data_raw
## # A tibble: 48,895 × 16
##       id name          host_id host_name neighbourhood_g… neighbourhood latitude
##    <dbl> <chr>           <dbl> <chr>     <chr>            <chr>            <dbl>
##  1  2539 clean & quie…    2787 john      brooklyn         kensington        40.6
##  2  2595 skylit midto…    2845 jennifer  manhattan        midtown           40.8
##  3  3647 the village …    4632 elisabeth manhattan        harlem            40.8
##  4  3831 cozy entire …    4869 lisaroxa… brooklyn         clinton hill      40.7
##  5  5022 entire apt: …    7192 laura     manhattan        east harlem       40.8
##  6  5099 large cozy 1…    7322 chris     manhattan        murray hill       40.7
##  7  5121 blissartsspa…    7356 garon     brooklyn         bedford-stuy…     40.7
##  8  5178 large furnis…    8967 shunichi  manhattan        hell's kitch…     40.8
##  9  5203 cozy clean g…    7490 maryellen manhattan        upper west s…     40.8
## 10  5238 cute & cozy …    7549 ben       manhattan        chinatown         40.7
## # … with 48,885 more rows, and 9 more variables: longitude <dbl>,
## #   room_type <chr>, price <dbl>, minimum_nights <dbl>,
## #   number_of_reviews <dbl>, last_review <date>, reviews_per_month <dbl>,
## #   calculated_host_listings_count <dbl>, availability_365 <dbl>

Our Data

Airbnb Data from Kaggle
id name host_id host_name neighbourhood_group neighbourhood latitude longitude room_type price minimum_nights number_of_reviews last_review reviews_per_month calculated_host_listings_count availability_365
2539 clean & quiet apt home by the park 2787 john brooklyn kensington 40.64749 -73.97237 private room 149 1 9 2018-10-19 0.21 6 365
2595 skylit midtown castle 2845 jennifer manhattan midtown 40.75362 -73.98377 entire home/apt 225 1 45 2019-05-21 0.38 2 355
3647 the village of harlem….new york ! 4632 elisabeth manhattan harlem 40.80902 -73.94190 private room 150 3 0 NA NA 1 365
3831 cozy entire floor of brownstone 4869 lisaroxanne brooklyn clinton hill 40.68514 -73.95976 entire home/apt 89 1 270 2019-07-05 4.64 1 194
5022 entire apt: spacious studio/loft by central park 7192 laura manhattan east harlem 40.79851 -73.94399 entire home/apt 80 10 9 2018-11-19 0.10 1 0

Visualizations

1.1 - Average Price of each Neighborhood Group

1.2 - Average Minimum Number of Nights for each Neighborhood Group

1.3 - Relationship Between Price and Minimum Nights

## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## Warning: Removed 13 rows containing non-finite values (stat_smooth).
## Warning: Removed 13 rows containing missing values (geom_point).

1.4 - Average Price for Each Room Type

1.5 - Number of Room Types per Neighborhood

1.6 - Comparison of Mean Price of each Neighborhood Group according to Type of The Room

1.7 - Number of Reviews Across all Neighborhood Groups

1.9 - Interactive Leaflet Map

# create leaflet map
# each marker has a specific color depending on its room type
data_raw$room_type <- factor(data_raw$room_type)

new <- c("red", "green","blue")[data_raw$room_type]

icons <- awesomeIcons(
  icon = 'ios-close',
  iconColor = 'black',
  library = 'ion',
  markerColor = new
)

airbnb_map <- leaflet(data_raw) %>%
  addProviderTiles("CartoDB.Positron") %>%
  addAwesomeMarkers(
    clusterOptions = markerClusterOptions(),
    icon = icons,
    lng = ~longitude, 
    lat = ~latitude,
    label = ~paste(name),
    popup = ~paste(name,"|", 
                            "Type Room :", room_type,"|",
                            "Min Nights :", minimum_nights, "|",
                            "Price :", price)
  )

airbnb_map