mini1

1. The City I selected

: Naperville, IL

1) Getting census api and tract boundary

tract <- suppressMessages(
  get_acs(geography = "tract",
        state = "IL",
        county = c("DuPage County", "Will County"),
        variables = c(hhincome = 'B19019_001'),
        year =2021,
        survey = "acs5",
        geometry = TRUE,
        output = "wide",
        progress = FALSE)
)

# select the city I want to see
naperville <- tigris::places('IL') %>%
  filter(NAME == "Naperville")

##   |                                                                              |                                                                      |   0%  |                                                                              |=                                                                     |   1%  |                                                                              |=                                                                     |   2%  |                                                                              |==                                                                    |   2%  |                                                                              |==                                                                    |   3%  |                                                                              |==                                                                    |   4%  |                                                                              |===                                                                   |   4%  |                                                                              |====                                                                  |   5%  |                                                                              |====                                                                  |   6%  |                                                                              |=====                                                                 |   8%  |                                                                              |======                                                                |   9%  |                                                                              |=======                                                               |  10%  |                                                                              |========                                                              |  11%  |                                                                              |========                                                              |  12%  |                                                                              |=========                                                             |  12%  |                                                                              |=========                                                             |  13%  |                                                                              |==========                                                            |  14%  |                                                                              |==========                                                            |  15%  |                                                                              |===========                                                           |  15%  |                                                                              |===========                                                           |  16%  |                                                                              |============                                                          |  17%  |                                                                              |============                                                          |  18%  |                                                                              |=============                                                         |  18%  |                                                                              |=============                                                         |  19%  |                                                                              |==============                                                        |  19%  |                                                                              |==============                                                        |  20%  |                                                                              |===============                                                       |  21%  |                                                                              |===============                                                       |  22%  |                                                                              |================                                                      |  22%  |                                                                              |================                                                      |  23%  |                                                                              |=================                                                     |  24%  |                                                                              |=================                                                     |  25%  |                                                                              |==================                                                    |  25%  |                                                                              |==================                                                    |  26%  |                                                                              |===================                                                   |  27%  |                                                                              |===================                                                   |  28%  |                                                                              |====================                                                  |  28%  |                                                                              |====================                                                  |  29%  |                                                                              |=====================                                                 |  29%  |                                                                              |=====================                                                 |  30%  |                                                                              |=====================                                                 |  31%  |                                                                              |======================                                                |  31%  |                                                                              |======================                                                |  32%  |                                                                              |=======================                                               |  32%  |                                                                              |=======================                                               |  33%  |                                                                              |========================                                              |  34%  |                                                                              |========================                                              |  35%  |                                                                              |=========================                                             |  35%  |                                                                              |=========================                                             |  36%  |                                                                              |==========================                                            |  37%  |                                                                              |==========================                                            |  38%  |                                                                              |===========================                                           |  38%  |                                                                              |===========================                                           |  39%  |                                                                              |============================                                          |  39%  |                                                                              |============================                                          |  40%  |                                                                              |============================                                          |  41%  |                                                                              |=============================                                         |  41%  |                                                                              |=============================                                         |  42%  |                                                                              |==============================                                        |  42%  |                                                                              |==============================                                        |  43%  |                                                                              |===============================                                       |  44%  |                                                                              |===============================                                       |  45%  |                                                                              |================================                                      |  45%  |                                                                              |================================                                      |  46%  |                                                                              |=================================                                     |  47%  |                                                                              |=================================                                     |  48%  |                                                                              |==================================                                    |  48%  |                                                                              |==================================                                    |  49%  |                                                                              |===================================                                   |  50%  |                                                                              |===================================                                   |  51%  |                                                                              |====================================                                  |  51%  |                                                                              |====================================                                  |  52%  |                                                                              |=====================================                                 |  53%  |                                                                              |=======================================                               |  55%  |                                                                              |=======================================                               |  56%  |                                                                              |========================================                              |  57%  |                                                                              |========================================                              |  58%  |                                                                              |=========================================                             |  58%  |                                                                              |=========================================                             |  59%  |                                                                              |==========================================                            |  59%  |                                                                              |==========================================                            |  60%  |                                                                              |==========================================                            |  61%  |                                                                              |===========================================                           |  61%  |                                                                              |===========================================                           |  62%  |                                                                              |============================================                          |  62%  |                                                                              |============================================                          |  63%  |                                                                              |============================================                          |  64%  |                                                                              |=============================================                         |  64%  |                                                                              |=============================================                         |  65%  |                                                                              |==============================================                        |  65%  |                                                                              |==============================================                        |  66%  |                                                                              |===============================================                       |  67%  |                                                                              |===============================================                       |  68%  |                                                                              |================================================                      |  68%  |                                                                              |=================================================                     |  70%  |                                                                              |==================================================                    |  71%  |                                                                              |===================================================                   |  73%  |                                                                              |====================================================                  |  74%  |                                                                              |====================================================                  |  75%  |                                                                              |=====================================================                 |  75%  |                                                                              |=====================================================                 |  76%  |                                                                              |======================================================                |  77%  |                                                                              |======================================================                |  78%  |                                                                              |=======================================================               |  78%  |                                                                              |=======================================================               |  79%  |                                                                              |========================================================              |  79%  |                                                                              |========================================================              |  80%  |                                                                              |=========================================================             |  81%  |                                                                              |=========================================================             |  82%  |                                                                              |==========================================================            |  82%  |                                                                              |==========================================================            |  83%  |                                                                              |===========================================================           |  84%  |                                                                              |===========================================================           |  85%  |                                                                              |============================================================          |  85%  |                                                                              |============================================================          |  86%  |                                                                              |=============================================================         |  87%  |                                                                              |==============================================================        |  88%  |                                                                              |==============================================================        |  89%  |                                                                              |===============================================================       |  90%  |                                                                              |===============================================================       |  91%  |                                                                              |================================================================      |  91%  |                                                                              |================================================================      |  92%  |                                                                              |=================================================================     |  93%  |                                                                              |==================================================================    |  94%  |                                                                              |===================================================================   |  95%  |                                                                              |===================================================================   |  96%  |                                                                              |====================================================================  |  97%  |                                                                              |====================================================================  |  98%  |                                                                              |===================================================================== |  98%  |                                                                              |===================================================================== |  99%  |                                                                              |======================================================================|  99%  |                                                                              |======================================================================| 100%

