#Airbnb Listings & Reviews - Kaggle.
##cleaning the dataset
library(tidyverse) #I start by installing the tidyverse package#we read the dataset and assign it to a variable
df <- read_csv('Data Science with R/Assignments/Assignment 1/data/Listings/Listings.csv')Rows: 279712 Columns: 33── Column specification ───────────────────────────────────────────────────────────────────────────────────────────────
Delimiter: ","
chr (9): name, host_location, host_response_time, neighbourhood, district, city, property_type, room_type, amenities
dbl (19): listing_id, host_id, host_response_rate, host_acceptance_rate, host_total_listings_count, latitude, long...
lgl (4): host_is_superhost, host_has_profile_pic, host_identity_verified, instant_bookable
date (1): host_since
ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.# we explore the dataframe
str(df)spc_tbl_ [279,712 × 33] (S3: spec_tbl_df/tbl_df/tbl/data.frame)
$ listing_id : num [1:279712] 281420 3705183 4082273 4797344 4823489 ...
$ name : chr [1:279712] "Beautiful Flat in le Village Montmartre, Paris" "39 m² Paris (Sacre Cœur)" "Lovely apartment with Terrace, 60m2" "Cosy studio (close to Eiffel tower)" ...
$ host_id : num [1:279712] 1466919 10328771 19252768 10668311 24837558 ...
$ host_since : Date[1:279712], format: "2011-12-03" "2013-11-29" "2014-07-31" "2013-12-17" ...
$ host_location : chr [1:279712] "Paris, Ile-de-France, France" "Paris, Ile-de-France, France" "Paris, Ile-de-France, France" "Paris, Ile-de-France, France" ...
$ host_response_time : chr [1:279712] NA NA NA NA ...
$ host_response_rate : num [1:279712] NA NA NA NA NA NA NA NA NA NA ...
$ host_acceptance_rate : num [1:279712] NA NA NA NA NA NA NA NA NA NA ...
$ host_is_superhost : logi [1:279712] FALSE FALSE FALSE FALSE FALSE FALSE ...
$ host_total_listings_count : num [1:279712] 1 1 1 1 1 1 1 1 1 1 ...
$ host_has_profile_pic : logi [1:279712] TRUE TRUE TRUE TRUE TRUE TRUE ...
$ host_identity_verified : logi [1:279712] FALSE TRUE FALSE TRUE FALSE TRUE ...
$ neighbourhood : chr [1:279712] "Buttes-Montmartre" "Buttes-Montmartre" "Elysee" "Vaugirard" ...
$ district : chr [1:279712] NA NA NA NA ...
$ city : chr [1:279712] "Paris" "Paris" "Paris" "Paris" ...
$ latitude : num [1:279712] 48.9 48.9 48.9 48.8 48.9 ...
$ longitude : num [1:279712] 2.33 2.35 2.32 2.31 2.27 ...
$ property_type : chr [1:279712] "Entire apartment" "Entire apartment" "Entire apartment" "Entire apartment" ...
$ room_type : chr [1:279712] "Entire place" "Entire place" "Entire place" "Entire place" ...
$ accommodates : num [1:279712] 2 2 2 2 2 2 2 2 2 2 ...
$ bedrooms : num [1:279712] 1 1 1 1 1 1 1 1 1 1 ...
$ amenities : chr [1:279712] "[\"Heating\", \"Kitchen\", \"Washer\", \"Wifi\", \"Long term stays allowed\"]" "[\"Shampoo\", \"Heating\", \"Kitchen\", \"Essentials\", \"Washer\", \"Dryer\", \"Wifi\", \"Long term stays allowed\"]" "[\"Heating\", \"TV\", \"Kitchen\", \"Washer\", \"Wifi\", \"Long term stays allowed\"]" "[\"Heating\", \"TV\", \"Kitchen\", \"Wifi\", \"Long term stays allowed\"]" ...
$ price : num [1:279712] 53 120 89 58 60 95 80 59 80 90 ...
$ minimum_nights : num [1:279712] 2 2 2 2 2 2 2 2 2 2 ...
$ maximum_nights : num [1:279712] 1125 1125 1125 1125 1125 ...
$ review_scores_rating : num [1:279712] 100 100 100 100 100 100 100 100 100 100 ...
$ review_scores_accuracy : num [1:279712] 10 10 10 10 10 10 10 10 10 10 ...
$ review_scores_cleanliness : num [1:279712] 10 10 10 10 10 10 10 10 10 10 ...
$ review_scores_checkin : num [1:279712] 10 10 10 10 10 10 10 10 10 10 ...
$ review_scores_communication: num [1:279712] 10 10 10 10 10 10 10 10 10 10 ...
$ review_scores_location : num [1:279712] 10 10 10 10 10 10 10 10 10 10 ...
$ review_scores_value : num [1:279712] 10 10 10 10 10 10 10 10 10 10 ...
$ instant_bookable : logi [1:279712] FALSE FALSE FALSE FALSE FALSE FALSE ...
- attr(*, "spec")=
.. cols(
.. listing_id = col_double(),
.. name = col_character(),
.. host_id = col_double(),
.. host_since = col_date(format = ""),
.. host_location = col_character(),
.. host_response_time = col_character(),
.. host_response_rate = col_double(),
.. host_acceptance_rate = col_double(),
.. host_is_superhost = col_logical(),
.. host_total_listings_count = col_double(),
.. host_has_profile_pic = col_logical(),
.. host_identity_verified = col_logical(),
.. neighbourhood = col_character(),
.. district = col_character(),
.. city = col_character(),
.. latitude = col_double(),
.. longitude = col_double(),
.. property_type = col_character(),
.. room_type = col_character(),
.. accommodates = col_double(),
.. bedrooms = col_double(),
.. amenities = col_character(),
.. price = col_double(),
.. minimum_nights = col_double(),
.. maximum_nights = col_double(),
.. review_scores_rating = col_double(),
.. review_scores_accuracy = col_double(),
.. review_scores_cleanliness = col_double(),
.. review_scores_checkin = col_double(),
.. review_scores_communication = col_double(),
.. review_scores_location = col_double(),
.. review_scores_value = col_double(),
.. instant_bookable = col_logical()
.. )
- attr(*, "problems")=<externalptr> summary(df) listing_id name host_id host_since host_location host_response_time
Min. : 2577 Length:279712 Min. : 1822 Min. :2008-08-12 Length:279712 Length:279712
1st Qu.:13844619 Class :character 1st Qu.: 17206558 1st Qu.:2014-07-01 Class :character Class :character
Median :27670985 Mode :character Median : 58269114 Median :2016-02-14 Mode :character Mode :character
Mean :26381955 Mean :108165773 Mean :2016-04-11
3rd Qu.:39784851 3rd Qu.:183285319 3rd Qu.:2018-04-09
Max. :48343530 Max. :390187445 Max. :2021-02-26
NA's :165
host_response_rate host_acceptance_rate host_is_superhost host_total_listings_count host_has_profile_pic
Min. :0.00 Min. :0.00 Mode :logical Min. : 0.00 Mode :logical
1st Qu.:0.90 1st Qu.:0.78 FALSE:229294 1st Qu.: 1.00 FALSE:916
Median :1.00 Median :0.98 TRUE :50253 Median : 1.00 TRUE :278631
Mean :0.87 Mean :0.83 NA's :165 Mean : 24.58 NA's :165
3rd Qu.:1.00 3rd Qu.:1.00 3rd Qu.: 4.00
Max. :1.00 Max. :1.00 Max. :7235.00
NA's :128782 NA's :113087 NA's :165
host_identity_verified neighbourhood district city latitude longitude
Mode :logical Length:279712 Length:279712 Length:279712 Min. :-34.26 Min. :-99.340
FALSE:78356 Class :character Class :character Class :character 1st Qu.:-22.96 1st Qu.:-43.198
TRUE :201191 Mode :character Mode :character Mode :character Median : 40.71 Median : 2.383
NA's :165 Mean : 18.76 Mean : 12.595
3rd Qu.: 41.91 3rd Qu.: 28.987
Max. : 48.90 Max. :151.340
property_type room_type accommodates bedrooms amenities price
Length:279712 Length:279712 Min. : 0.000 Min. : 1.000 Length:279712 Min. : 0.0
Class :character Class :character 1st Qu.: 2.000 1st Qu.: 1.000 Class :character 1st Qu.: 75.0
Mode :character Mode :character Median : 2.000 Median : 1.000 Mode :character Median : 150.0
Mean : 3.289 Mean : 1.516 Mean : 608.8
3rd Qu.: 4.000 3rd Qu.: 2.000 3rd Qu.: 474.0
Max. :16.000 Max. :50.000 Max. :625216.0
NA's :29435
minimum_nights maximum_nights review_scores_rating review_scores_accuracy review_scores_cleanliness
Min. : 1.000 Min. :1.000e+00 Min. : 20.00 Min. : 2.00 Min. : 2.00
1st Qu.: 1.000 1st Qu.:4.500e+01 1st Qu.: 91.00 1st Qu.: 9.00 1st Qu.: 9.00
Median : 2.000 Median :1.125e+03 Median : 96.00 Median :10.00 Median :10.00
Mean : 8.051 Mean :2.756e+04 Mean : 93.41 Mean : 9.57 Mean : 9.31
3rd Qu.: 5.000 3rd Qu.:1.125e+03 3rd Qu.:100.00 3rd Qu.:10.00 3rd Qu.:10.00
Max. :9999.000 Max. :2.147e+09 Max. :100.00 Max. :10.00 Max. :10.00
NA's :91405 NA's :91713 NA's :91665
