYWC9cq/+HU/1nwVca/vwlQnK9hJJVwETqGZuP7sy/URERERERHRHZmwHtuuBdSV9vL1A0m6S3gGMAB4tSe2+rDjjuqWk9pfGHg7cVNfvLcCekrYufQ7r7KTlDpxPtXx509JfREREREREn0hiO4DZNtWs6LvK637uBk4BHgFmAC2SWqlmb++tafpb4CNlmfLGwA/q+n0MmAKcX+rcAmzfw/CuATYHLixxRkRERERE9IksRR7gbD9CtY+1kXEdlO/QQV/71FxfD+zWjfEfpjrEqr78Jaql0BEREREREX1KmUyL/qClpcWtra3NDiMiIiIiIvo3NSrMUuSIiIiIiIgY0DJjG/3Ca7ce4f2+3tHK6Wi2iw+6qtkhRERERERAZmwjIiIiIiJiTZTEdg0m6ZuSjqn5fLWks2o+f13SsT3o7xRJx/V2nBEREREREasiie2a7WZgDwBJrwFGAm+pub8HMGd1BSNpyOoaKyIiIiIiBo8ktmu2OZTEliqhXQA8Lem1ktYF3gy8W9LtkhZImiZJAJKOlnSPpHmSLqjpcwdJN0p6UNLR7YWSPizpNkltkv6nPYmV9IykUyXdSsevH4qIiIiIiFhpSWzXYOUdty9J2pIqwf0N0J5gtgDzgO/a3s32jsBQ4P2l+fHALrZ3Bo6q6XZ74N3A7sDJktaW9GZgErCn7bHAMmByqT8cWGD77bZv6sPHjYiIiIiIQWqtZgcQfa591nYP4BvAFuV6EdVS5X0lfR4YBmwM3A1cTpX0zpB0GXBZTX9X2l4KLJX0KLAp8E5gV+D2MuE7FHi01F8GXNwoMElTgakAQ0et10uPGxERERERg00S2zVf+z7bnaiWIv8J+FdgMXA2cBbQYvtPkk4B2jPM9wF7AwcC/yGpfW/u0pq+l1H9DQk4x/a/Nxj/edvLGgVmexowDarX/azsA0ZERERExOCWpchrvjlUy4ufsL3M9hPARlTLkX9T6iyUtD4wEV4+aOoNtm8APl/qr9/JGNcBEyW9rrTfWNJWffI0ERERERERdTJju+abT3Ua8nl1ZevbXijph+Xzw8DtdAvZewAAIABJREFU5f4Q4CeSRlDNxn7T9lNlmfGr2L5H0onANSUpfhH4FPCHPnieiIiIiIiIFcjOCtBovtduPcL7fT2HJvdXFx90VbNDiIiIiIiAauLt1YVJbKM/aGlpcWtra7PDiIiIiIiI/q1hYps9thERERERETGgZcY2+oURW7/Oe3x9YrPDGHR+cdD3mx1CRERERERPZMY2IiIiIiIi1jxJbCMiIiIiImJAS2I7QEhaJqmt5uf41TDmMZKG1Xz+uaSNumjzsKSRfR1bREREREREu7zHduBYYnvsah7zGOAnwHMAtt+7msePiIiIiIjoUmZsBzhJX5F0j6R5kv67lB0maYGkuyTNLmVDJJ0u6fZS9xOlfB9JN0qaKeleSTNUORrYHLhB0g2l7suzsZIuk3SHpLslTW0Q13BJV5YYFkiatLq+k4iIiIiIGFwyYztwDJXUVvP5y8C1wARge9uuWSZ8EvBu23+pKfsYsMj2bpLWBeZIuqbc2wV4C/AIMAfY0/a3JR0L7Gt7YYN4Pmr7CUlDgdslXWz78Zr77wEesf0+AEkj6jsoCfFUgPVGrd/T7yMiIiIiIgLIjO1AssT22JqfC4HFwPPAWZIOoSwZpkpOp0v6ODCklB0AHFGS41uBTYBtyr3bbP/Z9nKgDRjdjXiOlnQXcAvwhpq+2s0H9pf0VUl72V5U34HtabZbbLess+HQ7n0LERERERERdZLYDmC2XwJ2By4GDgauKuVHASdSJZxtkjahet/TZ2oS4zfabp+xXVrT7TK6mMmXtA+wPzDO9luBO4H16mL7HbArVYL7ZUknrcqzRkREREREdCRLkQcwSesDw2z/XNItwO9L+RjbtwK3SvoAVYJ7NfDPkq63/aKkbYG/dDHE08AGQP1S5BHAk7afk7Q98I8NYtsceML2TyQ9A0xZ+SeNiIiIiIjoWBLbgaN+j+1VwBnAzyStRzUj+9ly73RJ25Sy64C7gHlUS4znShLwGNUsb2emAb+Q9Ffb+9aNfZSkecB9VMuR6+1U4lgOvAj8c7efNCIiIiIiogdku9kxRNDS0uLW1tZmhxEREREREf2bGhVmj21EREREREQMaElsIyIiIiIiYkDLUuToF0Zsvbn3PP3/NTuMNdrPJ5za7BAiIiIiIlZVliJHRERERETEmieJbXSpvK4nIiIiIiKiX0piGytF0pBmxxAREREREQFJbKMHJO0j6QZJ5wHzJa0n6UeS5ku6U9K+pd4USZdIukrS/ZK+1uTQIyIiIiJiDbZWswOIAWd3YEfbD0n6VwDbO0naHrhG0ral3lhgF2ApcJ+k79j+U21HkqYCUwHWGzVitT1ARERERESsWTJjGz11m+2HyvV44FwA2/cCfwDaE9vrbC+y/TxwD7BVfUe2p9lusd2yzobDVkPoERERERGxJkpiGz31bM11w6O2i6U118vI6oCIiIiIiOgjSWxjVcwGJgOUJchbAvc1NaKIiIiIiBh0ktjGqvg+METSfOBCYIrtpV20iYiIiIiI6FWy3ewYImhpaXFra2uzw4iIiIiIiP6t4XbIzNhGRERERETEgJbENiIiIiIiIga0nFQb/cL9T/2N9116erPDWGNdOeFzzQ4hIiIiIqLPZMY2IiIiIiIiBrQktv2MpGWS2mp+Rku6uYd9HCNpWCf3R0l6UdIn6sp/LmmjBvVPkXRcZ+WS1pN0raSTy+eby+/Rkj7Uk/gjIiIiIiJ6Iolt/7PE9tian4dt71FfSdKQTvo4BugwsQUOA24BDq8ttP1e20/1NGBJ6wAXA3fY/s/SV3vMo4EkthERERER0WeS2A4Akp4pv/eRdIOk84D5koZLulLSXZIWSJok6Whgc+AGSTd00OXhwL8C/yBpi5pxHpY0slyfIOk+Sb8EtuskvLWAC4D7bR9fHzPwFWCvMvv82ZX7BiIiIiIiIjqWw6P6n6GS2sr1Q7Yn1N3fHdjR9kOSDgUesf0+AEkjbC+SdCywr+2F9Z1LegPwetu3SfopMAn4Rl2dXYEPArtQ/Y3MBe7oIN7PA7+0fUwH948HjrP9/gaxTAWmAqw36lUroCMiIiIiIrolM7b9T+1S5PqkFuA22w+V6/nA/pK+Kmkv24u60f8HgZ+W6wuoW45c7AVcavs524uBWZ30dxMwTtK23Rh7Bban2W6x3bLOhsN72jwiIiIiIgJIYjsQPdt+Yft3wK5UCe6XJZ3UjfaHA1MkPUyVsL5V0jYN6rmb8cym2tP7C0mbd7NNREREREREr0liO4CVRPI52z8B/ht4W7n1NLBBg/rbAcNtb2F7tO3RwJepZnFrzQYmSBoqaQPgA53FYfti4HTgqganKjeMJSIiIiIiorcksR3YdgJuK3tyTwD+q5RPo5pBrT886nDg0rqyi3n16chzgQuBtnL/110FYvtM4BJglqT1am7NA14qB1zl8KiIiIiIiOh1sru74jSi74zY+h88/vR/aXYYa6wrJ3yu2SFERERERPQGNSxMYhv9QUtLi1tbW5sdRkRERERE9G8NE9ssRY6IiIiIiIgBLe+xjX7h/qce5X2XfLfZYayRrjzk080OISIiIiKiT3U5YytpW0nXSVpQPu8s6cS+Dy0iIiIiIiKia91ZivxD4N+BFwFsz+PVr4cZcCQtk9RW8zN6Ffs7UNLx5foUScd1o83hkk6QNEXSd0vZaySdI+lsVX7e4BU6HY5Ryv9S81xf6SzWVVUbh6Tpkib2Rr8RERERERHd1Z2lyMNs3yatsEf3pT6KZ3VaYntsb3VmexYwq4fN3gN8m+q1Paj6ks8E1gaOdHWy13tXIpxv2v7vRjckrbWSsUZERERERPRL3ZmxXShpDGCAMiP31z6NqgkkrV+WXM+VNF/SQaV8tKR7JZ0laYGkGZL2lzRH0v2Sdi/1Xp51relzjKS5NZ+3kXRHuRYwFphb0+QMYBPgCNvLS72HJY0s1ydIuk/SL4HtevBs0yV9o7zX9qt1M8SjJF0s6fbys2cpP6XMGt8o6UFJR9f012kckt4p6dKaz++SdEl3442IiIiIiOiJ7szYfgqYBmwv6S/AQ8DkPo1q9Rgqqa1cPwQcBkywvbgkkrdIap/V3LrcnwrcDnwIGA8cCHwBOLjRALYfkLRI0ljbbcCRwPRyexfgLtsus+EfAn4L7GP7VTPiknalWgK+C9W/21zgjg6e7bOSPlyu/6383hbY3/YySVNq6p5BNcN7k6QtgauBN5d72wP7AhsA90n6AbBzN+K4HviepFG2HyvP/aMOYo2IiIiIiFglXSa2th8E9pc0HHiN7af7PqzVYoWlyJLWBk6TtDewHNgC2LTcfsj2/FLvbuC6kpDOB0Z3Mc5ZwJGSjgUmAbuX8vcAv6ipN5cqkdwdmNOgn72AS20/V+LobCnxCkuRJR0OXGR7WYO6+wM71Cw131DSBuX6