tract_naperville <- tract[naperville,]

2) Visualization of Census Tracts and Naperville

tmap_mode("view")

tm_shape(tract_naperville) + tm_borders(lwd = 2) + 
  tm_shape(naperville) + tm_polygons(col = 'blue', alpha = 0.4)

3) Create a buffer based on the distance from the centroid of each census tract and a corner of the each bounding box

# create a function
get_r <- function(poly, epsg_id){
  bb <- st_bbox(poly)
  
  bb_corner <- st_point(c(bb[1], bb[2])) %>% st_sfc(crs = epsg_id)
  bb_center_x <- (bb[1]+bb[3])/2
  bb_center_y <- (bb[2]+bb[4])/2
  bb_center <- st_point(c(bb_center_x, bb_center_y)) %>% st_sfc(crs = epsg_id) %>% st_sf
  
  r = st_distance(bb_corner, bb_center)
  bb_center$radius <- r*1.1
  return(bb_center)
}

# run this function on our data
epsg_id <- 4326
r4all_loop <- vector("list", nrow(tract_naperville))

for (i in 1:nrow(tract_naperville)){
  r4all_loop[[i]] <- tract_naperville %>%
    st_transform(crs = epsg_id) %>%
    st_geometry() %>%
    .[[i]] %>%
    get_r(epsg_id)
}

r4all_loop<-bind_rows(r4all_loop)

# add the location data at columns
ready_4_yelp <- r4all_loop %>%
  mutate(x = st_coordinates(.)[,1],
         y = st_coordinates(.)[,2])

4) Viusalization of the each buffers.

tmap_mode('view')

ready_4_yelp %>%
  st_buffer(., dist = .$radius) %>%
  tm_shape(.) + tm_polygons(alpha = 0.5, col = 'pink')+
  tm_shape(tract_naperville) +tm_borders(col='skyblue')

