plotly

Setup

Loading the data

library(tidyverse)

## ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.1 ──

## ✓ ggplot2 3.3.4     ✓ purrr   0.3.4
## ✓ tibble  3.1.2     ✓ dplyr   1.0.7
## ✓ tidyr   1.1.3     ✓ stringr 1.4.0
## ✓ readr   1.4.0     ✓ forcats 0.5.1

## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## x dplyr::filter() masks stats::filter()
## x dplyr::lag()    masks stats::lag()

library(p8105.datasets)
library(plotly)

## 
## Attaching package: 'plotly'

## The following object is masked from 'package:ggplot2':
## 
##     last_plot

## The following object is masked from 'package:stats':
## 
##     filter

## The following object is masked from 'package:graphics':
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##     layout

library(leaflet)

data("nyc_airbnb")

nyc_airbnb_1 =
  nyc_airbnb %>% 
    mutate(rating = review_scores_location / 2) %>% 
    select(neighbourhood_group, neighbourhood, rating, price, room_type, lat, long) %>% 
  filter(neighbourhood_group == "Manhattan",
         price %in% 100:500,
         room_type == "Entire home/apt") %>% 
  drop_na(rating)

Plotly plots

Scatterplot

puts stuff on the next line str_c has created a new variable with those columns

Plotly works and looks like ggplot that requires the aesthetics to work.

nyc_airbnb_1 %>% 
  mutate(
    text_label = str_c("Price: $", price, "\nRating: ", rating)) %>% 
  plot_ly(x = ~lat, y = ~long, color = ~price, text = ~text_label, alpha = 0.5, type = "scatter", mode = "markers")

Boxplot

nyc_airbnb_1 %>% 
  mutate(neighbourhood = fct_reorder(neighbourhood, price)) %>% 
  plot_ly(y = ~price, x = ~neighbourhood, color = ~neighbourhood,
          type = "box", colors = "viridis")

Barplot

nyc_airbnb_1 %>% 
  count(neighbourhood) %>% 
  mutate(
    neighbourhood = fct_reorder(neighbourhood, n)) %>% 
  plot_ly(x = ~neighbourhood, y = ~n, color = ~neighbourhood, type = "bar", colors = "viridis")

ggplotly

ggp_scatter =
  nyc_airbnb_1 %>% 
  ggplot(aes(x = lat, y = long, color = price)) + 
  geom_point()

ggplotly(ggp_scatter)

Boxplots

fct_reorder considers two variables and organizes the data in those two variables.

Boxplots

nyc_airbnb_1 %>% 
  filter(
    price <1000,
    neighbourhood_group == "Manhattan") %>% 
  mutate(
    neighbourhood = fct_reorder(neighbourhood, price)) %>%
  ggplot(aes(x = neighbourhood, y = price)) +
  geom_boxplot() +
  coord_flip()

Map

All of NYC

nyc_airbnb_2 =
  nyc_airbnb %>% 
    mutate(rating = review_scores_location / 2) %>% 
    select(neighbourhood_group, neighbourhood, rating, price, room_type, lat, long) %>% 
  filter(price %in% 100:500,
         room_type == "Entire home/apt") %>% 
  drop_na(rating) 

Generate Leaflet map by Rating

pal = colorNumeric("magma", nyc_airbnb_2 %>% pull(rating))

nyc_airbnb_2 %>% 
  leaflet() %>% 
  addProviderTiles(providers$CartoDB.Positron) %>% 
  addCircleMarkers(~lat, ~long, radius = 0.5, color = ~pal(rating))