review_scores_checkin review_scores_communication review_scores_location review_scores_value instant_bookable
Min. : 2.0 Min. : 2.0 Min. : 2.00 Min. : 2.00 Mode :logical
1st Qu.:10.0 1st Qu.:10.0 1st Qu.: 9.00 1st Qu.: 9.00 FALSE:164105
Median :10.0 Median :10.0 Median :10.00 Median :10.00 TRUE :115607
Mean : 9.7 Mean : 9.7 Mean : 9.63 Mean : 9.34
3rd Qu.:10.0 3rd Qu.:10.0 3rd Qu.:10.00 3rd Qu.:10.00
Max. :10.0 Max. :10.0 Max. :10.00 Max. :10.00
NA's :91771 NA's :91687 NA's :91775 NA's :91785 #deleting two columns i definitely won't use
df <- df |>
select(-latitude, -longitude)df |> colnames() [1] "listing_id" "name" "host_id"
[4] "host_since" "host_location" "host_response_time"
[7] "host_response_rate" "host_acceptance_rate" "host_is_superhost"
[10] "host_total_listings_count" "host_has_profile_pic" "host_identity_verified"
[13] "neighbourhood" "district" "city"
[16] "property_type" "room_type" "accommodates"
[19] "bedrooms" "amenities" "price"
[22] "minimum_nights" "maximum_nights" "review_scores_rating"
[25] "review_scores_accuracy" "review_scores_cleanliness" "review_scores_checkin"
[28] "review_scores_communication" "review_scores_location" "review_scores_value"
[31] "instant_bookable" df$host_location |> unique() [1] "Paris, Ile-de-France, France"
[2] "New York, New York, United States"
[3] "Hericy, Ile-de-France, France"
[4] "Montreuil, Ile-de-France, France"
[5] "FR"
[6] NA
[7] "Lyon, Rhone-Alpes, France"
[8] "Nice, Provence-Alpes-Côte d'Azur, France"
[9] "Raray, Hauts-de-France, France"
[10] "Saint-Pierre-du-Perray, Ile-de-France, France"
[11] "Angers, Pays de la Loire, France"
[12] "Mexico City, Federal District, Mexico"
[13] "Bordeaux, Aquitaine, France"
[14] "Caen, Lower Normandy, France"
[15] "Metz, Lorraine, France"
[16] "Toulouse, Languedoc-Roussillon-Midi-Pyrenees, France"
[17] "Montpellier, Languedoc-Roussillon, France"
[18] "Chateauneuf-de-Gadagne, Provence-Alpes-Côte d'Azur, France"
[19] "Nizhny Novgorod, Nizhny Novgorod Oblast, Russia"
[20] "Éragny, Ile-de-France, France"
[21] "Pau, Aquitaine-Limousin-Poitou-Charentes, France"
[22] "Meaux, Ile-de-France, France"
[23] "US"
[24] "Saint-Just-le-Martel, Nouvelle-Aquitaine, France"
[25] "Conches-sur-Gondoire, Ile-de-France, France"
[26] "Bezons, Ile-de-France, France"
[27] "Tunis, Tunis, Tunisia"
[28] "IE"
[29] "Les Éparres, Rhone-Alpes, France"
[30] "RS"
[31] "Triqueville, Upper Normandy, France"
[32] "Crevin, Brittany, France"
[33] "Tours, Centre-Val de Loire, France"
[34] "Los Angeles, California, United States"
[35] "Brooklyn, New York, United States"
[36] "Montreal, Quebec, Canada"
[37] "Taoyuan City, Taiwan"
[38] "Cape Town, Western Cape, South Africa"
[39] "ZA"
[40] "Rio de Janeiro, Rio de Janeiro, Brazil"
[41] "Rio de Janeiro, State of Rio de Janeiro, Brazil"
[42] "Tijuca, State of Rio de Janeiro, Brazil"
[43] "BR"
[44] "AU"
[45] "Bondi, New South Wales, Australia"
[46] "Sydney, New South Wales, Australia"
[47] "Parramatta, New South Wales, Australia"
[48] "Istanbul, Istanbul, Turkey"
[49] "Rome, Lazio, Italy"
[50] "AR"
[51] "Grottaferrata, Lazio, Italy"
[52] "China"
[53] "Darien, Connecticut, United States"
[54] "HK"
[55] "Hong Kong"
[56] "Mexico City, Mexico City, Mexico"
[57] "Wentworth Point, New South Wales, Australia"
[58] "Brighton-Le-Sands, New South Wales, Australia"
[59] "San Francisco, California, United States"
[60] "Gaja-et-Villedieu, Occitanie, France"
[61] "Ile-de-France, France"
[62] "Maisons-Laffitte, Ile-de-France, France"
[63] "Marseille, Provence-Alpes-Côte d'Azur, France"
[64] "Occitanie, France"
[65] "Seattle, Washington, United States"
[66] "Ciudad de Mexico, Ciudad de Mexico, Mexico"
[67] "MX"
[68] "Santiago de Queretaro, Queretaro, Mexico"
[69] "State of Mexico, Mexico"
[70] "Jerusalem Township, Ohio, United States"
[71] "Tlalnepantla de Baz, State of Mexico, Mexico"
[72] "The Hague, South Holland, Netherlands"
[73] "Sumare, State of Sao Paulo, Brazil"
[74] "Nova Iguacu, State of Rio de Janeiro, Brazil"
[75] "Hillsdale, New South Wales, Australia"
[76] "Old Guildford, New South Wales, Australia"
[77] "Newport, New South Wales, Australia"
[78] "Balgowlah, New South Wales, Australia"
[79] "New South Wales, Australia"
[80] "Bondi Beach, New South Wales, Australia"
[81] "Hurstville, New South Wales, Australia"
[82] "Puiseux-Pontoise, Ile-de-France, France"
[83] "Randwick, New South Wales, Australia"
[84] "Wolli Creek, New South Wales, Australia"
[85] "Pyrmont, New South Wales, Australia"
[86] "IT"
[87] "Portici, Campania, Italy"
[88] "London, England, United Kingdom"
[89] "Pantin, Ile-de-France, France"
[90] "Saint-Denis, Ile-de-France, France"
[91] "Pont-Ã -Marcq, Nord-Pas-de-Calais, France"
[92] "Nantes, Pays de la Loire, France"
[93] "Enghien-les-Bains, Ile-de-France, France"
[94] "Amsterdam, Noord-Holland, Netherlands"
[95] "Geneva, Geneva, Switzerland"
[96] "Drancy, Ile-de-France, France"
[97] "Boulogne-Billancourt, Ile-de-France, France"
[98] "Queens, New York, United States"
[99] "RU"
[100] "Bangkok, Thailand"
[101] "TH"
[102] "Gold Coast, Queensland, Australia"
[103] "Ashfield, New South Wales, Australia"
[104] "Turkey"
[105] "Perpignan, Languedoc-Roussillon, France"
[106] "CH"
[107] "Hong Kong, Hong Kong"
[108] "Rio, Rio de Janeiro, Brazil"
[109] "Ostia, Lazio, Italy"
[110] "Toulouse, Midi-Pyrenees, France"
[111] "Acacia Gardens, New South Wales, Australia"
[112] "France"
[113] "Lyon, Auvergne-Rhône-Alpes, France"
[114] "Manly, New South Wales, Australia"
[115] "Istanbul, Turkey"
[116] "Saint-Cloud, Ile-de-France, France"
[117] "Marnes-la-Coquette, Ile-de-France, France"
[118] "Bloomington, Indiana, United States"
[119] "Montigny-le-Bretonneux, Ile-de-France, France"
[120] "Berlin, Berlin, Germany"
[121] "Brooklyn, NY"
[122] "Arcadia, California, United States"
[123] "Cagliari, Sardinia, Italy"
[124] "Philadelphia, Pennsylvania, United States"
[125] "Singapore"
[126] "Johannesburg, Gauteng, South Africa"
[127] "Juiz de Fora, Minas Gerais, Brazil"
[128] "Double Bay, New South Wales, Australia"
[129] "Cronulla, New South Wales, Australia"
[130] "Mona Vale, New South Wales, Australia"
[131] "Surry Hills, New South Wales, Australia"
[132] "Fairlight, New South Wales, Australia"
[133] "Castlecrag, New South Wales, Australia"
[134] "Carlingford, New South Wales, Australia"
[135] "St Leonards, New South Wales, Australia"
[136] "Tamarama, New South Wales, Australia"
[137] "Woolloomooloo, New South Wales, Australia"
[138] "Kadıköy, Istanbul, Turkey"
[139] "TR"
[140] "ES"
[141] "Santa Monica, California, United States"
[142] "Manhattan"
[143] "Denver, Colorado, United States"
[144] "Melbourne, Victoria, Australia"
[145] "Zürich, Zurich, Switzerland"
[146] "La Seyne-sur-Mer, Provence-Alpes-Côte d'Azur, France"
[147] "Castelnaudary, Occitanie, France"
[148] "State of Rio de Janeiro, Brazil"
[149] "Sarıyer, Istanbul, Turkey"
[150] "BeÅŸiktaÅŸ, Istanbul, Turkey"
[151] "Le Pre-Saint-Gervais, Ile-de-France, France"
[152] "San Miniato, Toscana, Italy"
[153] "Perpignan, Languedoc-Roussillon Midi-Pyrenees, France"
[154] "Vincennes, Ile-de-France, France"
[155] "Rennes, Brittany, France"
[156] "DE"
[157] "Sorgues, Provence-Alpes-Côte d'Azur, France"
[158] "Rouen, Normandy, France"
[159] "Calgary, Alberta, Canada"
[160] "Salon-de-Provence, Provence-Alpes-Côte d'Azur, France"
[161] "Bangkok/TH"
[162] "Hong Kong Island, Hong Kong"
[163] "Naucalpan, State of Mexico, Mexico"
[164] "RO"
[165] "Fortaleza, Ceara, Brazil"
[166] "Brasilia, State of Sao Paulo, Brazil"
[167] "Zola Predosa, Emilia-Romagna, Italy"
[168] "Sao Paulo, State of Sao Paulo, Brazil"