SttLgaWSHqX6PrqMo3w35wIflvQjYBxwRH09SVOp/rOA9Ua+tpPHiYiIiIiI6FiXia2kTYCTqWYoLekm4FTbj/d1cKvZZGAUsKvtFyU9DKxX7i2tqbe85vNyuv4OL6b6/q4H7qj53g4ADq2pdy9wEvBTSe+2fXeDvtzNZ2nk2Q7KXwOMs72ktrAkurXPvYxXnrU7cfwIuBx4niqpftUstO1pVKsBGLH1lqvybBERERERMYh1Z4/tBcBjVEnYxHJ9YV8G1SQjgEdLUrsvsFVvdGr7earlvT+gLMeVNAJYq/4/B2zfDBwFXFmWBdeaDUyQNLTMqH6gN+IDrgFeftGppK4O1OpWHLYfAR4BTuSV5dcRERERERG9rjt7bDe2/cWaz/8lqeGe0gFuBnC5pFagjWoGtTf7PoQqiQR4F/DLRhVtXyFpFHCVpL1qyudKurDE9gfg170U29FU+2HnUf09zKZKrhvqYRwzgFG27+mlWCMiIiIiIl5F1RtlOqkg/TfQCvy0FE0E3mL75D6ObY1R3vM6wvZ/lM9nAWfZvqW5kfWtcvLynbb/t6u6I7be0uO/9vnVENXgc+Uhn+66UkRERETEwKCGhd1IbJ8GhlPtsQQYwiv7NW17w96KcE1UXnszBtjP9sJmx7O6lNcaPQu8qxxA1amWlha3trb2fWARERERETGQNUxsu3Mq8gZd1YmO2Z7Q7BiawfauzY4hIiIiIiIGhy4Pj5I0U9J7JXXnoKmIiIiIiIiI1ao7S5H3B44E/hG4CJhuuzcPVopgxJjRHv+1E5odxoB35aEfb3YIERERERF9qeFS5C5nYW3/0vZk4G3Aw8C1km6WdKSktXs3xoiIiIiIiIie6dbyYkmbAFOA/wfcCZxBleheu6oBSFomqU3SAkkXSRrWSd2xkt7bw/6fKb83lzRzVeNdVZKmSNq85vPDkkY2qHegpONXb3QrT9LBknZodhwRERERETH4dJjYSppefl9C9a7SYcAHbB9o+0LbnwHW74UYltgea3tH4AU6eYcqMBboUWLbzvYjtieuTNteNgXYvKtKtmfZ/kpvDixpSG/2V9PvWsDBQBLbiIiIiIhY7Tqbsd25/P6u7R1sf9n2X2sr2G7p5Xh+DWwtabiksyXdLulOSQdJWgc4FZhUZngnSXpHuW4r9To8wVnSaEkLyvWtkt5Sc+9GSbs2GrdBP5J0eplhni9pUinfp/QzU9K9kmZIUl3biUALMKPEPLTc+oykuaW/7UvdKeU9sEg6rIx3l6TZDWLaR9JsSZdKukfSme2HfUl6RtKpkm4Fxkk6tvS1QNIxNd/NvZLOkTSvPMOwcm9XSb+SdIekqyVtVvOdnSbpV8C/AQcCp5fnGiNpbk1825TX/0RERERERPS6zhLbYZJ2AZ6S9Lb6n94OpMz6/R9gPnACcL3t3YB9gdOBtYGTgAvLDO+FwHHAp2yPBfYClnRzuAuAfyrjbgZsbvuORuNKGl7X9hCqmeO3AvuXOpuVe7sAx1DNXL4J2LO2oe2ZQCswuTxDe7wLbb8N+EF5pnonAe+2/VaqBLKR3YF/BXaiem/uIaV8OLDA9tupvp8jgbdTHQb28fJvDLAdMM32zsBi4JNlD/V3gInl9T1nA1+qGXMj2++w/SVgFvC58lwPAIskjS31jgSm1wcsaaqkVkmtLyx+uoPHioiIiIiI6Fxn77HdAvg6jU+dMrBfL8UwVFJbuf418L/AzcCBktqTvPWALRu0nQN8Q9IM4BLbf+7mmD+l2h98MlWCe1EpP6CDcX9b03Y8cL7tZcDfy4zlblTJ4G3tMZRnGg3c1I14Lim/7+CVhLTWHGC6pJ/W1K13m+0Hy9jnlzhnAsuAi2tiv9T2s6XeJVT/ITAL+JPtOaXeT4CjgauAHakODAMYAtTO2l/YyTOdBRwp6VhgElXivQLb04BpUJ2K3ElfERERERERHeossf297d5KXjuzpMy4vqws4T3U9n115W+v/Wz7K5KupNp3e4uk/bvzKiLbf5H0uKSdqZKuT7QP0WjcOg2Ply6W1lwvo/Pvt1G7hm1sH1We/X1Am6Sxth+vr9bB5+dLEg6dx96ovYC7bY/roM2znfR3MdV/HFwP3NEg3oiIiIiIiF7RrVORm+Bqqn2nAqhZLvs08PI+WkljbM+3/VWqJb7b92CMC4DPAyNsz+9i3Fqzqfb5DpE0CtgbuK0H467wDN1RnvNW2ycBC4E3NKi2u6Q3lr21k2g8UzwbOFjSsLLEegLVLDnAlpLaE9jDS/v7gFHt5ZLWrt2b3Nlz2X6e6vv8AfCjHjxuREREREREj3SW2P7baovi1b5Itad2Xjnw6Yul/AZgh3JA0STgmPZDlaj2j/6iB2PMBD5ItSy5q3FrXQrMA+6imo38vO2/9WDc6cCZdYdHdeX0crDUAqrk9K4GdX4DfAVYADxU4lyB7bll/NuAW4GzbN9Zbv8W+IikecDGwA9svwBMBL5avuM2YI8OYrwA+JyqQ7fGlLIZVDO/13TzOSMiIiIiInpMdrY2DnSS9gGOs/3+lWw/GriivHKp15S9yiNs/0dXdVtaWtza2tqbw0dERERExJqn4fbK7u4BjegRSZdSnc68OvZpR0RERETEINZlYitpR9sLVkcwsXJs3wjcuArtH6Y6/bjX2J7Qm/1FRERERER0pDsztmdKWodqb+Z5tp/q25BiMPr9k4/z/pk/bnYYA9YVE49odggREREREU3T5anItscDk6lO4m2VdJ6kd/V5ZBERERERERHd0K3X/di+HziR6qTkdwDflnSvpEP6MrhYOZKeqfs8RdJ3V7KvsZLeW/P5QEnHr2qMERERERERvaXLxFbSzpK+SfU6mP2AD9h+c7n+Zh/HF803Fng5sbU9y/ZXmhhPRERERETECrqzx/a7wA+BL9he0l5o+xFJJ/ZZZNEnJI0CzgS2LEXH2J4jaXfgW8BQqncCH0n1PtxTgaGSxgNfLvdbbH9a0nRgMdACvJ7qnb4zJb2G6u/mHaWP1wBn2565mh4zIiIiIiIGke4ktpfYPre2QNK/2D6jvjz6jaGS2mo+bwzMKtdnAN+0fZOkLYGrgTcD9wJ7235J0v7AabYPlXQSJZGFallz3VibAeOB7csYM4FDgNHATsDrqGb7z64PUtJUYCrA0JGbrOozR0RERETEINWdxPYIqpm8WlOoEqTon5bYHtv+oSSjLeXj/sAO0svvNd5Q0gbACOAcSdsABtbu5liX2V4O3CNp01I2HriolP9N0g2NGtqeBkwD2GjMG93dh4uIiIiIiKjVYWIr6XDgQ8AbJc2qubUB8HhfBxZ95jXAuNpl5QCSvgPcYHuCpNF0/724S2u7qfsdERERERHR5zqbsb0Z+CswEvh6TfnTwLy+DCr61DXAp4HToTr12HYb1YztX0qdKTX1n6b6z4yeuAn4iKRzgFHAPsB5Kx9yRERERERExzpMbG3/AfgDMG71hROrwdHA9yTNo/r3nw0cBXyNainyscD1NfVvAI4ve3a/3M0xLgbeCSwAfgfcCizqnfAjIiIiIiJWJLvx1kZJN9keL+lpqj2XL98CbHvD1RFgDEyS1rf9jKRNgNuAPW3/raP6LS0tbm1tXX0BRkRERETEQNRw22NnM7bjy++eLkONALhC0kbAOsAXO0tqIyIiIiIiVkV3TkVG0hBg09r6tv/YV0HFwGd7n2bHEBERERERg0OXia2kzwAnA38HlpdiAzv3YVwxyPz+ySd4/8wLmh3GgHXFxA82O4SIiIiIiKbpzoztvwDb2c4rfiIiIiIiIqLf6U5i+ydyou0aS9IyYD6wNvAScA7wLdvLO20YERERERHRT3QnsX0QuFHSlcDS9kLb3+izqGJ1WmJ7LICk11G9b3YE1fLzl0lay/ZLKzuIpCG2l61SpBEREREREQ28pht1/ghcS3W67QY1P7GGsf0oMBX4tCpTJF0k6XLgGknnSjqovb6kGZIOlDRE0umSbpc0T9Inyv19JN0g6TyqWeGIiIiIiIhe1+WMre3/BJA03PazfR9SNJPtByW9BnhdKRoH7Gz7CUnvAD4L/EzSCGAP4CPAx4BFtneTtC4wR9I1pf3uwI62H6ofS9JUqkSaoSNH9ulzRURERETEmqvLGVtJ4yTdA/y2fH6rpO/3eWTRTLUvPb7W9hMAtn8FbF2WLB8OXFyWJx8AHCGpDbgV2ATYprS/rVFSW/qbZrvFdss6G2YRQERERERErJzu7LH9FvBuYBaA7bsk7d2nUUXTSHoTsAx4tBTVz9KfC0wGPgh8tL0Z8BnbV9f1tU+D9hEREREREb2qO3tssf2nuqIcArQGkjQKOBP4rm13UG06cAyA7btL2dXAP0tau/SzraThfRxuREREREQE0M3X/UjaA7CkdYCjKcuSY40wtCwhbn/dz7lAhyde2/67pN8Cl9UUnwWMBuZKEvAYcHCfRRwREREREVGjO4ntUcAZwBbAn4FrgE/1ZVCx+tge0sm96VQztC+TNIxq/+z5NfWWA18oP7VuLD8RERERERF9Rh2vOI1YkaT9gbOBb9j+Vm/23dLS4tbW1t7sMiIiIiIi1jxqVNjljK2kNwKfoVpq+nJ92wf2VmQxMNj+JbBls+OIiIiIiIio1Z2lyJcB/wtcDizv23BisPr9k0/xgZmXNjuMfu3yiROaHUJERERERL/UncT2edvf7vNIIiIiIiIiIlZCdxLbMySdTHVo1NL2Qttz+yyqiIiIiIiIiG7qTmK7E/B/gf14ZSmyy+foxyQ9Y3v9ms9TgBbbn+6kzcHA72zfU1d+AnBY+bgTML9cn91oRl/SjcBxtnMiVERERERE9KnuJLYTgDfZfqGvg4l+4WDgCmCFxNb2l4AvwcsJ89gmxBYREREREfEqr+lGnbuAjfo6kFi9JG0l6TpJ88rvLSXtARwInC6pTdKYLvoYLWlBzefjJJ1SU+XDkm6WtEDS7n3zJBERERERMdh1Z8Z2U+BeSbez4h7bvO6n/xsqqa3m88bArHL9XeDHts+R9FHg27YPljQLuML2zF4Yf7jtPSTtTfX+2x1rb0qaCkwFGDpyVC8MFxERERERg1F3EtuT+zyK6CtLapcMt++xLR/HAYeU63OBr/XB+OcD2J4taUNJG9l+qv2m7WnANICNxmztPhg/IiIiIiIGgS4TW9u/qv0saU/gQ8CvGreIAWplEsuXWHE5+3pd9JnkNSIiIiIiel139tgiaaykr0l6GPgv4Ld9GlWsDjcDHyzXk4GbyvXTwAbd7OPvwOskbSJpXeD9dfcnAUgaDyyyvWjVQo6IiIiIiHi1DmdsJW1LlfgcDjwOXAjI9r6rKbboW0cDZ0v6HPAYcGQpvwD4oaSjgYm2H+ioA9svSjoVuBV4CLi3rsqTkm4GNgQ+2tsPEBERERERAVWi2viGtBz4NfAx278vZQ/aftNqjC8GiZaWFre25pW3ERERERHRKTUq7Gwp8qHA34AbJP1Q0js76iQiIiIiIiKiWTpMbG1fansSsD1wI/BZYFNJP5B0wGqKLyIiIiIiIqJTHS5FblhZ2hg4DJhke78+iyoGnY3GbON3fPWMZofRb/1s4nubHUJERERERH/Q46XIr2L7Cdv/k6Q2IiIiIiIi+oseJbbR+yT9g6SfSbpf0gOSzpC0Trk3VtJ7a+qeIum4Jsa6Qjyl7GBJJ3XSZidJ0/s8uIiIiIiIGLSS2DaRJAGXAJfZ3gbYFlgf+FKpMhbotTWokoasYheN4vk88P2OGtieD/yDpC1XceyIiIiIiIiGktg2137A87Z/BGB7GdUhXR+VtCFwKjBJUpukSaXNDpJulPRgedcsAJI+LOm2Uvd/2pNYSc9IOlXSrcC42sFLP9+SdLOkBZJ2L+XDJZ0t6XZJd0o6qMwirxBPedfxUtsLS7vDSj93SZpdM9TlVO9EjoiIiIiI6HVJbJvrLcAdtQW2FwN/BEYDJwEX2h5r+8JSZXvg3cDuwMmS1pb0ZmASsKftscAyYHKpPxxYYPvttm9qEMNw23sAnwTOLmUnANfb3g3YFzgdWLtBPHsCc2v6Ogl4t+23AgfWlLcCe9UPLGmqpFZJrS8sXtTpFxUREREREdGRtZodwCAnoNGx1B2VA1xpeymwVNKjwKbAO4Fdgdur1c0MBR4t9ZcBF3cSw/kAtmdL2lDSRsABwIE1+3nXAxotJd4MeKzm8xxguqSfUi2xbvcosHl9Y9vTgGlQnYrcSYwREREREREdSmLbXHcDh9YWlCXIbwAeoEpW6y2tuV5G9W8o4Bzb/96g/vNliXNH6hNKl/4OtX1fXWxvr6u7BBjxckP7qFLnfUCbpLG2H6dKjJd0EkNERERERMRKy1Lk5roOGCbpCHj5cKevA9NtPwc8DWzQzX4mSnpd6WdjSVt1M4ZJpc14YJHtRcDVwGfK4VZI2qXUrY/nt8DW7R8kjbF9q+2TgIVUCTpUh2It6GY8ERERERERPZLEtolsG5gAHCbpfuB3wPPAF0qVG6gOi6o9PKpRP/cAJwLXSJoHXEu1TLg7npR0M3Am8LFS9kWqPbXzJC0onxvFMxvYpT0BBk6XNL+0mQ3cVcr3Ba7sZjwRERERERE9oiq3isFI0o3AcbZbV6GPM4DLbf+yg/vrAr8Cxtt+qaN+Wlpa3Nq60mFERERERMTgoEaFmbGNVXUaMKyT+1sCx3eW1EZERERERKyKHB41iNnepxf6+Dswq5P79wP3r+o4ERERERERHUliG/3C7598moNnXt/sMPqNyybu1+wQIiIiIiIGjCxFjoiIiIiIiAEtie1KkPRMD+vvI+mKPohjtKQl5ZTi9p8tJc3sxTF69KwRERERERGrW5YiDyCS1mpwCNMDtsfWlU3sZtuIiIiIiIgBLzO2q6DMxN4oaaakeyXNaH+nq6T3lLKbgENq2mws6TJJ8yTdImnnLspPkTRN0jXAj7sR0+jyHlkkTZF0kaTLqd5xO1zS2ZJul3SnpINq6v1M0lWS7pN0coN+15d0naS55V21B9XcO6LEfZekc0vZKEkXl7Ful7TnKnzVERERERERHcqM7arbBXgL8AgwB9hTUivwQ2A/4PfAhTX1/xO40/bBkvajSlbHdlIOsCvVe2CXNBh/jKS2cj0HOL3u/jhgZ9tPSDoNuN72RyVtBNwmqf39s7sDOwLPAbdLurLu/bbPAxNsL5Y0ErhF0ixgB+AEYE/bCyVtXOqfAXzT9k2StgSuBt5cG5ikqcBUgKEjX9fg0SIiIiIiIrqWxHbV3Wb7zwAlwRwNPAM8VF51g6SfUBI4YDxwKIDt6yVtImlEJ+UAszpIaqFuKbKk0XX3r7X9RLk+ADhQ0nHl83pU75ltr/d46eOSEk9tYivgNEl7A8uBLYBNqZL3mbYXltjbx9of2KFMYANsKGkD20+3F9ieBkwD2GjMdu7g+SIiIiIiIjqVxHbVLa25XsYr32lHiZoalLmTcoBnVy60V7UVcKjt+1YISHo7r463/vNkYBSwq+0XJT1MlRirQV3QoQ9fAAAgAElEQVSolrmP6yQhj4iIiIiI6BXZY9s37gXeKGlM+Xx4zb3ZVEkikvYBFtpe3El5b7oa+EzNPuBdau69q+zzHQocTLWsudYI4NGS1O4LbFXKrwP+SdImpc/2pcjXAJ9ubyyp/oCriIiIiIiIXpEZ2z5g+/myf/RKSQuBm6j2rwKcAvxI0jyq/awf6aK8N30R+BYwryS3DwPvL/duAs4FtgbOq9tfCzADuLzsH26jSt6xfbekLwG/krQMuBOYAhwNfK88z1pUiftRffBMERERERExyMnO1sbBTtIUoMX2p7uq21daWlrc2lqfS0dERERERKyg0RbOLEWOiIiIiIiIgS1LkQPb04HpTQ4jIiIiIiJipSSxjX7hgSef5ZCLf9PsMJrukkPHNTuEiIiIiIgBJ0uRIyIiIiIiYkBLYrsGk/RMzfV7Jd0vaUtJR0k6opRPkbR5F/1MkfTdvo43IiIiIiJiZWQp8iAg6Z3Ad4ADbP8ROLPm9hRgAfBIE0KLiIiIiIhYZZmxXcNJ2gv4IfA+2w+UslMkHSdpItACzJDUJmmopN0k3SzpLkm3SdqgdLW5pKvKrO/Xavo/QNJvJM2VdJGk9Uv5w5L+s5TPl7T9an70iIiIiIgYJJLYrtnWBX4GHGz73vqbtmcCrcBk22OBZcCFwL/YfiuwP7CkVB8LTAJ2AiZJeoOkkcCJwP6231b6OrZmiIWl/AfAcfXjS5oqqVVS69LFT/bOE0dERERExKCTxHbN9iJwM/CxbtbfDvir7dsBbC+2/VK5d53tRbafB+4BtgL+EdgBmCOpDfhIKW93Sfl9BzC6fjDb02y32G5Zd8PX9uzJIiIiIiIiiuyxXbMtB/4J+KWkL9g+rYv6AtzBvaU118uo/nYEXGv78C7atNePiIiIiIjodZmxXcPZfg54PzBZUqOZ26eB9n2091Ltpd0NQNIGkjpLSG8B9pS0dak/TNK2vRd9RERERERE1zKLNgjYfkLSe4DZkhbW3Z4OnClpCTCOah/tdyQNpdpfu38n/T4maQpwvqR1S/GJwO96+REiIiIiIiI6JLujlacRq89rx7zZ+37t7GaH0XSXHDqu2SFERERERPRnalSYGdvoF8a8dniSuoiIiIiIWCnZYxsREREREREDWmZso1948MklHHbx/GaH0acuOnSnZocQEREREbFGyoxtREREREREDGhJbCMiIiIiImJAS2I7QEk6QdLdkuZJapP0dkkPSxrZ7NgiIiIiIiJWp+yxHYAkjQPeD7zN9tKSzK7T5LAiIiIiIiKaIjO2A9NmwELbSwFsL7T9SLn3GUlzJc2XtD2ApN0l3SzpzvJ7u1I+RdJlki6X9JCkT0s6ttS7RdLGpd6Nkr5V2i6QtHsp37i0n1fq79xZeURERERERF9IYjswXQO8QdLvJH1f0jtq7i20/TbgB8BxpexeYG/buwAnAafV1N8R+BCwO/Al4LlS7zfAETX