inst/shiny-examples/bikesR/R/bikesR-internal.R
In OzzieBelazi/advRProject: Data analysis on TFL Bike data
.GeocodedInformation <-
structure(list(`295696b7d59dc616d3050a1cf879d81f` = structure(list(
results = list(structure(list(address_components = list(structure(list(
long_name = "London", short_name = "London", types = c("locality",
"political")), .Names = c("long_name", "short_name",
"types")), structure(list(long_name = "London", short_name = "London",
types = "postal_town"), .Names = c("long_name", "short_name",
"types")), structure(list(long_name = "Greater London", short_name = "Greater London",
types = c("administrative_area_level_2", "political")), .Names = c("long_name",
"short_name", "types")), structure(list(long_name = "England",
short_name = "England", types = c("administrative_area_level_1",
"political")), .Names = c("long_name", "short_name",
"types")), structure(list(long_name = "United Kingdom", short_name = "GB",
types = c("country", "political")), .Names = c("long_name",
"short_name", "types"))), formatted_address = "London, UK",
geometry = structure(list(bounds = structure(list(northeast = structure(list(
lat = 51.6723432, lng = 0.148271), .Names = c("lat",
"lng")), southwest = structure(list(lat = 51.3849401,
lng = -0.3514683), .Names = c("lat", "lng"))), .Names = c("northeast",
"southwest")), location = structure(list(lat = 51.5073509,
lng = -0.1277583), .Names = c("lat", "lng")), location_type = "APPROXIMATE",
viewport = structure(list(northeast = structure(list(
lat = 51.6723432, lng = 0.148271), .Names = c("lat",
"lng")), southwest = structure(list(lat = 51.3849401,
lng = -0.3514683), .Names = c("lat", "lng"))), .Names = c("northeast",
"southwest"))), .Names = c("bounds", "location",
"location_type", "viewport")), place_id = "ChIJdd4hrwug2EcRmSrV3Vo6llI",
types = c("locality", "political")), .Names = c("address_components",
"formatted_address", "geometry", "place_id", "types"))),
status = "OK"), .Names = c("results", "status")), `295696b7d59dc616d3050a1cf879d81f` = structure(list(
results = list(structure(list(address_components = list(structure(list(
long_name = "London", short_name = "London", types = c("locality",
"political")), .Names = c("long_name", "short_name",
"types")), structure(list(long_name = "London", short_name = "London",
types = "postal_town"), .Names = c("long_name", "short_name",
"types")), structure(list(long_name = "Greater London", short_name = "Greater London",
types = c("administrative_area_level_2", "political")), .Names = c("long_name",
"short_name", "types")), structure(list(long_name = "England",
short_name = "England", types = c("administrative_area_level_1",
"political")), .Names = c("long_name", "short_name",
"types")), structure(list(long_name = "United Kingdom", short_name = "GB",
types = c("country", "political")), .Names = c("long_name",
"short_name", "types"))), formatted_address = "London, UK",
geometry = structure(list(bounds = structure(list(northeast = structure(list(
lat = 51.6723432, lng = 0.148271), .Names = c("lat",
"lng")), southwest = structure(list(lat = 51.3849401,
lng = -0.3514683), .Names = c("lat", "lng"))), .Names = c("northeast",
"southwest")), location = structure(list(lat = 51.5073509,
lng = -0.1277583), .Names = c("lat", "lng")), location_type = "APPROXIMATE",
viewport = structure(list(northeast = structure(list(
lat = 51.6723432, lng = 0.148271), .Names = c("lat",
"lng")), southwest = structure(list(lat = 51.3849401,
lng = -0.3514683), .Names = c("lat", "lng"))), .Names = c("northeast",
"southwest"))), .Names = c("bounds", "location",
"location_type", "viewport")), place_id = "ChIJdd4hrwug2EcRmSrV3Vo6llI",
types = c("locality", "political")), .Names = c("address_components",
"formatted_address", "geometry", "place_id", "types"))),
status = "OK"), .Names = c("results", "status"))), .Names = c("295696b7d59dc616d3050a1cf879d81f",
"295696b7d59dc616d3050a1cf879d81f"))
.GoogleGeocodeQueryCount <-
structure(list(time = structure(c(1504087528.77375, 1504087900.6707
), class = c("POSIXct", "POSIXt")), url = c("295696b7d59dc616d3050a1cf879d81f",
"295696b7d59dc616d3050a1cf879d81f"), elements = c(1, 1)), .Names = c("time",
"url", "elements"), row.names = c(NA, -2L), class = "data.frame")
.GoogleRouteQueryCount <-
structure(list(time = structure(c(1504087524.32668, 1504087897.03683
), class = c("POSIXct", "POSIXt")), url = c("https://maps.googleapis.com/maps/api/directions/json?origin=St.%20Mark%27s%20Road%2C%20North%20Kensington&destination=Aberdeen%20Place%2C%20St.%20John%27s%20Wood&mode=bicycling&units=metric&alternatives=false",
"https://maps.googleapis.com/maps/api/directions/json?origin=St.%20Mark%27s%20Road%2C%20North%20Kensington&destination=Aberdeen%20Place%2C%20St.%20John%27s%20Wood&mode=bicycling&units=metric&alternatives=false"
), elements = c(1, 1)), .Names = c("time", "url", "elements"), row.names = c(NA,
-2L), class = "data.frame")
.Random.seed <-
c(403L, 28L, 1394401734L, 682504481L, 906559923L, 689126690L,
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OzzieBelazi/advRProject documentation built on May 8, 2019, 11:47 a.m.