[169] "Belo Horizonte, State of Minas Gerais, Brazil"
[170] "Melbourne, Florida, United States"
[171] "Vila Velha, EspÃrito Santo, Brazil"
[172] "Clovelly, New South Wales, Australia"
[173] "Artigues-près-Bordeaux, Aquitaine, France"
[174] "Newtown, New South Wales, Australia"
[175] "Kingsford, New South Wales, Australia"
[176] "Neutral Bay, New South Wales, Australia"
[177] "Bordeaux, Nouvelle-Aquitaine, France"
[178] "CN"
[179] "Bogota, Bogota, Colombia"
[180] "London, England"
[181] "Skukuza, Mpumalanga, South Africa"
[182] "Pretoria, Gauteng, South Africa"
[183] "Joinville, Santa Catarina, Brazil"
[184] "Orlando, Florida, United States"
[185] "De Pinte, Flanders, Belgium"
[186] "Jacarepagua, State of Rio de Janeiro, Brazil"
[187] "Ipanema, State of Rio de Janeiro, Brazil"
[188] "Ribeirao Preto, State of Sao Paulo, Brazil"
[189] "Chatswood, New South Wales, Australia"
[190] "Manhattan Beach, California, United States"
[191] "Ulaanbaatar, Ulaanbaatar, Mongolia"
[192] "Lugano, Ticino, Switzerland"
[193] "Scarsdale, New York, United States"
[194] "Checy, Centre, France"
[195] "Mantes-la-Jolie, Ile-de-France, France"
[196] "Orsay, Ile-de-France, France"
[197] "Montceau-les-Mines, Bourgogne-Franche-Comte, France"
[198] "Sannois, Ile-de-France, France"
[199] "Alixan, Auvergne-Rhône-Alpes, France"
[200] "Madrid, Community of Madrid, Spain"
[201] "Dourdan, Ile-de-France, France"
[202] "Pornic, Pays de la Loire, France"
[203] "Dallas, Texas, United States"
[204] "Union, New Jersey, United States"
[205] "Bangkok,Thailand"
[206] "Santa Cruz de la Sierra, Santa Cruz Department, Bolivia"
[207] "BrasÃlia, Federal District, Brazil"
[208] "Nova Iguacu, Rio de Janeiro, Brazil"
[209] "Coogee, New South Wales, Australia"
[210] "Istanbul"
[211] "Edmonton, Alberta, Canada"
[212] "Hastings, Nebraska, United States"
[213] "Saint-Nom-la-Bretèche, Ile-de-France, France"
[214] "Biarritz, Nouvelle-Aquitaine, France"
[215] "Gif-sur-Yvette, Ile-de-France, France"
[216] "Carpentras, Provence-Alpes-Côte d'Azur, France"
[217] "Clichy, Ile-de-France, France"
[218] "GB"
[219] "Bordeaux, Aquitaine-Limousin-Poitou-Charentes, France"
[220] "MY"
[221] "Herrlisheim-près-Colmar, Alsace-Champagne-Ardenne-Lorraine, France"
[222] "Ajaccio, Corsica, France"
[223] "Bondues, Nord-Pas-de-Calais, France"
[224] "England, United Kingdom"
[225] "Fontenay-sous-Bois, Ile-de-France, France"
[226] "New Territories, Hong Kong"
[227] "Mexico City, Distrito Federal, Mexico"
[228] "Taruma, Rio Grande do Sul, Brazil"
[229] "Alexandria, New South Wales, Australia"
[230] "Vaucluse, New South Wales, Australia"
[231] "Bangkok"
[232] "London, United Kingdom"
[233] "ÅžiÅŸli, Istanbul, Turkey"
[234] "Milan, Lombardy, Italy"
[235] "Italy"
[236] "Roseto degli Abruzzi, Abruzzo, Italy"
[237] "Ho Chi Minh City, Ho Chi Minh, Vietnam"
[238] "Bengaluru, Karnataka, India"
[239] "Tel Aviv, Israel"
[240] "Jersey City, New Jersey, United States"
[241] "Tournefeuille, Occitanie, France"
[242] "Fleury, Occitanie, France"
[243] "Audenge, Aquitaine, France"
[244] "Saulx-les-Chartreux, Ile-de-France, France"
[245] "Mesnay, Bourgogne-Franche-Comte, France"
[246] "Metz, Alsace-Champagne-Ardenne-Lorraine, France"
[247] "AI"
[248] "Blanquefort, Aquitaine, France"
[249] "Shanghai, Shanghai, China"
[250] "Macae, Rio de Janeiro, Brazil"
[251] "Écouen, Ile-de-France, France"
[252] "Brazil"
[253] "Copacabana, State of Rio de Janeiro, Brazil"
[254] "Gladesville, New South Wales, Australia"
[255] "Marrakesh, Marrakesh-Tensift-El Haouz, Morocco"
[256] "NL"
[257] "Dee Why, New South Wales, Australia"
[258] "Beirut, Beirut, Lebanon"
[259] "The Bronx, New York, United States"
[260] "Florence, Tuscany, Italy"
[261] "CA"
[262] "Australia"
[263] "Still Bay, Western Cape, South Africa"
[264] "Rushcutters Bay, New South Wales, Australia"
[265] "Dundas, New South Wales, Australia"
[266] "Freshwater, New South Wales, Australia"
[267] "Ravenna, Emilia-Romagna, Italy"
[268] "Lamezia Terme, Calabria, Italy"
[269] "Annecy-le-Vieux, Rhone-Alpes, France"
[270] "Saint-Maurice, Ile-de-France, France"
[271] "Amsterdam, North Holland, The Netherlands"
[272] "St-Genis-Laval, Auvergne-Rhône-Alpes, France"
[273] "Clamart, Ile-de-France, France"
[274] "Saint-Martin-d'Auxigny, Centre-Val de Loire, France"
[275] "Caen, Normandy, France"
[276] "Perpignan, Occitanie, France"
[277] "Manhattan, NY"
[278] "San Diego, California, United States"
[279] "Brasil"
[280] "Manaus, Amazonas, Brazil"
[281] "Waterloo, New South Wales, Australia"
[282] "Rose Bay, New South Wales, Australia"
[283] "Sydney Olympic Park, New South Wales, Australia"
[284] "Maroubra, New South Wales, Australia"
[285] "Ciampino, Lazio, Italy"
[286] "Naples, Campania, Italy"
[287] "Aix-en-Provence, Provence-Alpes-Côte d'Azur, France"
[288] "Saint-Jean-du-Thenney, Normandy, France"
[289] "Le Mesnil-Saint-Denis, Ile-de-France, France"
[290] "La Celle-Saint-Cloud, Ile-de-France, France"
[291] "Versailles, Ile-de-France, France"
[292] "Grenoble, France"
[293] "Bedford - Stuyvesant, New York, United States"
[294] "Catete, State of Rio de Janeiro, Brazil"
[295] "Meadowbank, New South Wales, Australia"
[296] "Castle Hill, New South Wales, Australia"
[297] "Nepal"
[298] "Bilbao, Basque Country, Spain"
[299] "Collalto Sabino, Lazio, Italy"
[300] "Bilthoven, Utrecht, The Netherlands"
[301] "Stellenbosch, Western Cape, South Africa"
[302] "Western Cape, South Africa"
[303] "AguaÃ, State of Sao Paulo, Brazil"
[304] "Potts Point, New South Wales, Australia"
[305] "Municipio Roma X, Lazio, Italy"
[306] "Monaco"
[307] "Bry-sur-Marne, Ile-de-France, France"
[308] "La Breille-les-Pins, Pays de la Loire, France"
[309] "Saint-Cyr-sur-Mer, Provence-Alpes-Côte d'Azur, France"
[310] "Villiers-sur-Marne, Ile-de-France, France"
[311] "Plaisir, Ile-de-France, France"
[312] "Triel-sur-Seine, Ile-de-France, France"
[313] "Ferrières-en-Brie, Ile-de-France, France"
[314] "Nogent-sur-Marne, Ile-de-France, France"
[315] "Raleigh, North Carolina, United States"
[316] "Teyran, Languedoc-Roussillon, France"
[317] "Barcelona, Catalonia, Spain"
[318] "Saint-Barthelemy-d'Anjou, Pays de la Loire, France"
[319] "Claye-Souilly, Ile-de-France, France"
[320] "CY"
[321] "Épinay-sur-Orge, Ile-de-France, France"
[322] "Ermont, Ile-de-France, France"
[323] "Perth, Western Australia, Australia"
[324] "Saint-Germain-des-Pres, Pays de la Loire, France"
[325] "Bayonne, Nouvelle-Aquitaine, France"
[326] "I'm residing between Paris and Barcelona"
[327] "Copenhagen, Denmark"
[328] "Washington, District of Columbia, United States"
[329] "Belle Isle, Florida, United States"
[330] "Bangkok, Bangkok, Thailand"
[331] "Gauteng, South Africa"
[332] "Kensington, New South Wales, Australia"
[333] "MacGregor, Queensland, Australia"
[334] "Paddington, New South Wales, Australia"
[335] "Salzburg, Salzburg, Austria"
[336] "Saint-Germain-en-Laye, Ile-de-France, France"
[337] "Bagnolet, Ile-de-France, France"
[338] "Cancun, Quintana Roo, Mexico"
[339] "Macquarie Park, New South Wales, Australia"
[340] "Wollstonecraft, New South Wales, Australia"
[341] "Rambouillet, Ile-de-France, France"
[342] "Saint-Maur-des-Fosses, Ile-de-France, France"
[343] "Austin, Texas, United States"
[344] "Saint-Raphaël, Provence-Alpes-Côte d'Azur, France"
[345] "Orange, New South Wales, Australia"
[346] "North Bondi, New South Wales, Australia"
[347] "New Jersey, United States"
[348] "CZ"
[349] "Mexico"
[350] "Pennant Hills, New South Wales, Australia"
[351] "I'm living in Paris but spend large amounts of my time in Portugal."