1htveA/gkcHYp+0/gTts7A18AftxF+QokTZXUKql16eIne/4tREREREREkKXIA5LtZyTtCuwF7AtcKOn4cvuS8vsO4JByPQI4R9I2gIG1a7q7wfbTwNOSFgGXl/L5QO1M6/ll7NmSNpS0ETAeOLSUXy9pE0kjOiq3vajuOaYB0wA2HvMWr8JXEhERERERg1gS2wHK9jLgRuBGSfOBj5RbS8vvZbzy7/tFqgR2gqTRpR119QGW13xezop/H/WJpwE1Cq2T8oiIiIiIiF6XpcgDkKTtyuxru7HAHzppMgL4S7mespLDTipjjwcWldnX2cDkUr4P1TLoxZ2UR0RERERE9LrM2A5M6wPfKcuBXwJ+D0ylOim5ka9RLUU+Frh+Jcd8UtLNwIbAR0vZKcCPJM0DnuOVWeOOyiMiIiIiInqd7KwQjc5JuhE4znZrX43R0tLi1tY+6z4iIiIiItYMjbY9ZilyREREREREDGxZihxdsr1Ps2OIiIiIiIjoSBLb6BceeuoFjriks/OvBq4fH7JVs0OIiIiIiFijZSlyREREREREDGhJbAcgScsktUm6S9JcSXv0Ur+jJS3o4N75kuZJ+mwP+xwr6b29EV9EREREREQjWYo8MC2xPRZA0ruBLwPvqK0gaYjtZb0xmKTXA3vYXpk1tWOBFuDnvRFLREREREREvczYDnwbAk8CSNpH0g2SzgPmSxoi6XRJt5fZ1k+UeutLuq7M9s6XdFB9p5LeJOlOSbsB1wCvK7PEe0n6eOnzLkkXSxpW2hwmaUEpny1pHeBUYFJpO2l1fSkRERERETF4ZMZ2YBoqqQ1YD9gM2K/m3u7AjrYfkjQVWGR7N0nrAnMkXQP8CZhge7GkkcAtkma1dyBpO+AC4EjbbZIOBK6omSW+x/YPy/V/AR8DvgOcBLzb9l8kbWT7BUknAS22P13/ECW+qQDDR27Rq19QREREREQMHklsB6bapcjjgB9L2rHcu832Q+X6AGBnSRPL5xHANsCfgdMk7Q0sB7YANi11RgE/Aw61fXcH4+9YEtqNgPWBq0v5HGC6pJ8Cl3T1ELanAdMANtl6Z3f92BEREREREa+WxHaAs/2bMus6qhQ9W3NbwGdsX13bRtKUUn9X2y9Kephq9hdgEdWM7p5AR4ntdOBg23eVvvYpsRwl6e3A+4A2SWNX6eEiIiIiIiK6IXtsBzhJ2wNDgMcb3L4a+GdJa5e620oaTjVz+2hJavcFag+FegE4GDhC0oc6GHYD4K+l38k1sYyxfavtk4CFwBuAp0v9iIiIiIiIPpEZ24GpfY8tVLOyH7G9TFJ9vbOA0cBcVTcfo0paZwCXS2oF2oB7axvZflbS+4FrJT0L3FXX738AtwJ/AObzSuJ6uqRtSkzXlXZ/BI4v8X7Z9oWr9OQRERERERF1ZGdrYzRfS0uLW1tbmx1GRERERET0b6+azYMsRY6IiIiIiIgBLoltREREREREDGjZYxv9wl+fepH/uvSvzQ6j1504YbNmhxARERERscbLjG1EREREREQMaElsIyIiIiIiYkBLYjuISXq9pAskPSDpHkk/l7RtB3U3kvTJurLNJF3RSf/rSJotKUveIyIiIiKizySxHaTKe20vBW60Pcb2DsAXgE07aLIR8Mm6smOBH3Y0hu0XqN5nO2nVI46IiIiIiGgsie3gtS/wou0z2wtstwF3SrpO0lxJ8yUdVG5/BRgjqU3S6aXsUOAqAElvkXRbuT9P0jalzmXA5EYBSJoqqVVS67OLH++LZ4yIiIiIiEEgS0QHrx2BOxqUPw9MsL1Y0kjgFkmzgOOBHW2PBZD0RuBJ20tLu6OAM2zPkLQOMKSULwB2axSA7WnANIAttn6re+m5IiIiIiJikEliG/UEnCZpb2A5sAWNlydvBjxW8/k3wAmS/gG4xPb9ALaXSXpB0ga2n+7j2CMiIiIiYhDKUuTB625g1wblk4FRwK5ldvbvwHoN6i2pLbd9HnBgKb9a0n41ddelmgmOiIiIiIjodUlsB6/rgXUlfby9QNJuwFbAo7ZflLRv+QzwNLBBTfvfAaNr2r4JeND2t4FZwM6lfBPgMdsv9uGzRERERETEIJalyIOUbUuaAHxL0vFUM6oPA6cA35bUCrQB95b6j0uaI2kB8AvbnyuvCdra9u+pTj7+sKQXgb8Bp5ah9gV+3lU8m220NidO2Kx3HzIiIiIiIgYF2TmzJ1ZOSYx3tX1iJ3UuAf7d9n2d9dXS0uLW1tbeDjEiIiIiItYsalSYGdtYabYvLUuNGyqnI1/WVVIbERERERGxKjJjG/3C6K3H+oSvXdPsMFbaxw95XbNDiIiIiIgYDBrO2ObwqIiIiIiIiBjQmprYSlomqa3mZ3Qv93+jpPsk3VUOPtquB21Hl4OS6stbJH27N+NcWTXf3wJJF0ka1gdjHCXpiN7uNyIiIiIiorc0e4/tkvKu1FeRJKql0stXcYzJtlslTQVOp3rXaqckDenonu1W4P+3d+dRdlVl+se/DyGSQJgnmSMIQpgqUEEJg4CIoiggsRmigAOIPyQCIo2iiNh2oygoIo0REVAEBARRWxJknkmRoUKYbDE0CDLPhiHh+f1xdpFLcWtMVW5V8nzWqlXn7LOHd9+6i8WbffY5A+UpR29+fpIuAA4DTm27KGmI7XkLMoDtsxYsxIiIiIiIiP41oG5FLquk90o6E5gKrCPpq5KmSGqV9O2aup+SdGdZsfxZZ8locSPw7jLGTZKmlp+xpb+dJF0n6TfAzHZxrS9pmqQxpd4fS/mJks4pK8MPSppQ0+abku6TdLWkCyUdU2e+60m6psztGknrlvJzJZ0u6dbS77hufHw3lfm9ZR6Shkg6peYz/ELNfG+Q9FtJD0g6WdL48pnOlLRBzRyPKccTJN1T+rmolC1TPoMp5TPas5RvWvP3aZW0YTfmEBERERER0WONTmyH19yGfHkpew9wvu3R5XhDYBugCdha0o6SNqF6b+p2ZcVyHjC+i7E+RpWwPgF80PZWpY/a24q3AY63PaqtoNy+fBnwGdtT6vS7MfCh0vZbkoZKagb2AUYDnwCaO4jpjDLXLYAL2sWyBrA9sAdwcmcTk7QksDvzE/LaeXwOeN72GGAMcIikd5V6WwJfBjYHPg1sZHsb4GzgiDpDHQeMLvEeVsqOB64t/e8MnCJpmXL9x+Xv0ww8UifuQyW1SGp58fmnO5tiREREREREhwbUrchlj+1Dtm8vRbuVn2nlfARVorsFsDUwpbpjmeFUCWs9F0iaA8ymStaGAmdIakuIN6qpe6ftv9ecrwr8HtjH9qwO+v+T7VeBVyU9AaxOlZD+3vacMq8/dNB2W6rEF+BXwPdrrl1RbsO+R9LqHbQfLml6Ob4J+AUwtt08dgO2qFn1XZ7qM3wNmGL7sRLj34C2xxLPpEpS22ul+jyvAK6o6f/jNSvSw4B1gduA4yWtDfzO9l/bd2Z7IjARqqcidzDHiIiIiIiITjU6sa3n5ZpjAf9l+2e1FSQdAZxn+2vd6G982Rfb1vZE4HGq1colgFc6GBvgeeBhYDugo8T21ZrjeVSfad1HUHdDbXJX229H/b1tj3JJ9Nt/hkfYntSu3k7txnij5vwN6n83PgrsSLVP+ZuSNi3971PnXbX3SrqjtJkk6fO2r+1gHhEREREREb3W6FuRuzIJ+KykEQCS1pK0GnANMK4cI2klSet1s8/lgcfKauingc725r4G7AUcKOmAHsR9M/AxScNK7B/toN6twH7leHxp19cmAV+UNBRA0kblVuEekbQEsI7t64BjgRWoVtAnAUeoZNSSRpff6wMP2j4duJJqlT0iIiIiIqLPDcQV2zfZnlz2095W8qaXgE/ZvkfSN4DJJeF6HTgceKgb3Z4JXCbpk8B1vH2Vtn0ML0vaA7ha0stUq7hdxT1F0pXAjBJTSwftJgDnSPoq8CTwmW7E31NnAyOBqSX5fJIqWe+pIcCvJS1PtUp7mu3nJH0H+BHQWvqfTbUveF/gU5JeB/4JnLSgE4mIiIiIiKhHdrY29gdJI2y/pOrdsjcCh9qe2ui4BqqR727y8d+f3HXFAeqQT6zW6BAiIiIiIhYHdbdpDugV20FuoqRRVA9TOi9JbedWWWHJJIcREREREdErSWz7ie2e7MmNiIiIiIiIXkpiGwPCs8/O5bJLn2p0GD22z7hVGh1CRERERMRib6A/FTkiIiIiIiKiU0lsIyIiIiIiYlBLYht1SVpd0m8kPSjpLkm3Sdq70XFFRERERES0l8Q23qa8j/YK4Ebb69veGtgPWLuxkUVERERERLxdEtuoZxfgNdtntRXYfsj2TyTdJKmprVzSLZK2kHSipPMkTZY0W9InJH1f0kxJV0ka2pCZRERERETEIi+JbdSzKdDRe3fPBg4GkLQRsJTt1nJtA+CjwJ7Ar4HrbG8OzCnlbyHpUEktklpeeOHpvp1BREREREQsNpLYRpck/VTSDElTgEuAPcoK7GeBc2uq/tn