2. The businesses I selected

: Kids Activities, Ice cream

1) create a function to get data from yelp api

get_yelp <- function(tract, category){

  Sys.sleep(1)
  n <- 1
  resp <- business_search(api_key = Sys.getenv("yelp_api"), 
                          categories = category, 
                          latitude = tract$y, 
                          longitude = tract$x, 
                          offset = (n - 1) * 50,
                          radius = round(tract$radius), 
                          limit = 50)
  required_n <- ceiling(resp$total/50)
  out <- vector("list", required_n)
  out[[n]] <- resp$businesses
  
  names(out)[n] <- required_n
  
  if (resp$total >= 1000)
  {
    print(glue::glue("{n}th row has >= 1000 businesses."))
    return(out)
  } 
  else 
  {
    n <- n + 1
  
    while(n <= required_n){
      resp <- business_search(api_key = Sys.getenv("yelp_api"), 
                              categories = category, 
                              latitude = tract$y, 
                              longitude = tract$x, 
                              offset = (n - 1) * 50, 
                              radius = round(tract$radius), 
                              limit = 50)
      
      out[[n]] <- resp$businesses
      
      n <- n + 1
    } 
    out <- out %>% bind_rows()
    return(out)
  }
}

2) Get the first Business data : Kids Activities

yelp_kids_list <- vector("list", nrow(ready_4_yelp))

for (row in 1:nrow(ready_4_yelp)){
  yelp_kids_list[[row]] <- suppressMessages(get_yelp(ready_4_yelp[row,], "kids_activities"))
  print(paste0("Current row: ", row))
}

## [1] "Current row: 1"
## [1] "Current row: 2"
## [1] "Current row: 3"
## [1] "Current row: 4"
## [1] "Current row: 5"
## [1] "Current row: 6"
## [1] "Current row: 7"
## [1] "Current row: 8"
## [1] "Current row: 9"
## [1] "Current row: 10"
## [1] "Current row: 11"
## [1] "Current row: 12"
## [1] "Current row: 13"
## [1] "Current row: 14"
## [1] "Current row: 15"
## [1] "Current row: 16"
## [1] "Current row: 17"
## [1] "Current row: 18"
## [1] "Current row: 19"
## [1] "Current row: 20"
## [1] "Current row: 21"
## [1] "Current row: 22"
## [1] "Current row: 23"
## [1] "Current row: 24"
## [1] "Current row: 25"
## [1] "Current row: 26"
## [1] "Current row: 27"
## [1] "Current row: 28"
## [1] "Current row: 29"
## [1] "Current row: 30"
## [1] "Current row: 31"
## [1] "Current row: 32"
## [1] "Current row: 33"
## [1] "Current row: 34"
## [1] "Current row: 35"
## [1] "Current row: 36"
## [1] "Current row: 37"
## [1] "Current row: 38"
## [1] "Current row: 39"
## [1] "Current row: 40"
## [1] "Current row: 41"
## [1] "Current row: 42"
## [1] "Current row: 43"
## [1] "Current row: 44"
## [1] "Current row: 45"
## [1] "Current row: 46"
## [1] "Current row: 47"
## [1] "Current row: 48"
## [1] "Current row: 49"
## [1] "Current row: 50"
## [1] "Current row: 51"
## [1] "Current row: 52"

yelp_kids <- yelp_kids_list %>% bind_rows() %>% as_tibble()

3) Get the second Business data : Ice cream

yelp_ice_list <- vector("list", nrow(ready_4_yelp))

for (row in 1:nrow(ready_4_yelp)){
  yelp_ice_list[[row]] <- suppressMessages(get_yelp(ready_4_yelp[row,], "icecream"))
  print(paste0("Current row: ", row))
}

## [1] "Current row: 1"
## [1] "Current row: 2"
## [1] "Current row: 3"
## [1] "Current row: 4"
## [1] "Current row: 5"
## [1] "Current row: 6"
## [1] "Current row: 7"
## [1] "Current row: 8"
## [1] "Current row: 9"
## [1] "Current row: 10"
## [1] "Current row: 11"
## [1] "Current row: 12"
## [1] "Current row: 13"
## [1] "Current row: 14"
## [1] "Current row: 15"
## [1] "Current row: 16"
## [1] "Current row: 17"
## [1] "Current row: 18"
## [1] "Current row: 19"
## [1] "Current row: 20"
## [1] "Current row: 21"
## [1] "Current row: 22"
## [1] "Current row: 23"
## [1] "Current row: 24"
## [1] "Current row: 25"
## [1] "Current row: 26"
## [1] "Current row: 27"
## [1] "Current row: 28"
## [1] "Current row: 29"
## [1] "Current row: 30"
## [1] "Current row: 31"
## [1] "Current row: 32"
## [1] "Current row: 33"
## [1] "Current row: 34"
## [1] "Current row: 35"
## [1] "Current row: 36"
## [1] "Current row: 37"
## [1] "Current row: 38"
## [1] "Current row: 39"
## [1] "Current row: 40"
## [1] "Current row: 41"
## [1] "Current row: 42"
## [1] "Current row: 43"
## [1] "Current row: 44"
## [1] "Current row: 45"
## [1] "Current row: 46"
## [1] "Current row: 47"
## [1] "Current row: 48"
## [1] "Current row: 49"
## [1] "Current row: 50"
## [1] "Current row: 51"
## [1] "Current row: 52"