[352] "Mexico DF"
[353] "Vancouver, British Columbia, Canada"
[354] "Spain"
[355] "West Pennant Hills, New South Wales, Australia"
[356] "Rhodes, New South Wales, Australia"
[357] "Ariccia, Lazio, Italy"
[358] "Giulianova, Abruzzo, Italy"
[359] "RE"
[360] "Jakarta, Indonesia"
[361] "Cergy, Ile-de-France, France"
[362] "Issy-les-Moulineaux, Ile-de-France, France"
[363] "Lyon, Rhône-Alpes, France"
[364] "Saint-Ouen, Ile-de-France, France"
[365] "Moscow, Moscow, Russia"
[366] "Lods, Bourgogne-Franche-Comte, France"
[367] "Roubaix, Hauts-de-France, France"
[368] "Ville-d'Avray, Ile-de-France, France"
[369] "Bang Rak, Bangkok, Thailand"
[370] "Leme, State of Rio de Janeiro, Brazil"
[371] "Leichhardt, New South Wales, Australia"
[372] "Hamburg, Hamburg, Germany"
[373] "Tel Aviv-Yafo, Tel Aviv District, Israel"
[374] "India"
[375] "Thailand"
[376] "Markham, Ontario, Canada"
[377] "Belgium"
[378] "Wheatley, England, United Kingdom"
[379] "Brussels, Brussels, Belgium"
[380] "Bronx, New York, United States"
[381] "Guanajuato, Guanajuato, Mexico"
[382] "Navegantes, State of Santa Catarina, Brazil"
[383] "North Strathfield, New South Wales, Australia"
[384] "Velletri, Lazio, Italy"
[385] "Boussy-Saint-Antoine, Ile-de-France, France"
[386] "Atlanta, Georgia, United States"
[387] "Staten Island, New York, United States"
[388] "Annandale, New South Wales, Australia"
[389] "Blacktown, New South Wales, Australia"
[390] "SA"
[391] "Luxembourg City, Luxembourg District, Luxembourg"
[392] "Pujaut, Occitanie, France"
[393] "Laneuveville-devant-Nancy, Lorraine, France"
[394] "Lille, Hauts-de-France, France"
[395] "Agua Dulce, California, United States"
[396] "Yonkers, New York, United States"
[397] "Cleveland, Ohio, United States"
[398] "O'Malley, Australian Capital Territory, Australia"
[399] "roma vaticano"
[400] "Lazio, Italy"
[401] "Marino, Lazio, Italy"
[402] "Lido di Ostia, Lazio, Italy"
[403] "Stonington, Connecticut, United States"
[404] "New Canaan, Connecticut, United States"
[405] "Huntingdale, Victoria, Australia"
[406] "Bernex, Geneva, Switzerland"
[407] "Uccle, Brussels, Belgium"
[408] "Poitiers, Aquitaine-Limousin-Poitou-Charentes, France"
[409] "Hyères, Provence-Alpes-Côte d'Azur, France"
[410] "Arezzo, Tuscany, Italy"
[411] "Reims, Champagne-Ardenne, France"
[412] "Le Vesinet, Ile-de-France, France"
[413] "Khet Phra Nakhon, Krung Thep Maha Nakhon, Thailand"
[414] "Morelia, Michoacan, Mexico"
[415] "Naucalpan de Juarez, State of Mexico, Mexico"
[416] "Frankfurt, Hesse, Germany"
[417] "Stockholm, Stockholm County, Sweden"
[418] "Darling Point, New South Wales, Australia"
[419] "Botany, New South Wales, Australia"
[420] "Bronte, New South Wales, Australia"
[421] "Bundeena, New South Wales, Australia"
[422] "Chifley, New South Wales, Australia"
[423] "Munich, Bavaria, Germany"
[424] "Istanbul, Istanbul Province, Turkey"
[425] "Malakoff, Ile-de-France, France"
[426] "Cachan, Ile-de-France, France"
[427] "Bedford, New York, United States"
[428] "Caxias do Sul, Rio Grande do Sul, Brazil"
[429] "Paciencia, State of Rio de Janeiro, Brazil"
[430] "Katy, Texas, United States"
[431] "Barra da Tijuca, State of Rio de Janeiro, Brazil"
[432] "Campinas, State of Sao Paulo, Brazil"
[433] "Woolooware, New South Wales, Australia"
[434] "San Pedro Apatlaco, Morelos, Mexico"
[435] "Rio das Ostras, Rio de Janeiro, Brazil"
[436] "Carqueiranne, Provence-Alpes-Côte d'Azur, France"
[437] "Brioude, Auvergne, France"
[438] "Brittany, France"
[439] "Milwaukee, Wisconsin, United States"
[440] "San Antonio, Texas, United States"
[441] "Malmesbury, Western Cape, South Africa"
[442] "Liège, Walloon Region, Belgium"
[443] "Atibaia, Sao Paulo, Brazil"
[444] "Toronto, Ontario, Canada"
[445] "Bellevue Hill, New South Wales, Australia"
[446] "Maroubra Beach"
[447] "Büyükcekmece, Istanbul, Turkey"
[448] "BeyoÄŸlu, Istanbul, Turkey"
[449] "Neuilly-sur-Seine, Ile-de-France, France"
[450] "Aberdeen, Scotland, United Kingdom"
[451] "Lagoa, State of Rio de Janeiro, Brazil"
[452] "Lille, Nord-Pas-de-Calais, France"
[453] "Newton, Wisconsin, United States"
[454] "Byron Bay, New South Wales, Australia"
[455] "Stuttgart, Baden-Württemberg, Germany"
[456] "Italia"
[457] "Centre-Val de Loire, France"
[458] "Toulouse, Occitanie, France"
[459] "Fatih, Istanbul Province, Turkey"
[460] "Murcia, Region of Murcia, Spain"
[461] "Camorim, State of Rio de Janeiro, Brazil"
[462] "Millburn, New Jersey, United States"
[463] "Canada Bay, New South Wales, Australia"
[464] "Tallard, Provence-Alpes-Côte d'Azur, France"
[465] "Orgeval, Ile-de-France, France"
[466] "Nova Lima, Minas Gerais, Brazil"
[467] "Houston, Texas, United States"
[468] "Sao Conrado, Rio de Janeiro, Brazil"
[469] "Bussy-Saint-Georges, Ile-de-France, France"
[470] "Vermont, United States"
[471] "Valley Stream, New York, United States"
[472] "Mosman, New South Wales, Australia"
[473] "Redondo Beach, California, United States"
[474] "Pagewood, New South Wales, Australia"
[475] "Beacon Hill, New South Wales, Australia"
[476] "St. Gallen, St. Gallen, Switzerland"
[477] "Chappaqua, New York, United States"
[478] "Santa Barbara, California, United States"
[479] "Hidden Hills, California, United States"
[480] "Thousand Oaks, California, United States"
[481] "South Yarra, Victoria, Australia"
[482] "EG"
[483] "Boulder, Colorado, United States"
[484] "Haverford, Pennsylvania, United States"
[485] "CO"
[486] "Le Kremlin-Bicetre, Ile-de-France, France"
[487] "Tours, Centre, France"
[488] "Mexico D. F."
