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R package for working with spatial data from St. Louis
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README.md

gateway

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The gateway package contains tools for manipulating spatial data for the City of St. Louis

Installation

You can install gateway from Github with the remotes package:

remotes::install_github("slu-openGIS/gateway")

Usage

Data Access

gateway contains a function, gw_get_data(), that provides access to 18 data sets hosted by the City of St. Louis, the Saint Louis University openGIS Project, and (via tigris) the U.S. Census Bureau. This provides a “one stop shop” for downloading and accessing data about St. Louis.

> # download census tracts (via tigris)
> tracts <- gw_get_data(data = "Tracts", class = "sf")
>
> # download neighborhoods (via the City of St. Louis)
> nhoods <- gw_get_data(data = "Neighborhoods", class = "tibble")

Geocoding

Along with its cousin postmastr, gateway can be used to gecode data. In order for the local geocoder to work correctly, data needed to be parsed and standardized ahead of time. The package contains a data set, sushi, that is the same as sushi2 in the postmastr package but has already been processed and is ready for geocoding:

> sushi <- sushi

Next, we need to build our local geocoder with gw_build_geocoder():

> geocoder <- gw_build_geocoder(class = "sf")

This can take a short period of time, both because it will download a fresh master address list from the City of St. Louis (~ 7.8MB in size) and because the size of this list, approximately 330,000 addresses. Once the function finishes executing, we can move on to geocoding our data

> # geocode
> sushi_sf <- gw_geocode(sushi, type = "local", class = "sf", 
+                        address = "address", geocoder = geocoder)

Since we requested sf output with the class argument, our data are returned both with the unique address identification number that the City of St. Louis uses and the coordinate in the geometry column of our sf object:

> sushi_sf
Simple feature collection with 15 features and 4 fields
geometry type:  POINT
dimension:      XY
bbox:           xmin: -90.26318 ymin: 38.5984 xmax: -90.19386 ymax: 38.645
epsg (SRID):    4269
proj4string:    +proj=longlat +ellps=GRS80 +towgs84=0,0,0,0,0,0,0 +no_defs
# A tibble: 15 x 5
   name                            address              visit    addrrecnum             geometry
   <chr>                           <chr>                <chr>    <chr>               <POINT [°]>
 1 BaiKu Sushi Lounge              3407 Olive St        3/20/18  10022116    (-90.2282 38.63671)
 2 Cafe Mochi                      3221 S Grand Blvd    10/10/18 10049492    (-90.24307 38.5984)
 3 Drunken Fish - Central West End 1 Maryland Plz       12/2/18  10279312     (-90.26181 38.645)
 4 Kampai Sushi Bar                4949 W Pine Blvd     2/13/18  10158461   (-90.26318 38.64242)
 5 Midtown Sushi & Ramen           3674 Forest Park Ave 3/4/18   10173725   (-90.23708 38.63332)
 6 Mizu Sushi Bar                  1013 Washington Ave  9/12/18  10015227   (-90.19418 38.63163)
 7 Sapporo 2                       3043 Olive St        3/1/18   10022067   (-90.22336 38.63539)
 8 Sapporo 2                       3043 Olive St        7/3/18   10022067   (-90.22336 38.63539)
 9 Sub Zero Vodka Bar              308 N Euclid Ave     12/7/18  10096925     (-90.26088 38.645)
10 Sushi Ai                        910 Olive St         3/29/18  10021018   (-90.19386 38.62869)
11 Sushi Ai                        910 Olive St         5/20/18  10021018   (-90.19386 38.62869)
12 Sushi Ai                        910 Olive St         6/17/18  10021018   (-90.19386 38.62869)
13 Sushi Ai                        910 Olive St         8/25/18  10021018   (-90.19386 38.62869)
14 Sushi Ai                        910 Olive St         10/30/18 10021018   (-90.19386 38.62869)
15 SUSHI KOI                       4 N Euclid Ave       1/17/18  10096866   (-90.26177 38.64049)

With the data converted to a sf object, they can be mapped using a variety of tools (including ggplot2, tmap, and leaflet) or further geoprocessed (see the next section).

Spatial Joins

The gateway package contains data for further modifying point data from St. Louis. There are two primary verbs, gw_identify() and gw_aggregate(). The gw_identify() function applies identifiers from an areal unit to the point data, while the gw_aggregate() function produces counts of points per feature of the areal unit.