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.GeocodedInformation <-
structure(list(`295696b7d59dc616d3050a1cf879d81f` = structure(list(
results = list(structure(list(address_components = list(structure(list(
long_name = "London", short_name = "London", types = c("locality",
"political")), .Names = c("long_name", "short_name",
"types")), structure(list(long_name = "London", short_name = "London",
types = "postal_town"), .Names = c("long_name", "short_name",
"types")), structure(list(long_name = "Greater London", short_name = "Greater London",
types = c("administrative_area_level_2", "political")), .Names = c("long_name",
"short_name", "types")), structure(list(long_name = "England",
short_name = "England", types = c("administrative_area_level_1",
"political")), .Names = c("long_name", "short_name",
"types")), structure(list(long_name = "United Kingdom", short_name = "GB",
types = c("country", "political")), .Names = c("long_name",
"short_name", "types"))), formatted_address = "London, UK",
geometry = structure(list(bounds = structure(list(northeast = structure(list(
lat = 51.6723432, lng = 0.148271), .Names = c("lat",
"lng")), southwest = structure(list(lat = 51.3849401,
lng = -0.3514683), .Names = c("lat", "lng"))), .Names = c("northeast",
"southwest")), location = structure(list(lat = 51.5073509,
lng = -0.1277583), .Names = c("lat", "lng")), location_type = "APPROXIMATE",
viewport = structure(list(northeast = structure(list(
lat = 51.6723432, lng = 0.148271), .Names = c("lat",
"lng")), southwest = structure(list(lat = 51.3849401,
lng = -0.3514683), .Names = c("lat", "lng"))), .Names = c("northeast",
"southwest"))), .Names = c("bounds", "location",
"location_type", "viewport")), place_id = "ChIJdd4hrwug2EcRmSrV3Vo6llI",
types = c("locality", "political")), .Names = c("address_components",
"formatted_address", "geometry", "place_id", "types"))),
status = "OK"), .Names = c("results", "status")), `295696b7d59dc616d3050a1cf879d81f` = structure(list(
results = list(structure(list(address_components = list(structure(list(
long_name = "London", short_name = "London", types = c("locality",
"political")), .Names = c("long_name", "short_name",
"types")), structure(list(long_name = "London", short_name = "London",
types = "postal_town"), .Names = c("long_name", "short_name",
"types")), structure(list(long_name = "Greater London", short_name = "Greater London",
types = c("administrative_area_level_2", "political")), .Names = c("long_name",
"short_name", "types")), structure(list(long_name = "England",
short_name = "England", types = c("administrative_area_level_1",
"political")), .Names = c("long_name", "short_name",
"types")), structure(list(long_name = "United Kingdom", short_name = "GB",
types = c("country", "political")), .Names = c("long_name",
"short_name", "types"))), formatted_address = "London, UK",
geometry = structure(list(bounds = structure(list(northeast = structure(list(
lat = 51.6723432, lng = 0.148271), .Names = c("lat",
"lng")), southwest = structure(list(lat = 51.3849401,
lng = -0.3514683), .Names = c("lat", "lng"))), .Names = c("northeast",
"southwest")), location = structure(list(lat = 51.5073509,
lng = -0.1277583), .Names = c("lat", "lng")), location_type = "APPROXIMATE",
viewport = structure(list(northeast = structure(list(
lat = 51.6723432, lng = 0.148271), .Names = c("lat",
"lng")), southwest = structure(list(lat = 51.3849401,
lng = -0.3514683), .Names = c("lat", "lng"))), .Names = c("northeast",
"southwest"))), .Names = c("bounds", "location",
"location_type", "viewport")), place_id = "ChIJdd4hrwug2EcRmSrV3Vo6llI",
types = c("locality", "political")), .Names = c("address_components",
"formatted_address", "geometry", "place_id", "types"))),
status = "OK"), .Names = c("results", "status"))), .Names = c("295696b7d59dc616d3050a1cf879d81f",
"295696b7d59dc616d3050a1cf879d81f"))
.GoogleGeocodeQueryCount <-
structure(list(time = structure(c(1504087528.77375, 1504087900.6707
), class = c("POSIXct", "POSIXt")), url = c("295696b7d59dc616d3050a1cf879d81f",
"295696b7d59dc616d3050a1cf879d81f"), elements = c(1, 1)), .Names = c("time",
"url", "elements"), row.names = c(NA, -2L), class = "data.frame")
.GoogleRouteQueryCount <-
structure(list(time = structure(c(1504087524.32668, 1504087897.03683
), class = c("POSIXct", "POSIXt")), url = c("https://maps.googleapis.com/maps/api/directions/json?origin=St.%20Mark%27s%20Road%2C%20North%20Kensington&destination=Aberdeen%20Place%2C%20St.%20John%27s%20Wood&mode=bicycling&units=metric&alternatives=false",
"https://maps.googleapis.com/maps/api/directions/json?origin=St.%20Mark%27s%20Road%2C%20North%20Kensington&destination=Aberdeen%20Place%2C%20St.%20John%27s%20Wood&mode=bicycling&units=metric&alternatives=false"
), elements = c(1, 1)), .Names = c("time", "url", "elements"), row.names = c(NA,
-2L), class = "data.frame")
.Random.seed <-
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