README.md
In slu-openGIS/gateway: Tools for Working with St. Louis Spatial Data
gateway 
The gateway package contains tools for manipulating spatial data for
the City of St. Louis. It was never published, though it was described in
the following publication:
Prener, Christopher G., and Branson Fox. "Creating open source composite geocoders: Pitfalls and opportunities." Transactions in GIS 25.4 (2021): 1868-1887.
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.
slu-openGIS/gateway documentation built on Jan. 31, 2024, 4:23 p.m.
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gateway
The gateway package contains tools for manipulating spatial data for
the City of St. Louis. It was never published, though it was described in
the following publication:
Prener, Christopher G., and Branson Fox. "Creating open source composite geocoders: Pitfalls and opportunities." Transactions in GIS 25.4 (2021): 1868-1887.
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)
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