268BMYAhwVSmfCYxs36/tibabbTcvt9zK/TmFiIiIiIhYhOU9tlHPLGCfthPbh0taBWix/S9JV1Otyv4b0FzT7tVS/w1Jr9t2KX+DfNciIiIiIqKfZMU26rkWGCbpizVlS9ccnw2cDkyx/cxCjSwiIiIiIqKdJLbxNmWldS/g/ZL+LulO4Dzg38v1u4AXgF82LsqIiIiIiIiK5t8tGtE9ktYErgc2tv1GX/TZ3NzslpaWvugqIiIiIiIWXapXmBXb6BFJBwJ3AMf3VVIbERERERGxIPJAn+gR2+cD5zc6joiIiIiIiDZJbGNAeOGZuUy+8KlGh9Gh3fZfpdEhREREREREB3IrckRERERERAxqSWwHAUkvtTs/WNIZXbT5uKTjutH3TpKelzRN0v2SbpS0x4LGHBERERERsbDkVuRFlO0rgSvbl0ta0vbcdsU32d6jXG8CrpA0x/Y13WjbbQvaPiIiIiIiop4ktoOcpI8B3wDeATwNjLf9uKSDgWbbX5J0LvAMMBqYCnylo/5sT5d0EvAl4Jp2baeX1dyxtp+UtATwAPA+qsdunwWsW7o60vYtkk4E1gRGAk8BB/Td7CMiIiIiIpLYDhbDJU2vOV+J+auxNwPvs21JnweOpX7iuhGwq+153RhvKvDVem0lPQeMB34E7ArMsP2UpN8Ap9m+WdK6wCRgk9J+a2B723NqB5F0KHAowGqrrN2NsCIiIiIiIt4uie3gMMd2U9tJ22psOV0buFjSGlSrtn/voI9LupnUwttfelzb9hzg91SJ7WeBX5byXYFR0ptNl5O0bDm+sn1SC2B7IjARYKP1m9zN2CIiIiIiIt4iD48a/H4CnGF7c+ALwLAO6r3cgz5HA/fWa2v7YeBxSbsA7wX+XC4tAWxru6n8rGX7xV6MHRERERER0SNJbAe/5YF/lOODFrQzSVsA3wR+2km1s4FfA7+tWcmdTLUvt62fpnoNIyIiIiIi+loS28HvROASSTdRPZypN3Zoe90PVUI7of0Tkdu5EhjB/NuQASYAzZJaJd0DHNbLWCIiIiIiInpEdrY2Rs9IaqZ6UNQOfdVnc3OzW1pa+qq7iIiIiIhYNLV/HhCQh0dFD0k6Dvgi1ZORIyIiIiIiGi63IkeP2D7Z9nq2b250LBEREREREZAV2xggXnp6Lree/2RDxh574KoNGTciIiIiIvpGVmwjIiIiIiJiUEtiG70iaWVJ08vPPyX9o+b8Q+3qHinpzEbFGhERERERi7YkttErtp+23WS7CTiL6inJTcB/A/u1q74fcOHCjjEiIiIiIhYPSWyjr10K7CFpKQBJI4E1gTxsKiIiIiIi+kUS2+hTtp8G7gQ+XIr2Ay52nRcmSzpUUoukludefHphhhkREREREYuQJLbRHy5k/u3IHd6GbHui7WbbzSssu/JCCy4iIiIiIhYtSWyjP1wBfEDSVsBw21MbHVBERERERCy6kthGn7P9EnA9cA55aFRERERERPSzJLbRXy4EtgQuanQgERERERGxaFOdZ/pELHTNzc1uaWlpdBgRERERETGwqV5hVmwjIiIiIiJiUEtiGxEREREREYPako0OIAJgzlNzmfHzJxoy9paHrNaQcSMiIiIiom9kxTYiIiIiIiIGtSS2DSBpnqTpku6WdImkpTup2yTpI70YY29JlrRxTdlISXeX450k/bF3M+hxLOdKGrcwxoqIiIiIiMVPEtvGmGO7yfZmwGvAYZ3UbQJ6nNgC+wM3A/v1om1ERERERMSgkcS28W4C3i1pGUnnSJoiaZqkPSW9AzgJ2Les8O4r6f3leHqpt2z7DiWNALYDPkc3EltJK0m6QlKrpNslbVHKZ0paQZWnJR1Yyn8laVdJQySdUmJulfSFcl2SzpB0j6Q/AdnEGhERERER/SaJbQNJWhLYHZgJHA9ca3sMsDNwCjAUOAG4uKzwXgwcAxxuuwnYAZhTp+u9gKtsPwA8I2mrLkL5NjDN9hbA14HzS/ktVAnypsCDZTyA9wG3UyXOz5eYxwCHSHoXsDfwHmBz4BBgbAfzP1RSi6SWZ198uosQIyIiIiIi6kti2xjDJU0HWoD/A34B7AYcV8qvB4YB69ZpewtwqqQJwAq259apsz9wUTm+qJx3ZnvgVwC2rwVWlrQ81WryjuXnv4HNJa0FPGP7pRLzgSXmO4CVgQ1L/Qttz7P9KHBtvUFtT7TdbLt5xWVX7iLEiIiIiIiI+vK6n8aYU1Zc3yRJwD62729X/t7ac9snl9t7PwLcLmlX2/fV1F8Z2AXYTJKBIYAlHdtJPKpTZuBG4HCqBPt4qpXYcVQJb1u7I2xPahfzR0r7iIiIiIiIfpcV24FjEnBESXCRNLqUvwi8uY9W0ga2Z9r+HtWK78bt+hkHnG97Pdsjba8D/J1qVbYjNwLjS/87AU/ZfsH2w8AqwIa2H6R6GNUxzE9sJwFflDS0tN1I0jKlv/3KHtw1qG6tjoiIiIiI6BdJbAeO71DtqW0tr+T5Tim/DhjV9vAo4MjymqAZVPtr/9yun/2By9uVXQYc0MnYJwLNklqBk4GDaq7dATxQjm8C1qJKcAHOBu4BppaYf0Z1F8DlwF+p9g7/N3BD51OPiIiIiIjoPdm5YzQab9ORTf7N8ZMbMvaWh+ShzRERERERg0S9bZTZYxsDw/BVlkyCGRERERERvZJbkSMiIiIiImJQy4ptDAivPvE6D57+z4U+7voT3rnQx4yIiIiIiL6VFduIiIiIiIgY1JLYRkRERERExKDWsMRW0rzyCpsZkqZKGtvAWO6S9GVJP6op+5mkv9ScHyHpdEnNkk7vYf8HSzqjL2Ou6ft6Sc1d1NlL0qj+GD8iIiIiIqLRGrliO8d2k+0tga8B/7UwB5e0ZPk9EvgHcCtQm1w3ActLGlLOxwK32G6xPaGj/gaovYAeJbYDfD4RERERERFvGii3Ii8HPAsgaSdJf2y7IOmMsuLZXFZ4p0uaKcmS1qwpm15WgdeTtKqkyyRNKT/blb5OlDRR0mTg/DLE7sBVwDRgI0nDJS0P/AuYDmxe6o0Fbq2Nr31/HY1bq5PY3l8zj2mSlpW0hqQbS9ndknbo7EOU9JKk75ZV8NslrV5Wwj8OnFL62aD8XFVWqm+StHFpf66kUyVdB3xP0rsl/aVmVX0DVU4p8cyUtG/N3+0GSb+V9ICkkyWNl3RnqbdBj78VERERERER3dDIVbnhkqYDw4A1gF06q2y7hWoVFUmnAFfZfrSm7HDg/bYfkvQb4DTbN0taF5gEbFK62hrY3vaccv5h4Cjbc0s8Y4DhwB3AX4Gxkp4AZPvhOgnam/11MW6bH3dQ5xjgcNu3SBoBvAIcCkyy/d2ycrx0F5/pMsDtto+X9H3gENv/IelK4I+2Ly2f1TXAYbb/Kum9wJnM//w3Ana1PU/SHcDJti+XNIzqH0I+UT7zLYFVgCmSbixttyxzeQZ4EDjb9jaSvgwcARxZG6ykQ8scWXPFtbqYWkRERERERH2NTGzn2G5LSrelWvHcrKtGkv4N2ArYraZsO+DzQNuK5q7AKEltVZaTtGw5vrItqZX0DmBt2w+Wa7dQrcwOB26jSmy/DjxJdatyPVfWJMmdjUsXdW4BTpV0AfA7249ImgKcI2kocIXt6Z1/OrwGtK123wV8sH2FkjSPBS6piWGpmiqXlKR2WWAt25cD2H6ltN8euND2POBxSTdQ/WPAC8AU24+Ven8DJpc+ZwI7t4/F9kRgIsDm627pLuYWERERERFR14DYR2n7NkmrAKsCc3nrLdLD2g4kbQp8G9ixJFZIWgP4BfBx2y+VqksA29YknG3tAV6uKdoBuLnm/FbgC2XMn1IltKPK71s6CL+2v87G7bQOcLKkPwEfAW6XtKvtGyXtCHwU+JWkU2yfT8det92WIM6j/t93CeC5tn9U6GQ+6uB6R+UAr9Ycv1Fz/kYHsURERERERCywAbHHtuzxHAI8DTxEtaK5VNnr+oFSZ3ngIuBA20+WsqHAb4F/t/1ATZeTgS/V9N9REvdh4M8157cC7wNWtf1ESRKfBPak4xXbWt0Zt24dSRvYnmn7e0ALsLGk9YAnbP+cKnnfqhsx1PMisCyA7ReAv0v6ZBlXkrZs36DUe0TSXqXeUpKWBm4E9pU0RNKqwI7Anb2MKyIiIiIiYoE1MrEd3vawJOBi4CDb82w/TJWstgIXUD3UCaon+64H/Lym3Viq22C/XfPgpTWBCUCzpFZJ9wCHdRDDTsANbSe2n6VKZGfV1LkNWA2Y0Y05dWfcjuocWR7INAOYQ5Vw7wRMlzQN2Idqf25vXAR8VdVDqTYAxgOfK2PNokrc6/k0MEFSK1Vi/07gcqq/zQzgWuBY2//sZVwRERERERELTPPvXF28SFob+Lnt3RsdS0Bzc7NbWloaHUZERERERAxsdbdGLrb7Hm0/QvWqn4iIiIiIiBjEBsQe24iIiIiIiIjeWmxXbGNgef2fr/HY9x/u93HWOHadfh8jIiIiIiIWrqzYRkRERERExKA2qBJbSadJOrLmfJKks2vOfyjpaEk7SfpjH415oqRjOrne47EknSRp1x7UnyHpwp6M0ZckrSnp0nJ8sKQzOqj3Ur3yiIiIiIiI/jSoEluqV86MBZC0BLAKsGnN9bHALQ2Iq0dsn2D7L+3LJQ2pU7YJ1d9pR0nLLIz42rP9qO1xjRg7IiIiIiKiK4Mtsb2FkthSJbR3Ay9KWlHSUsAmzH/v7QhJl0q6T9IFkgQgaWtJN0i6q6z4rlHKN5B0VSm/SdLG7QeX9G5JfykrqFPLO2E7G+sESVPK+2kn1pSfK2lcOZ5d6t0MfLLOnA8AfgVMBj5eE8sYSbeWWO6UtKykIZJ+IGlmeU/uEV3MeYKke0rdi0rZ+2veCTyt9DtS0t01Ma1TPqv7JX2r3h9K0lfL3FslfbvjP2lERERERMSCGVQPj7L9qKS5ktalSnBvAzEkr6QAAB2HSURBVNYCtgWeB1ptv1byx9FUye+jVAnxdpLuAH4C7Gn7SUn7At8FPgtMBA6z/VdJ7wXOBHZpF8IFwMm2L5c0jOofBtapNxZwM3CG7ZMAJP0K2AP4Q52pvWJ7+w6mvS/wQeA9wJeACyW9A7gY2Nf2FEnLAXOAQ4F3AaNtz5W0kqShncz5OOBdtl+VtEIZ7xjgcNu3SBoBvFInpm2AzYB/AVMk/cn2my+hlbQbsGGpJ+BKSTvavrG2E0mHlphZa4W1Oph+RERERERE5wZVYlu0rdqOBU6lSmzHUiW2t9bUu7O8qxZJ04GRwHNUCdnVJfkdAjxWErixwCWlHGCp2kElLQusZftyANuvlPKOxroZ2FnSscDSwErALOonthfXm6ikMcCTth+S9AhwjqQVgbWBx2xPKbG8UOrvCpxle24pf0bSZvXmXIZoBS6QdAVwRc3ne6qkC4Df2X6k5jNpc7Xtp8uYvwO2B1pqru9Wft5cPadKdN+S2NqeSPUPCmy59hau9xlERERERER0ZTAmtm37bDenuhX5YeArwAvAOTX1Xq05nkc1VwGzbG9b22FZ8XzOdlMn474tu+tsrLKieybQbPthSScCwzpo/3IH5fsDG0uaXc6XA/YB7gTqJYKqU153zsVHgR2pbnH+pqRNbZ8s6U/AR4DbS7LcftW2/Rj1xvwv2z/rYF4RERERERF9ZrDtsYVqRXEP4Bnb82w/A6xAdTvybV20vR9YVdK2AJKGlmTuBeDvkj5ZyiVpy9qGpc4jkvYqdZaStHQnY7UlsU+VFeEePXxJ1cOxPglsYXuk7ZHAnlTJ7n3AmmVFl7IPdkmqfbiHlWMkrdTRnEv/69i+DjiW6jMcIWkD2zNtf49qFfZte42BD5bbnIcDe/H2B3ZNAj5b5o2ktSSt1pP5R0REREREdNdgTGxnUj0N+fZ2Zc/bfqqzhrZfo0owvydpBjCd+Q+jGg98rpTPokoi2/s0MEFSK9XK8Ts7Ges54OcltiuAKV1P7S12BP5h+x81ZTcCo4CVqfbe/qTEezVVIn028H9Aayk/oJM5DwF+LWkm1S3Dp5WYjywPu5pBtW/3z3Viu5nqgVbTgctq99eWuU8GfgPcVvq/FFi2h/OPiIiIiIjoFtnZ2hiN19zc7JaWlq4rRkRERETE4qzuFtHBuGIbERERERER8aYkthERERERETGoDcanIsci6PXHX+Gfp97bp32+8+hN+rS/iIiIiIgYmLJiGxEREREREYNaEttFkKSXulHnyC5eV9RXsTRJ+kh/jxMREREREYuvJLaLryOBHiW2kob0YpwmIIltRERERET0myS2izBJO0m6XtKlku6TdIEqE4A1geskXVfq7ibpNklTJV0iaUQpny3pBEk3A58s598u9WZK2rjUW0bSOZKmSJomaU9J7wBOAvaVNF3Svg36KCIiIiIiYhGWxHbRN5pqdXYUsD6wne3TgUeBnW3vLGkV4BvArra3AlqAo2v6eMX29rYvKudPlXr/DRxTyo4HrrU9BtgZOAUYCpwAXGy7yfbFtYFJOlRSi6SWp19+ph+mHhERERERi4Mktou+O20/YvsNYDowsk6d91ElvrdImg4cBKxXc/3idvV/V37fVdPfbsBxpf31wDBg3c4Csz3RdrPt5pWXWanbE4qIiIiIiKiV1/0s+l6tOZ5H/b+5gKtt799BHy930GdtfwL2sX3/WzqW3tuzcCMiIiIiInomK7aLrxeBZcvx7cB2kt4NIGlpSRv1sL9JwBGSVPoYXWeciIiIiIiIPpfEdvE1EfizpOtsPwkcDFwoqZUq0d24h/19h2pPbauku8s5wHXAqDw8KiIiIiIi+otsNzqGCLZcZzNPOuqSPu3znUdv0qf9RUREREREw6leYfbYxoAwdPVhSUQjIiIiIqJXcityREREREREDGpZsY0B4fXH/8XjP2rpdfvVj2zuw2giIiIiImIwyYptREREREREDGpJbHtB0vGSZklqLU/7XeB3tUraSdIfe9n2REn/KLH8VdLvJI3qRruDJa3ZyzFHSjqgN20jIiIiIiL6UhLbHpK0LbAHsJXtLYBdgYcbGxUAp9lusr0hcDFwraRVu2hzMNCrxBYYCfQosZWUW98jIiIiIqLPJbHtuTWAp2y/CmD7KduPAkiaLek/Jd0mqUXSVpImSfqbpMNKHUk6RdLdkmbWe7erpDGSpklaX9LWkm6QdFfpa42uArR9MTCZknjW60PSOKAZuKCs9A7vaCxJ75b0F0kzJE2VtAFwMrBDaXuUpGGSflnmNE3SzqXtwZIukfSHElNERERERESfSmLbc5OBdSQ9IOlMSe9vd/1h29sCNwHnAuOA9wEnleufAJqALalWe0+pTVYljQXOAvakWgn+CTDO9tbAOcB3uxnnVGBjSUPr9WH7UqAFGG+7CZjbyVgXAD+1vSUwFngMOA64qawSnwYcDmB7c2B/4DxJw0r7bYGDbO9SG6CkQ8s/ALQ88/Kz3ZxWRERERETEW+XW0B6y/ZKkrYEdgJ2BiyUdZ/vcUuXK8nsmMML2i8CLkl6RtAKwPXCh7XnA45JuAMYALwCbABOB3Ww/KmkzYDPgakkAQ6iSyu5oe3Hxe7rZR916kpYF1rJ9eZn/KwClTq3tqRJjbN8n6SFgo3LtatvPtG9ge2KZL1uuM8rdnFdERERERMRbJLHthZKUXg9cL2kmcBDV6izAq+X3GzXHbedLMj/hrOcxYBgwGni01J1VVoB7ajTVimx3+6hbT9Jy3Ryvs3m93M0+IiIiIiIieiy3IveQpPdI2rCmqAl4qAdd3AjsK2lIebjTjsCd5dpzwEeB/5S0E3A/sGp5YBWShkratBsx7gPsBlzYRR8vAsuW47r1bL8APCJpr1K+lKSl27Vtm9f4UmcjYN3SZ0RERERERL9KYttzI6j2j94jqRUYBZzYg/aXA63ADOBa4Fjb/2y7aPtx4GPAT6lWXccB35M0A5hOtce1nqPaXvcDfArYxfaTtl/rpI9zgbMkTae69bijep8GJpT53gq8s8xhbnmg1FHAmcCQsoJ9MXBw2wO2IiIiIiIi+pPsbG2MxttynVGe/JXze91+9SOb+zCaiIiIiIgYoOpugcwe2xgQhq6+dJLTiIiIiIjoldyKHBEREREREYNaVmxjQHj9iZd4/PSbetRm9Qk79FM0ERERERExmGTFNiIiIiIiIga1JLYRERERERExqPVrYivpnZIukvS38nqc/ynvOO1JHy/1Q1wjJVnSd2rKVpH0uqQz+nq8DmI4TNKBHcR2dw/7mlde9TOrvH7naEmd/m3LOAf0NO6a9gdLWrO37SMiIiIiIvpKvyW2kkT1ztbrbW9gexTwdWD17rbvKjlbQA8Ce9ScfxKY1Y/jvYXts2z3/v02bzXHdpPtTYEPAh8BvtVFm5FArxNb4GCgR4mtpCELMF5ERERERERd/Zk47gy8bvustgLb023fJGmEpGskTZU0U9Ke8OYq4r2SzgSmAuuU8h+WutdIWrWUNUm6XVKrpMslrVjKr5f0PUl3SnpAUkdPGJoD3Cup7R0z+wK/bbsoab0yXmv5vW4pP1fS6ZJulfSgpHGlXJJOkXR3mdO+pfx0SSeU4w9JulHSEpJOlHRMKd+6rLTeBhxeE8OQ0ueUEscXuvrQbT8BHAp8qcTUUR8nAzuUld6jOhtL0rFlTjMknVzm3AxcUNoPl/QBSdNKvXMkLVXazpZ0gqSbqf7xICIiIiIiok/1Z2K7GXBXB9deAfa2vRVVAvzDssIL8B7gfNujbT8ELANMLXVvYP5K5PnAv9veApjJW1col7S9DXAkna9cXgTsJ2ltYB7waM21M0ocWwAXAKfXXFsD2J5qxffkUvYJoAnYEtgVOEXSGsBxwL6Sdi59fMb2G+3i+CUwwfa27co/BzxvewwwBjhE0rs6mQ8Ath+k+tuu1kkfxwE3lZXe0zqqJ2l3YC/gvba3BL5v+1KgBRhvuwkwcC6wr+3NqZ62/cWakF6xvb3ti2rjlHSopBZJLc