[489] "Duque de Caxias, Rio de Janeiro, Brazil"
[490] "Campo Grande, State of Rio de Janeiro, Brazil"
[491] "Marsfield, New South Wales, Australia"
[492] "Beaurepaire, Pays de la Loire, France"
[493] "Mombasa, Mombasa, Kenya"
[494] "Sandton, Gauteng, South Africa"
[495] "Wethersfield, England, United Kingdom"
[496] "Galeao, State of Rio de Janeiro, Brazil"
[497] "Barra do PiraÃ, State of Rio de Janeiro, Brazil"
[498] "Sao Carlos, Sao Paulo, Brazil"
[499] "Little Bay, New South Wales, Australia"
[500] "Levallois-Perret, Ile-de-France, France"
[501] "Sèvres, Ile-de-France, France"
[502] "Sao Paulo, Sao Paulo, Brazil"
[503] "Petropolis, Rio de Janeiro, Brazil"
[504] "Florianopolis, State of Santa Catarina, Brazil"
[505] "Brasilia, Federal District, Brazil"
[506] "Federal District, Mexico"
[507] "New Delhi, Delhi, India"
[508] "Bangkok , Thailand"
[509] "Barranquilla, Atlantico, Colombia"
[510] "Pilares, State of Rio de Janeiro, Brazil"
[511] "Guaratiba, State of Rio de Janeiro, Brazil"
[512] "Recreio dos Bandeirantes, State of Rio de Janeiro, Brazil"
[513] "Saint-Prex, Vaud, Switzerland"
[514] "Northwood, New South Wales, Australia"
[515] "Little Bay, Arkansas, United States"
[516] "Serris, Ile-de-France, France"
[517] "Champagne-au-Mont-d'Or, Rhone-Alpes, France"
[518] "Northampton, Massachusetts, United States"
[519] "Seoul, Korea"
[520] "Turin, Piedmont, Italy"
[521] "Seoul, South Korea"
[522] "Merignac, Nouvelle-Aquitaine, France"
[523] "Le Mans, Pays de la Loire, France"
[524] "Asnières-sur-Seine, Ile-de-France, France"
[525] "Le Blanc-Mesnil, Ile-de-France, France"
[526] "Maisons-Alfort, Ile-de-France, France"
[527] "Alexandria, Alexandria, Egypt"
[528] "Santa Teresa, State of Rio de Janeiro, Brazil"
[529] "Cidade Universitaria, State of Sao Paulo, Brazil"
[530] "Campos, State of Rio de Janeiro, Brazil"
[531] "Forestville, New South Wales, Australia"
[532] "Victoria, Australia"
[533] "Dijon, Burgundy, France"
[534] "Pondok Aren, Banten, Indonesia"
[535] "Nakhon Si Thammarat, Nakhon Si Thammarat, Thailand"
[536] "SE"
[537] "Prague, Hlavnà město Praha, Czech Republic"
[538] "Auckland, Auckland, New Zealand"
[539] "Morsang-sur-Orge, Ile-de-France, France"
[540] "Thiais, Ile-de-France, France"
[541] "Bouliac, Nouvelle-Aquitaine, France"
[542] "Bourges, Centre-Val de Loire, France"
[543] "Fresnes, Ile-de-France, France"
[544] "Agadir, Souss-Massa-Draa, Morocco"
[545] "Grenoble, Rhone-Alpes, France"
[546] "Saint-Jean-de-Monts, Pays de la Loire, France"
[547] "Casablanca, Casablanca-Settat, Morocco"
[548] "Macau"
[549] "Marica, Rio de Janeiro, Brazil"
[550] "Flamengo, Rio de Janeiro, Brazil"
[551] "Waverley, New South Wales, Australia"
[552] "Haymarket, New South Wales, Australia"
[553] "Wollongong, New South Wales"
[554] "Darlington, New South Wales, Australia"
[555] "Totowa, New Jersey, United States"
[556] "Perry, Florida, United States"
[557] "White Plains, New York, United States"
[558] "Dubai, Dubai, United Arab Emirates"
[559] "Palo Alto, California, United States"
[560] "Chicago, Illinois, United States"
[561] "Kelowna, British Columbia, Canada"
[562] "Salina, Kansas, United States"
[563] "St. Louis, Missouri, United States"
[564] "GR"
[565] "Warwick, New York, United States"
[566] "Richmond, British Columbia, Canada"
[567] "Harrison, New Jersey, United States"
[568] "Jerusalem, Israel"
[569] "Charlotte, North Carolina, United States"
[570] "ReykjavÃk, Iceland"
[571] "Orleans, Centre-Val de Loire, France"
[572] "Girolles, Bourgogne-Franche-Comte, France"
[573] "Gennevilliers, Ile-de-France, France"
[574] "Saint-Jeannet, Provence-Alpes-Côte d'Azur, France"
[575] "Val-de-Marne, Ile-de-France, France"
[576] "Courville-sur-Eure, Centre-Val de Loire, France"
[577] "Nimes, Languedoc-Roussillon, France"
[578] "Rapid City, South Dakota, United States"
[579] "Hanover, New Hampshire, United States"
[580] "Saint Louis, Missouri, United States"
[581] "Lapa, State of Sao Paulo, Brazil"
[582] "Forest Lodge, New South Wales, Australia"
[583] "South Bowenfels, New South Wales, Australia"
[584] "Queensland, Australia"
[585] "Shinjuku, Tokyo, Japan"
[586] "United Arab Emirates"
[587] "Taipei City, Taiwan"
[588] "Bologna, Emilia-Romagna, Italy"
[589] "Louveciennes, Ile-de-France, France"
[590] "MA"
[591] "L'Isle-Adam, Ile-de-France, France"
[592] "Champs-sur-Marne, Ile-de-France, France"
[593] "Poitiers, Poitou-Charentes, France"
[594] "Cauville-sur-Mer, Normandy, France"
[595] "Aulnay-sous-Bois, Ile-de-France, France"
[596] "TN"
[597] "Villers-Saint-Sepulcre, Hauts-de-France, France"
[598] "SJ"
[599] "Chaville, Ile-de-France, France"
[600] "Aarhus, Central Denmark Region, Denmark"
[601] "West Palm Beach, Florida, United States"
[602] "JP"
[603] "Atherton, California, United States"
[604] "Aterrado, Rio de Janeiro, Brazil"
[605] "Seaforth, New South Wales, Australia"
[606] "Darlinghurst, New South Wales, Australia"
[607] "Perugia, Umbria, Italy"
[608] "Lyon, Auvergne Rhône-Alpes, France"
[609] "Mouans-Sartoux, Provence-Alpes-Côte d'Azur, France"
[610] "Boston, Massachusetts, United States"
[611] "Teaneck, New Jersey, United States"
[612] "PH"
[613] "Le Teich, Aquitaine, France"
[614] "Casablanca, Grand Casablanca, Morocco"
[615] "Neuilly-Plaisance, Ile-de-France, France"
[616] "Blois, Centre-Val de Loire, France"
[617] "Sainte-Marie, La Trinite, Martinique"
[618] "Nanjing, Jiangsu, China"
[619] "Fort Lauderdale, Florida, United States"
[620] "Provincetown, Massachusetts, United States"
[621] "United States"
[622] "IL"
[623] "Gloria, State of Rio de Janeiro, Brazil"
[624] "Cerveteri, Lazio, Italy"
[625] "Burlington, Vermont, United States"
[626] "Tampa, Florida, United States"
[627] "Scottsdale, Arizona, United States"
[628] "Hangzhou, Zhejiang, China"
[629] "Berkeley, California, United States"
[630] "Miami, Florida, United States"
[631] "Kenilworth, Illinois, United States"
[632] "London, Ontario, Canada"
[633] "Tewksbury, New Jersey, United States"
[634] "Cranford, New Jersey, United States"
[635] "Mitcham, England, United Kingdom"
[636] "El Granada, California, United States"
[637] "Amsterdam, North Holland, Netherlands"
[638] "Moscow, Russia"
[639] "Plano, Texas, United States"
[640] "Italy, New York, United States"
[641] "New Haven, Connecticut, United States"
[642] "Dover Heights, New South Wales, Australia"
[643] "Vienna, Virginia, United States"
[644] "Elkins Park, Pennsylvania, United States"
[645] "Glendale, Arizona, United States"
[646] "Stantonsburg, North Carolina, United States"
[647] "Asbury, New Jersey, United States"
[648] "TEL AVIV"
[649] "Boca Raton, Florida, United States"
[650] "Singapore, Singapore"
[651] "Lancaster, Pennsylvania, United States"
[652] "Wilton, Connecticut, United States"
[653] "Spokane, Washington, United States"
[654] "Port Washington, New York, United States"
[655] "Petropavlovsk-Kamchatskiy, Kamchatka Krai, Russia"
[656] "Cambridge, Massachusetts, United States"
[657] "Kingston, New York, United States"
[658] "Scranton, Pennsylvania, United States"
[659] "Phoenix, Arizona, United States"
[660] "Chiang Mai, Chiang Mai, Thailand"
[661] "Treviso, Veneto, Italy"
[662] "Montego Bay, Saint James Parish, Jamaica"
[663] "Bangkok / London"
[664] "Bath, England, United Kingdom"
[665] "Nong Prue, Samut Prakan, Thailand"
[666] "KR"
[667] "Flamengo, State of Rio de Janeiro, Brazil"
[668] "Camperdown, New South Wales, Australia"
[669] "Wyongah, New South Wales, Australia"
[670] "Palaiseau, Ile-de-France, France"
[671] "Elizabeth Bay, New South Wales, Australia"
[672] "Chester, England, United Kingdom"
[673] "Dublin, County Dublin, Ireland"
[674] "Kirribilli, New South Wales, Australia"
[675] "Chatswood West, New South Wales, Australia"
[676] "London"
[677] "Courbevoie, Ile-de-France, France"
[678] "Chambourcy, Ile-de-France, France"
[679] "Lisbon, Lisbon, Portugal"
[680] "Amritsar, Punjab, India"
[681] "Warsaw, Masovian Voivodeship, Poland"
[682] "Trouville-sur-Mer, Normandy, France"
[683] "Montpellier, Languedoc-Roussillon-Midi-Pyrenees, France"
[684] "Sens, Burgandy, France"
[685] "Le Mesnil-le-Roi, Ile-de-France, France"
[686] "Courdimanche, Ile-de-France, France"
[687] "Carcassonne, Occitanie, France"
[688] "Strasbourg, Alsace, France"
[689] "Clisson, Pays de la Loire, France"
