nyclodging
nyclogding contains shiny application and documentation for analyzing
Airbnb listings in New York City in 2019. It includes:
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housing price prediction using text data with tidymodels
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spatial analysis and visualization with sf and tmap
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various user-defined statistical visualization
Example dataset:
nyclodging::listings
#> # A tibble: 48,895 × 15
#> list_id list_description host_id host_name neighbourhood_g… neighbourhood
#> <dbl> <chr> <dbl> <chr> <chr> <chr>
#> 1 2539 Clean & quiet apt h… 2787 John Brooklyn Kensington
#> 2 2595 Skylit Midtown Cast… 2845 Jennifer Manhattan Midtown
#> 3 3647 THE VILLAGE OF HARL… 4632 Elisabeth Manhattan Harlem
#> 4 3831 Cozy Entire Floor o… 4869 LisaRoxa… Brooklyn Clinton Hill
#> 5 5022 Entire Apt: Spaciou… 7192 Laura Manhattan East Harlem
#> 6 5099 Large Cozy 1 BR Apa… 7322 Chris Manhattan Murray Hill
#> 7 5121 BlissArtsSpace! 7356 Garon Brooklyn Bedford-Stuy…
#> 8 5178 Large Furnished Roo… 8967 Shunichi Manhattan Hell's Kitch…
#> 9 5203 Cozy Clean Guest Ro… 7490 MaryEllen Manhattan Upper West S…
#> 10 5238 Cute & Cozy Lower E… 7549 Ben Manhattan Chinatown
#> # … with 48,885 more rows, and 9 more variables: lat <dbl>, lon <dbl>,
#> # room_type <chr>, price <dbl>, min_nights <dbl>, reviews <dbl>,
#> # last_review_date <date>, reviews_per_month <dbl>, available_days <dbl>Shiny app: https://qiushiyan.shinyapps.io/nyclodging/
Package documentation: https://qiushiyan.github.io/nyclodging
Installation
You can install the development version of nyclodging like so:
remotes::install_github("qiushiyan/nyclodging")Usage
To start the shiny app locally
library(nyclodging)
run_app()Or if you prefer using docker
docker pull qiushiyan/nyclodging
docker run -p 8080:80 --rm qiushiyan/nyclodging
and then navigate to http://localhost:8080/
Source
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Inside Airbnb public data http://insideairbnb.com/
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Kaggle Dataset https://www.kaggle.com/dgomonov/new-york-city-airbnb-open-data