Identify Points

If we wanted to retain our geocoded point data, but add identifiers from one of several geographies, we can use gw_identify(). For example, we can add Census tract identifiers (GEOID) to our data:

> gw_identify(sushi_sf, to = "tract")
Point data transformed to Missouri State Plane East NAD83 (2011) for spatial join.
Simple feature collection with 15 features and 5 fields
geometry type:  POINT
dimension:      XY
bbox:           xmin: 270616.6 ymin: 306882.3 xmax: 276655.9 ymax: 312051.7
epsg (SRID):    6512
proj4string:    +proj=tmerc +lat_0=35.83333333333334 +lon_0=-90.5 +k=0.999933333 +x_0=250000 +y_0=0 +ellps=GRS80 +units=m +no_defs
# A tibble: 15 x 6
   name                            address              visit    addrrecnum GEOID                  geometry
   <chr>                           <chr>                <chr>    <chr>      <chr>               <POINT [m]>
 1 BaiKu Sushi Lounge              3407 Olive St        3/20/18  10022116   29510121100 (273663.4 311138.8)
 2 Cafe Mochi                      3221 S Grand Blvd    10/10/18 10049492   29510116301   (272381 306882.3)
 3 Drunken Fish - Central West End 1 Maryland Plz       12/2/18  10279312   29510112400 (270734.8 312050.5)
 4 Kampai Sushi Bar                4949 W Pine Blvd     2/13/18  10158461   29510112400 (270616.6 311764.6)
 5 Midtown Sushi & Ramen           3674 Forest Park Ave 3/4/18   10173725   29510118600   (272891.3 310760)
 6 Mizu Sushi Bar                  1013 Washington Ave  9/12/18  10015227   29510125600 (276626.9 310583.9)
 7 Sapporo 2                       3043 Olive St        3/1/18   10022067   29510121100 (274085.6 310994.1)
 8 Sapporo 2                       3043 Olive St        7/3/18   10022067   29510121100 (274085.6 310994.1)
 9 Sub Zero Vodka Bar              308 N Euclid Ave     12/7/18  10096925   29510112400 (270816.1 312051.7)
10 Sushi Ai                        910 Olive St         3/29/18  10021018   29510125600 (276655.9 310257.9)
11 Sushi Ai                        910 Olive St         5/20/18  10021018   29510125600 (276655.9 310257.9)
12 Sushi Ai                        910 Olive St         6/17/18  10021018   29510125600 (276655.9 310257.9)
13 Sushi Ai                        910 Olive St         8/25/18  10021018   29510125600 (276655.9 310257.9)
14 Sushi Ai                        910 Olive St         10/30/18 10021018   29510125600 (276655.9 310257.9)
15 SUSHI KOI                       4 N Euclid Ave       1/17/18  10096866   29510119101   (270740 311550.6)

The gw_identify() function also includes support for Census block groups, precincts, wards, and neighborhoods.

Aggregate Points

We can also convert these to a shapefile representing the neighborhood (or one of several other geographies) where sushi resturants are located:

> sushi_nhoods <- gw_aggregate(sushi_sf, to = "neighborhood")
Point data transformed to Missouri State Plane East NAD83 (2011) for spatial join.

We now can see that sushi resturants are concentrated in Downtown, Midtown, and the Central West End:

> sushi_nhoods %>% 
+ dplyr::arrange(dplyr::desc(COUNT))
Simple feature collection with 88 features and 4 fields
geometry type:  MULTIPOLYGON
dimension:      XY
bbox:           xmin: 265637.5 ymin: 299617.3 xmax: 278237.4 ymax: 326428.3
epsg (SRID):    6512
proj4string:    +proj=tmerc +lat_0=35.83333333333334 +lon_0=-90.5 +k=0.999933333 +x_0=250000 +y_0=0 +ellps=GRS80 +units=m +no_defs
First 10 features:
   ID                      NAME      AREA COUNT                       geometry
1  35                  Downtown 2675026.5     6 MULTIPOLYGON (((277330.3 31...
2  38          Central West End 4896607.3     4 MULTIPOLYGON (((270585.1 31...
3  37                   Midtown 3502572.3     3 MULTIPOLYGON (((274791.6 31...
4  77 Covenant Blu-Grand Center 1466647.6     1 MULTIPOLYGON (((273999.1 31...
5  15         Tower Grove South 3831397.4     1 MULTIPOLYGON (((272447.2 30...
6  43                Franz Park 1023053.7     0 MULTIPOLYGON (((267510.7 30...
7  29                   Tiffany  546954.1     0 MULTIPOLYGON (((272923.9 30...
8  28         Botanical Heights 1076380.0     0 MULTIPOLYGON (((272452.7 31...
9  40                 Kings Oak  437270.6     0 MULTIPOLYGON (((270502.8 31...
10 41                Cheltenham  858961.8     0 MULTIPOLYGON (((269632.1 31...