yelp_icecream <- yelp_ice_list %>% bind_rows() %>% as_tibble()

4) Delete the duplicate values and combine two data tables into one

#remove duplicate values
yelp_kids_uni <- yelp_kids %>% distinct(id, alias, rating, review_count, .keep_all = TRUE)
yelp_ice_uni <- yelp_icecream %>% distinct(id, alias, rating, review_count, .keep_all = TRUE)

# bind two data tables
yelp_all <- bind_rows(yelp_kids_uni, yelp_ice_uni)

5) Create spatial data frame to visualize the locations of each businesses

yelp_kids_sf <- yelp_kids_uni %>%
  mutate(x = .$coordinates$longitude,
         y = .$coordinates$latitude) %>%
  filter(!is.na(x) & !is.na(y)) %>%
  st_as_sf(coords = c("x", "y"), crs = 4326)

yelp_ice_sf <- yelp_ice_uni %>%
  mutate(x = .$coordinates$longitude,
         y = .$coordinates$latitude) %>%
  filter(!is.na(x) & !is.na(y)) %>%
  st_as_sf(coords = c("x","y"), crs=4326)

6) Visualize of ‘Kids Activities’ Business Location

tm_shape(yelp_kids_sf) + tm_dots(col = "review_count", style="quantile")

7) Visualize of ‘Ice cream’ Business Location

tm_shape(yelp_ice_sf) + tm_dots(col = "review_count", style="quantile")

Select only the location within the buffers

There were some points outside of the city buffer, so I removed those points and selected only the ones within the area.

1) Kids activities

# create the buffer area
buffer_area <- st_buffer(ready_4_yelp, dist = ready_4_yelp$radius)

# Select the 'kids activities' points within the buffer area
in_yelp_kids_sf <- yelp_kids_sf %>%
  filter(rowSums(st_within(., buffer_area, sparse = FALSE)) > 0)

# Visualize the points with buffer
tm_shape(buffer_area) + 
  tm_polygons(alpha = 0.3)+
  tm_shape(in_yelp_kids_sf) + 
  tm_dots(col = "review_count", style="quantile")

2) Ice cream

# Select the 'ice cream' points within the buffer area
in_yelp_ice_sf <- yelp_ice_sf %>%
  filter(rowSums(st_within(., buffer_area, sparse = FALSE)) > 0)

# Visualize the points with buffer
tm_shape(buffer_area) + 
  tm_polygons(alpha = 0.3)+
  tm_shape(in_yelp_ice_sf) + 
  tm_dots(col = "review_count", style="quantile")

Answers

Which city did you choose?

Naperville, IL

How many business are there in total?

yelp_all <- bind_rows(in_yelp_kids_sf, in_yelp_ice_sf)
sprintf("There are %s businesses", nrow(yelp_all))

## [1] "There are 93 businesses"

How many business are there for each business category?

sprintf("1. Kids Activity: %s", nrow(in_yelp_kids_sf))

## [1] "1. Kids Activity: 30"

sprintf("2. Ice cream and Frozen yogurt: %s", nrow(in_yelp_ice_sf))

## [1] "2. Ice cream and Frozen yogurt: 63"

Can you see any noticeable spatial patterns?

It shows that many ice cream shops are located along a specific road, suggesting that this road is likely a major commercial street. Since kids love ice cream, I also looked into the availability of ‘Kids Activities’ nearby. In this city, there are many kids activities, and they are located close to the ice cream shops, making it likely that children visit both frequently. Additionally, ice cream shops are more concentrated in certain areas, but the overall spatial distribution of both businesses looks similar.