+89FxX04qIiIiIiKirUQ+PEvCfklqBvwBrMf8W5Yds315T9w3g4nL8a2B7ScsDK9i+oZSfB+xY0+Z35fddVLfcduQqqlt3968Zo822wG/K8a+oEtk2V9h+w/Y9NXFvD1xoe57tx6mS8DG2/wUcAlwNnGH7b2/5IN4+l1/VXN4NOFDSdOAOYGVgw07m85aue9hHR/V2BX5Z5oHtZ+q0fQ/wd9sPlPP2f4/2ny2lr4m2m203rzRihW5OKyIiIiIi4q368z22s4BxHVwbD6wKbG37dUmzgWHl2std9OtujP1q+T2PTuZo+zVJdwFfATYFPtbNcV+tOVa73/VsDjxN/T2pouM5CTjC9qRO+n57I2l9qrk/0VEfknbqzliSPtxJfLVtO9PV3zQiIiIiIqLX+nPF9lpgKUmHtBVIGiPp/cDywBMlqd0ZWK+LGNsS5AOAm20/Dzxbs3/201QrpL3xQ6pbmp9uV34rsF85Hg/c3EU/N1Ldcjyk7APeEbhT0npUifNoYHdJ761tZPs54HlJbSvC42suTwK+KGkogKSNJC3TWRBl7LOoVofdSR8vAst2Y6zJwGclLV3KVyr1a9vfB4yU9O5yviB/j4iIiIiIiB7ptxVb25a0N/AjScdR7audTbXvdRbwB0ktwHSqxKgjLwOblpXV56ke8gRwEHBWSbgeBD7TyzhnUf9pyBOAcyR9FXiyG/1fTnX78gyqFc5jgcepbkE+xvajkj4HnCtpTLu2nylj/YsqwWxzNtWt1FPLHuQnqfa7tje83EI8FJhLdTvzqV300QrMlTSDan/sj+vVs32VpCagRdJrwP9QPd36XKrPf06Z92eASyQtCUyhSq4jIiIiIiL6napFvYjGam5udktLS6PDiIiIiIiIga3uNshGPTwqIiIiIiIiok8ksY2IiIiIiIhBrT+fihzRbXOfeIEnzqj/8OfVvvShhRxNREREREQMJlmxjYiIiIiIiEEtie0AIel4SbMktUqa3v61QHXqb1zqTZO0QSf1vt6LWN4p6SJJf5N0j6T/kbRRT/up6e9EScf0tn1ERERERERnktgOAJK2BfYAtrK9BbAr8HAXzfYCfm97tO2/dVKvR4ltedXP5cD1tjewPar0sXp320vK9yoiIiIiIhaa7LEdGNYAnrL9KoDtp9ouSDoB+BgwHLgV+AKwO9X7gOdJ2tH2zpI+RfXu3XcAdwD/D/gu899xO4vqfb9P2f5x6fu7wOO2T6+JZWfgddtvvofW9vRSfwTwe2BFqnfmfsP27yWNBP4MXEf1Ttu9SjwHUiXoTwJ39c1HFRERERER8VZZWRsYJgPrSHpA0pmS3l9z7QzbY2xvRpXc7mH7f4CzgNNKUrsJsC+wne0mYB4w3vZxwBzbTbbHA78ADgIoq6r7ARe0i2UzOk5CXwH2tr0VVQL8w7LCC/Ae4Hzbo4FVSt+jgU8AY+p1JulQSS2SWp5+6fnufVIRERERERHtJLEdAGy/BGwNHEq1unmxpIPL5Z0l3SFpJrALsGmdLj5Q2k8pq7MfANavM85s4GlJo4HdgGm2n+5BqAL+U1Ir8BdgLebfovyQ7dvL8Q7A5bb/ZfsF4MoO5j3RdrPt5pVHLN+DMCIiIiIiIubLrcgDhO15wPXA9SWJPUjSRcCZQLPthyWdCAyr01zAeba/1o2hzgYOBt4JnFPn+ixgXAdtxwOrAlvbfl3S7Jp4Xm4/pW7EEhERERERscCyYjsASHqPpA1ripqAh5ifND5V9rd2lHBeA4yTtFrpbyVJ65Vrr0saWlP3cuDDVLcH13tx7LXAUpIOqYlvTLk9enngiZLU7gysV6c9wI3A3pKGS1qWao9wREREREREv8iK7cAwAviJpBWAucD/Aofafk7Sz4GZwGxgSr3Gtu+R9A1gctk7+zpwOFVyPBFolTTV9njbr0m6DniurBK378uS9gZ+JOk4qn21s6keVjUL+IOkFmA6cF8H8UyVdHGp8xBwU68+lYiIiIiIiG6QnTtGFycl8Z0KfNL2XxsdT5vm5ma3tLQ0OoyIiIiIiBjYVK8wtyIvRiSNoloNvmYgJbURERERERELIrciL0Zs30OdpyVHREREREQMZlmxjYiIiIiIiEEtiW1EREREREQMakls+4Ck0yQdWXM+SdLZNec/lHR0D/s8UdIxfRzntuUpy7VlIyXNkTRN0r2S7pR0UF+OGxERERER0Z+S2PaNW4Gx8OZTh1cBNq25Pha4ZWEGJGlIneIPA1fVKf+b7dG2NwH2A46S9Jk6fS7QnuwFbR8REREREVFPEtu+cQslsaVKaO8GXpS0oqSlgE2AaZJOkDRF0t2SJkoSgKQJku6R1Crpopp+R0m6XtKDkia0FUr6VFlZnS7pZ21JrKSXJJ0k6Q5g2zpxfgD4S2cTsf0gcDQwofR5Yol1MnC+pJskNdXEcoukLSQtI+mcMr9pkvYs1w+WdImkPwCTu/+RRkREREREdE8S2z5g+1FgrqR1qRLc24C25LIZaLX9GnCG7TG2NwOGA3uULo4DRtveAjispuuNgQ8B2wDfkjRU0ibAvsB2tpuAecD4Un8Z4G7b77V9c22MklYBXrf9fDemNLWM3WZrYE/bBwBnAweXPjcClrLdChwPXGt7DLAzcIqkZUr7bYGDbO/SLqZDJbVIannyySe7EVZERERERMTbJbHtO22rtm2J7W0157eWOjtLukPSTGAX5t+u3ApcIOlTwNyaPv9k+1XbTwFPAKtTrbpuDUyRNL2ct73CZx5wWQfx7Ub3V0zbv/T4SttzyvElwB6ShgKfBc6t6f+4EtP1wDBg3XLtatvPtB/E9kTbzbabV1111W6GFhERERER8VbZ89h32vbZbk51K/LDwFeAF4BzJA0DzgSabT8s6USq5A/go8COwMeBb0pqS3hfrel/HtXfS8B5tr9WJ4ZXbM/rIL7dgVO7OZfRwL015y+3Hdj+l6SrgT2Bf6NakabEtY/t+2s7kvTe2vYRERERERF9LSu2fecWqluLn7E9r6xQrkB1G+5tzE9in5I0AhgHbz5sah3b1wHHljYjOhnnGmCcpNVK+5UkrddZYGUv7xbA9K4mIWkk8APgJ51UOxs4HZhSsxI7CTiiZt/w6K7GioiIiIiI6AtZse07M6mehvybdmUjyq3ElFftzARmA1NKnSHAryUtT7XqeZrt50p++Da275H0DWBySYpfBw4HHuoktq2BabbdwfUNJE2jSr5fBH5i+5cddWb7LkkvALV1vgP8CGgtye1s5u8hjoiIiIiI6DfqONeJRUVJhP/X9kVdVu5ef2tS7aPd2PYbfdFnc3OzW1pa+qKriIiIiIhYdNVdAcyK7WLA9n/0VV+SDgS+CxzdV0ltRERERETEgsiKbQwIkl4E7u+yYkT/WwV4qtFBxGIv38MYKPJdjIEg38Oo9ZTtD7cvzIptDBT3227uulpE/5LUku9iNFq+hzFQ5LsYA0G+h9EdeSpyREREREREDGpJbCMiIiIiImJQS2IbA8XERgcQUeS7GANBvocxUOS7GANBvofRpTw8KiIiIiIiIga1rNhGRERERETEoJbENiIiIiIiIga1JLbRcJI+LOl+Sf8r6bhGxxOLD0nnSHpC0t01ZStJulrSX8vvFRsZYyz6JK0j6TpJ90qaJenLpTzfxVhoJA2TdKekGeV7+O1Snu9hLHSShkiaJumP5Tzfw+hSEttoKElDgJ8CuwOjgP0ljWpsVLEYORdo/4Lv44BrbG8IXFPOI/rTXOArtjcB3gccXv47mO9iLEyvArvY3hJoAj4s6X3kexiN8WXg3przfA+jS0lso9G2Af7X9oO2XwMuAvZscEyxmLB9I/BMu+I9gfPK8XnAXgs1qFjs2H7M9tRy/CLV/8ytRb6LsRC58lI5HVp+TL6HsZBJWhv4KHB2TXG+h9GlJLbRaGsBD9ecP1LKIhpldduPQZVwAKs1OJ5YjEgaCYwG7iDfxVjIyu2f04EngKtt53sYjfAj4FjgjZqyfA+jS0lso9FUpyzvoIqIxY6kEcBlwJG2X2h0PLH4sT3PdhOwNrCNpM0aHVMsXiTtATxh+65GxxKDTxLbaLRHgHVqztcGHm1QLBEAj0taA6D8fqLB8cRiQNJQqqT2Atu/K8X5LkZD2H4OuJ7qGQT5HsbCtB3wcUmzqban7SLp1+R7GN2QxDYabQqwoaR3SXoHsB9wZYNjisXblcBB5fgg4PcNjCUWA5IE/AK41/apNZfyXYyFRtKqklYox8OBXYH7yPcwFiLbX7O9tu2RVP9PeK3tT5HvYXSD7Nz1GY0l6SNU+ymGAOfY/m6DQ4rFhKQLgZ2AVYDHgW8BVwC/BdYF/g/4pO32D5iK6DOStgduAmYyf0/Z16n22ea7GAuFpC2oHsozhGrh47e2T5K0MvkeRgNI2gk4xvYe+R5GdySxjYiIiIiIiEEttyJHRERERETEoJbENiIiIiIiIga1JLYRERERERExqCWxjYiIiIiIiEEtiW