[690] "Saint-Leu-la-Foret, Ile-de-France, France"
[691] "Élancourt, Ile-de-France, France"
[692] "Macon, Bourgogne-Franche-Comte, France"
[693] "Big studio of 33 m² with an amazing view in Paris18e"
[694] "Sceaux, Ile-de-France, France"
[695] "Colombes, Ile-de-France, France"
[696] "EU"
[697] "Khania, Crete, Greece"
[698] "Beijing, Beijing, China"
[699] "Romainville, Ile-de-France, France"
[700] "Paris, Texas, United States"
[701] "Chamalières, Auvergne-Rhône-Alpes, France"
[702] "Burgundy, France"
[703] "Craponne-sur-Arzon, Auvergne Rhône-Alpes, France"
[704] "Rueil-Malmaison, Ile-de-France, France"
[705] "Precy-sur-Vrin, Burgandy, France"
[706] "Arlington, Virginia, United States"
[707] "Fontaine-lès-Dijon, Bourgogne Franche-Comte, France"
[708] "Langres, Alsace-Champagne-Ardenne-Lorraine, France"
[709] "Montpellier, Occitanie, France"
[710] "Dijon, Burgandy, France"
[711] "Troisvaux, Hauts-de-France, France"
[712] "Amiens, Picardy, France"
[713] "Livry-sur-Seine, Ile-de-France, France"
[714] "Aurillac, Auvergne-Rhône-Alpes, France"
[715] "Nanterre, Ile-de-France, France"
[716] "Coëtmieux, Brittany, France"
[717] "Bourg-la-Reine, Ile-de-France, France"
[718] "Peymeinade, Provence-Alpes-Côte d'Azur, France"
[719] "Vigneux-sur-Seine, Ile-de-France, France"
[720] "Malabo, Bioko Norte, Equatorial Guinea"
[721] "Luxembourg City, Luxembourg, Luxembourg"
[722] "Lorient, Brittany, France"
[723] "Garges-lès-Gonesse, Ile-de-France, France"
[724] "Chong Khaep, Tak, Thailand"
[725] "La Rochelle, Nouvelle-Aquitaine, France"
[726] "Chelles, Ile-de-France, France"
[727] "Haux, Aquitaine-Limousin-Poitou-Charentes, France"
[728] "La Rochelle, Poitou-Charentes, France"
[729] "MU"
[730] "Étrepagny, Normandy, France"
[731] "Cambrai, Nord-Pas-de-Calais, France"
[732] "Le Bois-Plage-en-Re, Nouvelle-Aquitaine, France"
[733] "Sainte-Savine, Champagne-Ardenne, France"
[734] "Hendaye, Nouvelle-Aquitaine, France"
[735] "LB"
[736] "Auvergne-Rhône-Alpes, France"
[737] "I live in Bogota and spend summer in France"
[738] "Mougins, Provence-Alpes-Côte d'Azur, France"
[739] "Reims, Grand Est, France"
[740] "Saint-Étienne, Auvergne-Rhône-Alpes, France"
[741] "Ivry-sur-Seine, Ile-de-France, France"
[742] "Luxemburg City, Luxembourg, Luxembourg"
[743] "Fougères, Brittany, France"
[744] "Le Gosier, Grande-Terre, Guadeloupe"
[745] "Cesson, Ile-de-France, France"
[746] "Nastringues, Nouvelle-Aquitaine, France"
[747] "Paros, Egeo, Greece"
[748] "Pont-Éveque, France"
[749] "Amiens, Hauts-de-France, France"
[750] "Soorts-Hossegor, Aquitaine Limousin Poitou-Charentes, France"
[751] "Houilles, Ile-de-France, France"
[752] "Arrecife, Canary Islands, Spain"
[753] "Sainte-Foy-lès-Lyon, Rhone-Alpes, France"
[754] "Tassin-la-Demi-Lune, Auvergne-Rhône-Alpes, France"
[755] "Dalian, Liaoning, China"
[756] "Le Havre, Normandy, France"
[757] "Croissy-sur-Seine, Ile-de-France, France"
[758] "Neuille-Pont-Pierre, Centre-Val de Loire, France"
[759] "Killarney Heights, New South Wales, Australia"
[760] "Sydney, Chicago, Jamaica"
[761] "Birdwood, South Australia, Australia"
[762] "Marrickville, New South Wales, Australia"
[763] "Brisbane, Queensland, Australia"
[764] "Tonawanda, New York, United States"
[765] "Fethiye, MuÄŸla Province, Turkey"
[766] "Samut Prakan, Thailand"
[767] "Hong Kong, Kowloon, Hong Kong"
[768] "RD"
[769] "Cammeray, New South Wales, Australia"
[770] "Trondheim, Sor-Trondelag, Norway"
[771] "Heathmont, Victoria, Australia"
[772] "Caxias do Sul, State of Rio Grande do Sul, Brazil"
[773] "Freyming-Merlebach, Lorraine, France"
[774] "Bois d'Arcy, Ile-de-France, France"
[775] "Antibes, Provence-Alpes-Côte d'Azur, France"
[776] "Sainte-Geneviève-des-Bois, Ile-de-France, France"
[777] "Saint-Germain-sur-Morin, Ile-de-France, France"
[778] "Toshima City, Tokyo, Japan"
[779] "Marsac-sur-Don, Pays de la Loire, France"
[780] "Lisse, South Holland, Netherlands"
[781] "Villepinte, Ile-de-France, France"
[782] "Clermont-Ferrand, Auvergne, France"
[783] "Aubervilliers, Ile-de-France, France"
[784] "Bois-Colombes, Ile-de-France, France"
[785] "Poitiers, Nouvelle-Aquitaine, France"
[786] "Estonia"
[787] "Lille, Nord-Pas-de-Calais Picardie, France"
[788] "Fontaine-lès-Dijon, Bourgogne-Franche-Comte, France"
[789] "Strasbourg, Alsace-Champagne-Ardenne-Lorraine, France"
[790] "Rubelles, Ile-de-France, France"
[791] "Chatou, Ile-de-France, France"
[792] "Saint-Denis-en-Val, Centre-Val de Loire, France"
[793] "Artemare, Auvergne-Rhône-Alpes, France"
[794] "Saint-Remy-de-Provence, Provence-Alpes-Côte d'Azur, France"
[795] "Épinay-sur-Seine, Ile-de-France, France"
[796] "Malaga, Andalusia, Spain"
[797] "Colmar, Grand Est, France"
[798] "Belfort, Bourgogne-Franche-Comte, France"
[799] "Colmar, Alsace, France"
[800] "Viry-Chatillon, Ile-de-France, France"
[801] "Étrechy, Ile-de-France, France"
[802] "Kuala Lumpur, Federal Territory of Kuala Lumpur, Malaysia"
[803] "Alfortville, Ile-de-France, France"
[804] "Concarneau, Brittany, France"
[805] "Boa Vista, Sao Paulo, Brazil"
[806] "Chambery, Rhone-Alpes, France"
[807] "Suresnes, Ile-de-France, France"
[808] "Czechia"
[809] "Les Sables-d'Olonne, Pays de la Loire, France"
[810] "Wavrin, Nord-Pas-de-Calais, France"
[811] "Quimper, Bretagne, France"
[812] "Les Loges-en-Josas, Ile-de-France, France"
[813] "Netherlands"
[814] "Bouchain, Nord-Pas-de-Calais, France"
[815] "Nancy, Lorraine, France"
[816] "South Brisbane, Queensland, Australia"
[817] "La Courneuve, Ile-de-France, France"
[818] "Toulon, Provence-Alpes-Côte d'Azur, France"
[819] "Cambridge, England, United Kingdom"
[820] "Waverton, New South Wales, Australia"
[821] "Lleida, Catalonia, Spain"
[822] "Strasbourg, Grand Est, France"
[823] "Saint-Julien-en-Genevois, Rhone-Alpes, France"
[824] "Montrouge, Ile-de-France, France"
[825] "Vero Beach, Florida, United States"
[826] "Jouy-en-Josas, Ile-de-France, France"
[827] "Reims, France"
[828] "Lagraulière, Aquitaine Limousin Poitou-Charentes, France"
[829] "Paulhan, Occitanie, France"
[830] "Le Coudray-Montceaux, Ile-de-France, France"
[831] "Saint-Jean-d'Illac, Aquitaine, France"
[832] "Creteil, Ile-de-France, France"
[833] "Rennes, France"
[834] "Soisy-sur-Seine, Ile-de-France, France"
[835] "Grenoble, Auvergne-Rhône-Alpes, France"
[836] "Hillarys, Western Australia, Australia"
[837] "Whale Beach, New South Wales, Australia"
[838] "Cottesloe, Western Australia, Australia"
[839] "Cardiff, Wales, United Kingdom"
[840] "Besancon, Bourgogne-Franche-Comte, France"
[841] "Irving, Texas, United States"
[842] "Montigny-lès-Metz, Alsace-Champagne-Ardenne-Lorraine, France"
[843] "Saint-Christophe, Aquitaine-Limousin-Poitou-Charentes, France"
[844] "Frederiksberg, Capital Region of Denmark, Denmark"
[845] "Hanoi, Hanoi, Vietnam"
[846] "CR"
[847] "Ho Chi Minh City, Ho Chi Minh City, Vietnam"
[848] "Nakhon Ratchasima, Thailand"
[849] "Bondi Junction, New South Wales, Australia"
[850] "Vitre, Brittany, France"
[851] "Charenton-le-Pont, Ile-de-France, France"
[852] "Thionville, Lorraine, France"
[853] "Orleans, Centre, France"
[854] "Le Plessis-Belleville, Picardy, France"
[855] "La Marsa, Tunis, Tunisia"
[856] "Gedangan, East Java, Indonesia"
[857] "Amman, Amman, Jordan"
[858] "Saint-Remy-l'Honore, Ile-de-France, France"
[859] "Caceres‎, Extremadura, Spain"
[860] "Serbannes, Auvergne-Rhône-Alpes, France"
[861] "Nancy, Alsace-Champagne-Ardenne-Lorraine, France"
[862] "Saint-Prix, Ile-de-France, France"
[863] "Arles, Provence-Alpes-Côte d'Azur, France"
[864] "Saint-Brieuc, Brittany, France"
[865] "Bretigny-sur-Orge, Ile-de-France, France"
[866] "Nimes, Languedoc-Roussillon Midi-Pyrenees, France"
[867] "Aleria, Corsica, France"
[868] "Saint-Prix, Val-d'Oise, Ile-de-France, France"
[869] "Cheongju-si, Chungcheongbuk-do, South Korea"
[870] "Meyzieu, Auvergne-Rhône-Alpes, France"
[871] "34/7 Soi Lertbuya Rajthevee BKK10400 Thailand"
[872] "Belfast, Northern Ireland, United Kingdom"
[873] "Ancona, Marche, Italy"
[874] "Villefontaine, Auvergne-Rhône-Alpes, France"
[875] "Cork, Cork, Ireland"
[876] "Vaucresson, Ile-de-France, France"
[877] "IN"
[878] "Oslo, Oslo, Norway"
[879] "Paramus, New Jersey, United States"
[880] "Arizona, United States"
[881] "Ibhayi, Eastern Cape, South Africa"
