Sheet2
Category Feature Name Description
Night dim_is_requested True if ds_night receives a booking request eventually; false otherwise.
ds_night The night on the calendar
ds The date stamp on which data is collected
id_listing_anon Anonymized listing ID
id_user_anon Anonymized user ID of the host of the listing
m_effective_daily_price Effective daily price on listing calendar in USD
m_pricing_cleaning_fee Cleaning fee in USD.
Listing dim_market Market of the listing.
dim_lat Latitude of the listing.
dim_lng Longitude of the listing.
dim_room_type The type of room (Shared room, Private room or Entire home/apt).
dim_person_capacity Number of people the listings can accomadate
dim_is_instant_bookable 1 if the listing is instant bookable, 0 otherwise.
m_checkouts Total number of checkouts
m_reviews Total number of reviews
days_since_last_booking Number of days since last booking
cancel_policy Cancellation policy for the listing, coded in integers from 3 to 9
image_quality_score A score for the image quality
m_total_overall_rating Number of overall ratings left by guests
m_professional_pictures Number of professional pictures taken
dim_has_wireless_internet 1 if the listing has wifi, 0 otherwise.
Occupancy/availability ds_night_day_of_week 0 is Sunday
ds_night_day_of_year 1 is January 1
ds_checkin_gap Number of days available prior to ds_night, can be 0, 1, … to 6
ds_checkout_gap Number of days available post to ds_night, can be 0, 1, … to 6
occ_occupancy_plus_minus_7_ds_night Occupancy rate* around the ds_night for +/-7 days. *: Occupancy = Booked/(Booked + Available)
occ_occupancy_plus_minus_14_ds_night Occupancy rate around the ds_night for +/-14 days.
occ_occupancy_trailing_90_ds Occupancy rate in the past 90 days prior to ds (included)
m_minimum_nights Minimum nights required for requesting to book that ds_night
m_maximum_nights Maximum nights to request book that ds_night
Listing demand price_booked_most_recent Daily price in USD in the most recent booking
p2_p3_click_through_score Historical frequency of clicking on a particular listing from search results.
p3_inquiry_score Represents historical frequency of someone contacting the listing from the listing page.
listing_m_listing_views_2_6_ds_night_decay Average listing views in the past 2 days to 6 before ds with decay weights for the ds_night
Market demand general_market_m_unique_searchers_0_6_ds_night Average number of unique searchers in the past 6 days before ds for ds_night
general_market_m_contacts_0_6_ds_night Average number of unique contacts in the past 6 days before ds for ds_night
general_market_m_reservation_requests_0_6_ds_night Average number of unique requests in the past 6 days before ds for ds_night
general_market_m_is_booked_0_6_ds_night Avg number of booked listings in this market for the ds_night 0-6 days before ds
m_available_listings_ds_night Number of available listings in this market for the ds_night
KDT^room_type kdt_score A score specific for each kdt node
r_kdt_listing_views_0_6_avg_n100 Average of listing views within the kdt node (100 listings) and same room_type listings
r_kdt_n_active_n100 Number of active listings for the same room_type listings within the kdt node
r_kdt_n_available_n100 Number of available listings for the same room_type listings within the kdt node
r_kdt_m_effective_daily_price_n100_p50 The median of effective daily price for the same room_type listings within the kdt node
r_kdt_m_effective_daily_price_available_n100_p50 The median of effective daily price for the same room_type listings that are available within the kdt node
r_kdt_m_effective_daily_price_booked_n100_p50 The median of effective daily price for the same room_type listings that are booked within the kdt node