1EREREREQMaklsIyIiIiIiYlBLYhsREbGIkLS3JEvauJzvJOmPfdDvuZLGdVFnJ0ljF2CM3SW1SLpX0n2SftDLfpaS9BdJ0yXtK2kHSbPK+VqSLu2i/dmSRvVuFh32+fW+7C8iIt4uiW1ERMSiY3/gZmC/Boy9E9CrxFbSZsAZwKdsbwJsBjzYyzhGA0NtN9m+GBgP/KCc/8N2pwm67c/bvqeXY3ckiW1ERD9LYhsREbEIkDQC2A74HG9NbJeTdLmkeySdJWkJSUPKKuzdkmZKOqr00STpdkmtpc2KdcaZLWmVctws6XpJI4HDgKPKyugOklaVdJmkKeVnu07CPxb4ru37AGzPtX1mGWM9SdeUmK6RtG4pf1v/klYDfg00lTi+APwbcIKkCySNlHR3aT9E0g/K/FslHVHKr5fUXI53k3SbpKmSLimfcdtn8O1SPrNmhXyEpF/W9LmPpJOB4SWeC3r8h42IiG5ZstEBRERERJ/YC7jK9gOSnpG0VSnfBhgFPARcBXwC+Duwlu3NACStUOqeDxxh+wZJJwHfAo7samDbsyWdBbxk+welz98Ap9m+uSSjk4BNOuhiM+CHHVw7Azjf9nmSPgucXub64/b9295E0ueBY2zvUeLYFvij7UtLAt7mUOBdwGjbcyWtVDtoSd6/Aexq+2VJ/w4cDZxUqjxleytJ/w84Bvg88E3gedublz5WtH2ZpC/Zburqc4yIiN5LYhsREbFo2B/4UTm+qJz/CbjT9oMAki4EtgeuAdaX9JNSZ7Kk5YEVbN9Q+jgPuGQB4tkVGCWp7Xw5ScvafrGH/WxLlYwD/Ar4fmf99zC+s2zPBbD9TLvr76P6B4FbyhjvAG6ruf678vuumvh2pWa13PazPYgnIiIWQBLbiIiIQU7SysAuwGaSDAwBDPxP+V3Ltp+VtCXwIeBwqtt1j+rmcHOZv5VpWCf1lgC2tT2nG33OArYGZnSjbtt86vZfk+h2Rbz9s2l//Wrb+3dw/dXyex7z/3+qqz4jIqKfZI9tRETE4DeO6nbd9WyPtL0O1e3G2wPbSHqXpCWAfYGby222S9i+jOr22a1sPw88K2mH0uengRvePhSzqZJQgH1qyl8EaldMJwNfajuR1NmtuKcAX5e0Uam7hKSjy7Vbmb8KOp7q4Vg97b+eycBhkpYs7Vdqd/12YDtJ7y7Xl26Lr4s+a2Nq26P8uqShPYwvIiJ6IIltRETE4Lc/cHm7ssuAA6hunz0ZuJsq2b0cWAu4XtJ04Fzga6XNQcApklqBJubvJ631beDHkm6iWq1s8wdg77aHRwETgObyEKV7qB4uVZftVqq9vBdKurfEuka5PAH4TInp08CXa8q71X8Hzgb+D2iVNIPqs6qN6Ung4BJTK1Wiu3EXff4HsGJ5KNcMYOdSPrGMk4dHRUT0E9m5YyYiIiIiIiIGr6zYRkRERERExKCWh0dFRETEQiHpM8y/lbjNLbYPb0Q8ERGx6MityBERERERETGo5VbkiIiIiIiIGNSS2EZERERERMSglsQ2IiIiIiIiBrUkthERERERETGo/X/fk2LQcGJXUAAAAABJRU5ErkJggg==\n"},"metadata":{"needs_background":"light"}}]},{"metadata":{},"cell_type":"markdown","source":"Doorman and Elevator had a hgih influence on price"},{"metadata":{"trusted":true},"cell_type":"code","source":"# which bed type had a high influence on the price\n\nf, ax = plt.subplots(figsize=(10, 6))\nbed_type = coef_df[coef_df.est_int.str.startswith('bed_type')]\nbed_type['est_int']= bed_type['est_int'].str.replace('bed_type_','')\n\nsns.barplot(data=bed_type, x=\"est_int\", y=\"abs_coefs\");\nplt.title('What Bed Type Had a high Influence on the Price of a Listing?')\nplt.xlabel('Bed Type')\nplt.ylabel('Absolute_Coefficienct')\n# Hide the right and top spines\nax.spines['right'].set_visible(False)\nax.spines['top'].set_visible(False)\n\nshow_values_on_bars(ax)","execution_count":482,"outputs":[{"output_type":"stream","text":"/opt/conda/lib/python3.7/site-packages/ipykernel_launcher.py:5: SettingWithCopyWarning: \nA value is trying to be set on a copy of a slice from a DataFrame.\nTry using .loc[row_indexer,col_indexer] = value instead\n\nSee the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n  \"\"\"\n","name":"stderr"},{"output_type":"display_data","data":{"text/plain":"<Figure size 720x432 with 1 Axes>","image/png":"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\n"},"metadata":{"needs_background":"light"}}]},{"metadata":{},"cell_type":"markdown","source":"Futon looks to be the highest influencer on price and couch just bottomed down"},{"metadata":{},"cell_type":"markdown","source":"# Summary"},{"metadata":{},"cell_type":"markdown","source":"\nThis notebook uses data from the Seattle area of Airbnb and has been analyzed to answer the following questions.\n\n\n* What type of property type are most people interested in?\n  \n  From the histogram of showing property type and number of reviews, House and Apartment are what most people are intereste in.\n  \n* What are the top 10 characteristics of listing that influence the price of listings?\n    \n  From the statistical inference of the model,property types with Boat,Dorm,Loft, and Treehouse greatly influenced the price of listings. Again, Shared room type had a high price tag than Prive room. Then, Doorman and Washer amenities really spiked the prices of listings. We also saw that higher number of bedrroms increase prices of listings\n\n\n\n* When is the best time to host a listing for booking?\n\n  There is a busy season and from the timeline there was definitely an increase every year of the number of   people who travel. We found out that most of these travelers like to travel in september.\n  So the best time to host a listing for booking is september\n\n\n\n"}],"metadata":{"kernelspec":{"name":"python3","display_name":"Python 3","language":"python"},"language_info":{"name":"python","version":"3.7.6","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"}},"nbformat":4,"nbformat_minor":4}