[882] "Opatija, Primorje-Gorski Kotar County, Croatia"
[883] "State of Santa Catarina, Brazil"
[884] "Collaroy, New South Wales, Australia"
[885] "Mascot, New South Wales, Australia"
[886] "Dulwich Hill, New South Wales, Australia"
[887] "Eastwood, New South Wales, Australia"
[888] "Glen Waverley, Victoria, Australia"
[889] "Saint Peters, New South Wales, Australia"
[890] "Scarborough, Western Australia, Australia"
[891] "Epping, New South Wales, Australia"
[892] "Tilburg, North Brabant, Netherlands"
[893] "MuÄŸla Province, Turkey"
[894] "Kourou, Arrondissement of Cayenne, French Guiana"
[895] "Wallkill, New York, United States"
[896] "Winnipeg, Manitoba, Canada"
[897] "Lane Cove North, New South Wales, Australia"
[898] "Jardim da Gloria, State of Sao Paulo, Brazil"
[899] "Moreno Valley, California, United States"
[900] "Lilyfield, New South Wales, Australia"
[901] "Campsie, New South Wales, Australia"
[902] "Cuzco, Cusco, Peru"
[903] "Maplewood, New Jersey, United States"
[904] "North Willoughby, New South Wales, Australia"
[905] "Cairo, Cairo Governorate, Egypt"
[906] "La Massimina-Casal Lumbroso, Lazio, Italy"
[907] "Terni, Umbria, Italy"
[908] "Twickenham, England, United Kingdom"
[909] "Newton, Massachusetts, United States"
[910] "Poligny, Bourgogne-Franche-Comte, France"
[911] "Pound Ridge, New York, United States"
[912] "Hermanus, Western Cape, South Africa"
[913] "Brookvale, New South Wales, Australia"
[914] "Tucson, Arizona, United States"
[915] "Paris, New York, United States"
[916] "Bourbriac, Brittany, France"
[917] "Villefranche-sur-Mer, Provence-Alpes-Côte d'Azur, France"
[918] "Zug, Canton of Zug, Switzerland"
[919] "Palma, Balearic Islands, Spain"
[920] "Santiago, Santiago Metropolitan Region, Chile"
[921] "Darwin, Northern Territory, Australia"
[922] "Zagarolo, Lazio, Italy"
[923] "Konstanz, Baden-Württemberg, Germany"
[924] "Friedrichshafen, Baden-Württemberg, Germany"
[925] "State of Mato Grosso, Brazil"
[926] "Port Stephens, New South Wales, Australia"
[927] "La Merlatière, Pays de la Loire, France"
[928] "Cary, North Carolina, United States"
[929] "Salt Lake City, Utah, United States"
[930] "Nashville, Tennessee, United States"
[931] "Huntington, New York, United States"
[932] "Kirrawee, New South Wales, Australia"
[933] "Truckee, California, United States"
[934] "Izmir, Ä°zmir, Turkey"
[935] "Minsk, Minsk Region, Belarus"
[936] "Adainville, Ile-de-France, France"
[937] "Puteaux, Ile-de-France, France"
[938] "Moema, Sao Paulo, Brazil"
[939] "Queens Park, New South Wales, Australia"
[940] "Burwood, New South Wales, Australia"
[941] "Coral Springs, Florida, United States"
[942] "Rye, New York, United States"
[943] "Portland, Oregon, United States"
[944] "Fairfield, Connecticut, United States"
[945] "Clarkston, Michigan, United States"
[946] "Limerick, Limerick, Ireland"
[947] "Lincoln Park, New Jersey, United States"
[948] "Alexandria, Virginia, United States"
[949] "New York, United States"
[950] "Vila Velha, State of EspÃrito Santo, Brazil"
[951] "Tel Aviv, Israel ,Milan Italy"
[952] "Brûlain, Nouvelle-Aquitaine, France"
[953] "Inga, Rio de Janeiro, Brazil"
[954] "Sao Mateus, Minas Gerais, Brazil"
[955] "Barrington, Illinois, United States"
[956] "Manly Vale, New South Wales, Australia"
[957] "Sofia, Sofia City Province, Bulgaria"
[958] "Vilnius, Vilnius County, Lithuania"
[959] "Villeurbanne, Rhone-Alpes, France"
[960] "Mulhouse, Alsace, France"
[961] "Cesena, Emilia-Romagna, Italy"
[962] "Lausanne, Vaud, Switzerland"
[963] "Le Bourget, Ile-de-France, France"
[964] "South Africa"
[965] "Andover, England, United Kingdom"
[966] "Ankara, Ankara, Turkey"
[967] "Dorsten, North Rhine-Westphalia, Germany"
[968] "Saint-Gilles, Brussels, Belgium"
[969] "Vargem Pequena, State of Rio de Janeiro, Brazil"
[970] "Teresopolis, Rio de Janeiro, Brazil"
[971] "Üsküdar, Istanbul, Turkey"
[972] "Bodrum, MuÄŸla Province, Turkey"
[973] "Luxembourg, Luxembourg District, Luxembourg"
[974] "Nova Friburgo, Rio de Janeiro, Brazil"
[975] "Botafogo, State of Rio de Janeiro, Brazil"
[976] "PT"
[977] "State of Sao Paulo, Brazil"
[978] "Todos os Santos, State of Rio de Janeiro, Brazil"
[979] "Gurley, Alabama, United States"
[980] "Shoham"
[981] "Curitiba, State of Parana, Brazil"
[982] "Chermside West, Queensland, Australia"
[983] "Cremorne Point, New South Wales, Australia"
[984] "Ä°zmit, Kocaeli, Turkey"
[985] "Ixelles, Brussels, Belgium"
[986] "Bari, Apulia, Italy"
[987] "Fiumicino, Lazio, Italy"
[988] "Venice, Veneto, Italy"
[989] "Avare, Sao Paulo, Brazil"
[990] "Cuiaba, Mato Grosso, Brazil"
[991] "Lytham St Annes, Lancashire"
[992] "Glebe, New South Wales, Australia"
[993] "Gökova, Mugla, Turkey"
[994] "Saudi Arabia"
[995] "Istanbul/Türkiye"
[996] "Phnom Penh, Phnom Penh, Cambodia"
[997] "Woollahra, New South Wales, Australia"
[998] "Winmalee, New South Wales, Australia"
[999] "Paşaköy Köyü, Istanbul, Turkey"
[1000] "Taza, Fez-Meknès, Morocco"
[ reached getOption("max.print") -- omitted 6151 entries ]#we notice it is extremely unstructured data. some hosts enter paragraphs instead of their actual location. we will also drop this columndf <- df |>
select(-host_location)# Check for duplicates and remove them
df <- df[!duplicated(df), ]# the dataset is too large for our purposes so we need to select one city to work with.
df$city |> table()
Bangkok Cape Town Hong Kong Istanbul Mexico City New York Paris
19361 19086 7087 24519 20065 37012 64690
Rio de Janeiro Rome Sydney
26615 27647 33630 # we will go with new york since it still contains a lot of data, without exceeding 50000 rows
df <- df |>
filter(city == 'New York')#since we are only working on data from new york now, the column of the city is now useless to us
df <- df |>
select(-city)#we check the dimensions of our new dataframe
df |> dim()[1] 37012 29# the host_since column is mostly filled with null values. we will dismiss it
df <- df |>
select(-host_since)
# we are checking the distribution of reponse rate scores, and we perform some basic statistics
#we notice
df$host_response_rate |> table()
0 0.04 0.05 0.08 0.09 0.1 0.11 0.12 0.13 0.14 0.17 0.2 0.22 0.23 0.25 0.27 0.29 0.3 0.31
930 1 1 7 1 36 9 1 5 6 15 35 1 11 32 6 8 26 10
0.33 0.36 0.38 0.4 0.43 0.44 0.45 0.46 0.5 0.51 0.52 0.53 0.54 0.55 0.56 0.57 0.58 0.59 0.6
93 1 17 59 26 5 1 9 341 4 4 5 11 1 12 28 6 15 143
0.61 0.62 0.63 0.64 0.65 0.67 0.68 0.69 0.7 0.71 0.72 0.73 0.74 0.75 0.76 0.77 0.78 0.79 0.8
4 11 146 10 4 216 12 4 121 47 1 50 3 158 5 7 35 26 509
0.81 0.82 0.83 0.84 0.85 0.86 0.87 0.88 0.89 0.9 0.91 0.92 0.93 0.94 0.95 0.96 0.97 0.98 0.99
15 24 129 18 39 101 86 149 136 774 90 139 224 265 344 374 98 150 190
1
11869 df$host_response_rate |> summary() Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
0.000 0.900 1.000 0.885 1.000 1.000 18507 df |> colnames() [1] "listing_id" "name" "host_id"
[4] "host_response_time" "host_response_rate" "host_acceptance_rate"
[7] "host_is_superhost" "host_total_listings_count" "host_has_profile_pic"
[10] "host_identity_verified" "neighbourhood" "district"
[13] "property_type" "room_type" "accommodates"
[16] "bedrooms" "amenities" "price"
[19] "minimum_nights" "maximum_nights" "review_scores_rating"
[22] "review_scores_accuracy" "review_scores_cleanliness" "review_scores_checkin"
[25] "review_scores_communication" "review_scores_location" "review_scores_value"
[28] "instant_bookable" sapply(df, class) listing_id name host_id host_response_time
"numeric" "character" "numeric" "character"
host_response_rate host_acceptance_rate host_is_superhost host_total_listings_count
"numeric" "numeric" "logical" "numeric"
host_has_profile_pic host_identity_verified neighbourhood district
"logical" "logical" "character" "character"
property_type room_type accommodates bedrooms
"character" "character" "numeric" "numeric"
amenities price minimum_nights maximum_nights
"character" "numeric" "numeric" "numeric"
review_scores_rating review_scores_accuracy review_scores_cleanliness review_scores_checkin
"numeric" "numeric" "numeric" "numeric"
review_scores_communication review_scores_location review_scores_value instant_bookable
"numeric" "numeric" "numeric" "logical" # we will now cast the room_type column as a factor. it has 4 possibilites and is currently classified as character.
