R Notebook

install.packages(c(tidyverse, sf, tmap, spatstat, maptools, ggplot2, sqldf)) install.packages(“spatstat.geom”, dependencies = TRUE) install.packages(“leaflet.providers”) install.packages(“markdown”, dependencies = TRUE) install.packages(“polyclip”, dependencies = TRUE) install.packages(“ggmap”, dependencies = TRUE)

rdf %>% 
  mutate(birth.year = as.numeric('birth.year')) %>% #THIS CHANGES A STRING INTO A NUMBER
  dplyr::select(-c('birth.year'))  %>%    #THIS DELETES THE OLD COLUMN 
  arrange(birth.year) #THIS SORTS ON BIRTH YEAR

Warning: Problem with `mutate()` column `birth.year`.
ℹ `birth.year = as.numeric("birth.year")`.
ℹ NAs introduced by coercion
Error: arrange() failed at implicit mutate() step. 
* Problem with `mutate()` column `..1`.
ℹ `..1 = birth.year`.
x object 'birth.year' not found
Run `rlang::last_error()` to see where the error occurred.

# Turns it into a gis file
morningStationsGeo <- st_as_sf(morningStations, coords = c("lon", "lat"), dim = "XY", crs = 4326) #crs=coordinate reference system

# Save if you feel like it! # st_write(popularStations, "popularStations.shp", delete_layer = TRUE)

# Look at the map 
tmap_mode('view')

tmap mode set to interactive viewing

tm_shape(morningStationsGeo %>% 
           filter(!is.na(morningtrips)) %>% 
           mutate(morningtrips = as.numeric(morningtrips))) + tm_dots(col = "morningtrips", style="quantile", id = "name")

tm_shape(meStationsGeo %>% 
           filter(!is.na(diff)) %>% 
           mutate(diff = as.numeric(diff))) + tm_dots(col="diff", style="quantile", id = "name")

Variable(s) "diff" contains positive and negative values, so midpoint is set to 0. Set midpoint = NA to show the full spectrum of the color palette.

######## PART 4 KERNEL DENSITY  ######### 

## Read SF for a file of boroughs
boroughs <- st_read("borough.shp")

Reading layer `borough' from data source 
  `/Users/chaneumpark/OneDrive - Georgia Institute of Technology/2021-Fall/Urban Analytics/R lab session/Assignment2 CitiBike/borough.shp' 
  using driver `ESRI Shapefile'
Simple feature collection with 5 features and 4 fields
Geometry type: MULTIPOLYGON
Dimension:     XY
Bounding box:  xmin: -74.25559 ymin: 40.49612 xmax: -73.70001 ymax: 40.91553
Geodetic CRS:  WGS84(DD)

boroughs_prj <- st_transform(boroughs, crs = 2263)

# Density map (This method doesn't allow us to see the background map)
df.size.proj <- st_transform(morningStationsGeo, crs = 2263)
p.sp <- as(df.size.proj, "Spatial")
p.ppp <- as(p.sp, "ppp")
kernelDensityMorning <- (density(p.ppp, sigma = 1000))

##Plot the two together
plot(kernelDensityMorning, main="Heat Map of Mornign Citibike Origins")
plot(boroughs_prj$geometry, add=TRUE)

##CHALLENGES FOR YOUR DENSITY MAP
##Extra: Clip the raster and clip the vector as well. (only plot the intersection of the two?) 
##Extra: Make the lines white (hint: it is now a polygon!)
##Extra: Add the top 3 (or 5) points and label them.

######## PART 5 GGPLOT EXAMPLE WITH CONTOURS ######### 

# Heatmap in ggplot
library(ggplot2)
library(ggmap)

df.size.degree <- st_transform(morningStationsGeo, crs = 4326) %>% 
  mutate(lat = st_coordinates(.)[,2],
         lon = st_coordinates(.)[,1])

##Get borders
height <- max(st_coordinates(df.size.degree)[,2]) - min(st_coordinates(df.size.degree)[,2])
width <- max(st_coordinates(df.size.degree)[,1]) - min(st_coordinates(df.size.degree)[,1])
  
sac_borders <- c(bottom = min(st_coordinates(df.size.degree)[,2]) - 0.1*height,
                top = max(st_coordinates(df.size.degree)[,2]) + 0.1*height,
                left = min(st_coordinates(df.size.degree)[,1]) - 0.1*width,
                right = max(st_coordinates(df.size.degree)[,1]) + 0.1*width)

map <- get_stamenmap(sac_borders, zoom = 12, maptype = "toner-lite")

Source : http://tile.stamen.com/toner-lite/12/1205/1538.png
Source : http://tile.stamen.com/toner-lite/12/1206/1538.png
Source : http://tile.stamen.com/toner-lite/12/1205/1539.png
Source : http://tile.stamen.com/toner-lite/12/1206/1539.png
Source : http://tile.stamen.com/toner-lite/12/1205/1540.png
Source : http://tile.stamen.com/toner-lite/12/1206/1540.png
Source : http://tile.stamen.com/toner-lite/12/1205/1541.png
Source : http://tile.stamen.com/toner-lite/12/1206/1541.png

ggmap(map) +
  geom_density2d(data = df.size.degree, aes(x = lon, y = lat), size = 0.3) +
  stat_density2d(data = df.size.degree, aes(x = lon, y = lat, fill = ..level.., alpha = ..level..), 
                 geom = "polygon", bins = 10) + 
  scale_fill_gradient(low = "green", high = "red") +
  scale_alpha(range = c(0, 0.4), guide = FALSE) #Plot +

Warning: It is deprecated to specify `guide = FALSE` to remove a guide. Please use `guide = "none"` instead.

 coord_cartesian(xlim = c(-74.02, -95.7), 
                  ylim = c(29.5, 30.1))

<ggproto object: Class CoordCartesian, Coord, gg>
    aspect: function
    backtransform_range: function
    clip: on
    default: FALSE
    distance: function
    expand: TRUE
    is_free: function
    is_linear: function
    labels: function
    limits: list
    modify_scales: function
    range: function
    render_axis_h: function
    render_axis_v: function
    render_bg: function
    render_fg: function
    setup_data: function
    setup_layout: function
    setup_panel_guides: function
    setup_panel_params: function
    setup_params: function
    train_panel_guides: function
    transform: function
    super:  <ggproto object: Class CoordCartesian, Coord, gg>