Other options for spatial joins are block groups, tracts, precincts, wards, or city as a whole.

Data Wrangling

Neighborhood Identifier and Name Conversion

We can also convert the neighborhood names into numeric identification numbers and back using gw_nhood():

> gw_nhood(sushi_nhoods, var = NAME, to = "numeric")
Simple feature collection with 88 features and 4 fields
geometry type:  MULTIPOLYGON
dimension:      XY
bbox:           xmin: 265637.5 ymin: 299617.3 xmax: 278237.4 ymax: 326428.3
epsg (SRID):    6512
proj4string:    +proj=tmerc +lat_0=35.83333333333334 +lon_0=-90.5 +k=0.999933333 +x_0=250000 +y_0=0 +ellps=GRS80 +units=m +no_defs
First 10 features:
   ID NAME      AREA COUNT                       geometry
1  43   43 1023053.7     0 MULTIPOLYGON (((267510.7 30...
2  29   29  546954.1     0 MULTIPOLYGON (((272923.9 30...
3  28   28 1076380.0     0 MULTIPOLYGON (((272452.7 31...
4  40   40  437270.6     0 MULTIPOLYGON (((270502.8 31...
5  41   41  858961.8     0 MULTIPOLYGON (((269632.1 31...
6  42   42  907781.7     0 MULTIPOLYGON (((268176 3105...
7  39   39 1672008.7     0 MULTIPOLYGON (((272350.9 31...
8  44   44  721220.9     0 MULTIPOLYGON (((267019.9 31...
9  36   36 2978410.3     0 MULTIPOLYGON (((276518.1 31...
10 37   37 3502572.3     3 MULTIPOLYGON (((274791.6 31...

The gw_nhood() function also offers the reverse functionality, allowing users to conver the data from numeric to string.

Extracting Coordinates

Finally, gateway offers a helper function designed to take the geometry column in a sf point object and convert its coordinates to columns:

> gw_get_coords(sushi_sf, names = c("x","y"), crs = 4269)
Simple feature collection with 15 features and 6 fields
geometry type:  POINT
dimension:      XY
bbox:           xmin: -90.26318 ymin: 38.5984 xmax: -90.19386 ymax: 38.645
epsg (SRID):    4269
proj4string:    +proj=longlat +ellps=GRS80 +towgs84=0,0,0,0,0,0,0 +no_defs
# A tibble: 15 x 7
   name                            address              visit    addrrecnum     x     y             geometry
   <chr>                           <chr>                <chr>    <chr>      <dbl> <dbl>          <POINT [°]>
 1 BaiKu Sushi Lounge              3407 Olive St        3/20/18  10022116   -90.2  38.6  (-90.2282 38.63671)
 2 Cafe Mochi                      3221 S Grand Blvd    10/10/18 10049492   -90.2  38.6  (-90.24307 38.5984)
 3 Drunken Fish - Central West End 1 Maryland Plz       12/2/18  10279312   -90.3  38.6   (-90.26181 38.645)
 4 Kampai Sushi Bar                4949 W Pine Blvd     2/13/18  10158461   -90.3  38.6 (-90.26318 38.64242)
 5 Midtown Sushi & Ramen           3674 Forest Park Ave 3/4/18   10173725   -90.2  38.6 (-90.23708 38.63332)
 6 Mizu Sushi Bar                  1013 Washington Ave  9/12/18  10015227   -90.2  38.6 (-90.19418 38.63163)
 7 Sapporo 2                       3043 Olive St        3/1/18   10022067   -90.2  38.6 (-90.22336 38.63539)
 8 Sapporo 2                       3043 Olive St        7/3/18   10022067   -90.2  38.6 (-90.22336 38.63539)
 9 Sub Zero Vodka Bar              308 N Euclid Ave     12/7/18  10096925   -90.3  38.6   (-90.26088 38.645)
10 Sushi Ai                        910 Olive St         3/29/18  10021018   -90.2  38.6 (-90.19386 38.62869)
11 Sushi Ai                        910 Olive St         5/20/18  10021018   -90.2  38.6 (-90.19386 38.62869)
12 Sushi Ai                        910 Olive St         6/17/18  10021018   -90.2  38.6 (-90.19386 38.62869)
13 Sushi Ai                        910 Olive St         8/25/18  10021018   -90.2  38.6 (-90.19386 38.62869)
14 Sushi Ai                        910 Olive St         10/30/18 10021018   -90.2  38.6 (-90.19386 38.62869)
15 SUSHI KOI                       4 N Euclid Ave       1/17/18  10096866   -90.3  38.6 (-90.26177 38.64049)

Contributor Code of Conduct

Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.

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