df$room_type <- as.factor(df$room_type)
df$room_type |> levels()[1] "Entire place" "Hotel room" "Private room" "Shared room" #we will inspect the property_type column to see how many unique values exist. if there are less than 20, we could also cast it as categorical / factor.
df$property_type |> unique() [1] "Entire apartment" "Private room in apartment" "Entire condominium"
[4] "Entire house" "Private room in townhouse" "Entire loft"
[7] "Entire townhouse" "Entire place" "Private room in house"
[10] "Entire serviced apartment" "Entire bungalow" "Entire guest suite"
[13] "Private room in guest suite" "Entire guesthouse" "Room in serviced apartment"
[16] "Room in hotel" "Room in boutique hotel" "Private room in loft"
[19] "Entire cottage" "Private room in guesthouse" "Private room in serviced apartment"
[22] "Room in bed and breakfast" "Room in aparthotel" "Private room in resort"
[25] "Private room in condominium" "Houseboat" "Private room in tiny house"
[28] "Tiny house" "Entire floor" "Private room in bed and breakfast"
[31] "Entire home/apt" "Boat" "Private room"
[34] "Private room in camper/rv" "Shared room in apartment" "Private room in barn"
[37] "Camper/RV" "Shared room in guest suite" "Shared room in loft"
[40] "Shared room in house" "Shared room in hostel" "Private room in tent"
[43] "Shared room in serviced apartment" "Private room in villa" "Private room in bungalow"
[46] "Private room in hostel" "Private room in dome house" "Private room in casa particular"
[49] "Shared room in condominium" "Private room in earth house" "Shared room in townhouse"
[52] "Private room in castle" "Shared room in floor" "Shared room in bungalow"
[55] "Cave" "Private room in in-law" "Private room in farm stay"
[58] "Private room in lighthouse" "Private room in cabin" "Shared room in bed and breakfast"
[61] "Entire villa" "Shared room in guesthouse" "Bus"
[64] "Shared room in island" "Private room in cottage" "Entire resort"
[67] "Shared room in earth house" "Barn" "Private room in dorm"
[70] "Room in resort" "Private room in floor" "Private room in train"
[73] "Lighthouse" "Entire bed and breakfast" "Room in hostel" #we notice a lot of repetiotion in the rows: private room in... ; entire... ; shared room in ...
#we already knwo this information from the column room type. we can reduce the number of unique values and hence transform this column into a categorical.df$property_type <- lapply(df$property_type, function(x) gsub("Entire ", "", x))
df$property_type <- lapply(df$property_type, function(x) gsub("Private room in ", "", x))
df$property_type <- lapply(df$property_type, function(x) gsub("Room in ", "", x))
df$property_type <- lapply(df$property_type, function(x) gsub("Shared room in ", "", x))df$property_type |> unique()[[1]]
[1] "apartment"
[[2]]
[1] "condominium"
[[3]]
[1] "house"
[[4]]
[1] "townhouse"
[[5]]
[1] "loft"
[[6]]
[1] "place"
[[7]]
[1] "serviced apartment"
[[8]]
[1] "bungalow"
[[9]]
[1] "guest suite"
[[10]]
[1] "guesthouse"
[[11]]
[1] "hotel"
[[12]]
[1] "boutique hotel"
[[13]]
[1] "cottage"
[[14]]
[1] "bed and breakfast"
[[15]]
[1] "aparthotel"
[[16]]
[1] "resort"
[[17]]
[1] "Houseboat"
[[18]]
[1] "tiny house"
[[19]]
[1] "Tiny house"
[[20]]
[1] "floor"
[[21]]
[1] "home/apt"
[[22]]
[1] "Boat"
[[23]]
[1] "Private room"
[[24]]
[1] "camper/rv"
[[25]]
[1] "barn"
[[26]]
[1] "Camper/RV"
[[27]]
[1] "hostel"
[[28]]
[1] "tent"
[[29]]
[1] "villa"
[[30]]
[1] "dome house"
[[31]]
[1] "casa particular"
[[32]]
[1] "earth house"
[[33]]
[1] "castle"
[[34]]
[1] "Cave"
[[35]]
[1] "in-law"
[[36]]
[1] "farm stay"
[[37]]
[1] "lighthouse"
[[38]]
[1] "cabin"
[[39]]
[1] "Bus"
[[40]]
[1] "island"
[[41]]
[1] "Barn"
[[42]]
[1] "dorm"
[[43]]
[1] "train"
[[44]]
[1] "Lighthouse"df$property_type <- as.character(lapply(df$property_type, function(x) sub("^([a-z])", "\\U\\1", x, perl = TRUE)))
df$property_type <- as.character(lapply(df$property_type, function(x) sub("^([a-z])", "\\U\\1", x, perl = TRUE)))
df$property_type |> unique()
[1] "Apartment" "Condominium" "House" "Townhouse" "Loft"
[6] "Place" "Serviced apartment" "Bungalow" "Guest suite" "Guesthouse"
[11] "Hotel" "Boutique hotel" "Cottage" "Bed and breakfast" "Aparthotel"
[16] "Resort" "Houseboat" "Tiny house" "Floor" "Home/apt"
[21] "Boat" "Private room" "Camper/rv" "Barn" "Camper/RV"
[26] "Hostel" "Tent" "Villa" "Dome house" "Casa particular"
[31] "Earth house" "Castle" "Cave" "In-law" "Farm stay"
[36] "Lighthouse" "Cabin" "Bus" "Island" "Dorm"
[41] "Train" df |> colnames()
[1] "listing_id" "name" "host_id"
[4] "host_response_time" "host_response_rate" "host_acceptance_rate"
[7] "host_is_superhost" "host_total_listings_count" "host_has_profile_pic"
[10] "host_identity_verified" "neighbourhood" "district"
[13] "property_type" "room_type" "accommodates"
[16] "bedrooms" "amenities" "price"
[19] "minimum_nights" "maximum_nights" "review_scores_rating"
[22] "review_scores_accuracy" "review_scores_cleanliness" "review_scores_checkin"
[25] "review_scores_communication" "review_scores_location" "review_scores_value"
[28] "instant_bookable" ```{r}
Error: attempt to use zero-length variable namedf |> summary()
listing_id name host_id host_response_time host_response_rate host_acceptance_rate
Min. : 2595 Length:37012 Min. : 2438 Length:37012 Min. :0.000 Min. :0.000
1st Qu.:11033346 Class :character 1st Qu.: 9643914 Class :character 1st Qu.:0.900 1st Qu.:0.730
Median :24854480 Mode :character Median : 40236486 Mode :character Median :1.000 Median :0.940
Mean :25105891 Mean : 93709486 Mean :0.885 Mean :0.805
3rd Qu.:39821927 3rd Qu.:152968334 3rd Qu.:1.000 3rd Qu.:1.000
Max. :48039776 Max. :387071756 Max. :1.000 Max. :1.000
NA's :18507 NA's :14633
host_is_superhost host_total_listings_count host_has_profile_pic host_identity_verified neighbourhood
Mode :logical Min. : 0.00 Mode :logical Mode :logical Length:37012
FALSE:30023 1st Qu.: 1.00 FALSE:112 FALSE:7404 Class :character
TRUE :6971 Median : 1.00 TRUE :36882 TRUE :29590 Mode :character
NA's :18 Mean : 23.97 NA's :18 NA's :18
3rd Qu.: 2.00
Max. :2739.00
NA's :18
district property_type room_type accommodates bedrooms amenities
Length:37012 Length:37012 Entire place:19397 Min. : 0.000 Min. : 1.000 Length:37012
Class :character Class :character Hotel room : 299 1st Qu.: 2.000 1st Qu.: 1.000 Class :character
Mode :character Mode :character Private room:16630 Median : 2.000 Median : 1.000 Mode :character
Shared room : 686 Mean : 2.798 Mean : 1.316
3rd Qu.: 4.000 3rd Qu.: 1.000
Max. :16.000 Max. :21.000
NA's :3608
price minimum_nights maximum_nights review_scores_rating review_scores_accuracy
Min. : 0.0 Min. : 1.00 Min. :1.000e+00 Min. : 20.00 Min. : 2.000
1st Qu.: 60.0 1st Qu.: 4.00 1st Qu.:9.000e+01 1st Qu.: 92.00 1st Qu.: 9.000
Median : 99.0 Median : 30.00 Median :1.125e+03 Median : 97.00 Median :10.000
Mean : 142.8 Mean : 23.32 Mean :5.980e+04 Mean : 93.77 Mean : 9.587
3rd Qu.: 151.0 3rd Qu.: 30.00 3rd Qu.:1.125e+03 3rd Qu.:100.00 3rd Qu.:10.000
Max. :10000.0 Max. :1250.00 Max. :2.147e+09 Max. :100.00 Max. :10.000
NA's :10235 NA's :10259
review_scores_cleanliness review_scores_checkin review_scores_communication review_scores_location
Min. : 2.000 Min. : 2.000 Min. : 2.000 Min. : 2.0
1st Qu.: 9.000 1st Qu.:10.000 1st Qu.:10.000 1st Qu.: 9.0
Median :10.000 Median :10.000 Median :10.000 Median :10.0
Mean : 9.268 Mean : 9.721 Mean : 9.713 Mean : 9.6
3rd Qu.:10.000 3rd Qu.:10.000 3rd Qu.:10.000 3rd Qu.:10.0
Max. :10.000 Max. :10.000 Max. :10.000 Max. :10.0
NA's :10248 NA's :10271 NA's :10257 NA's :10272
review_scores_value instant_bookable
Min. : 2.000 Mode :logical
1st Qu.: 9.000 FALSE:25972
Median :10.000 TRUE :11040
Mean : 9.368
3rd Qu.:10.000
Max. :10.000
NA's :10272