Nothing
inst/doc/bikedata.R
In bikedata: Download and Aggregate Data from Public Hire Bicycle Systems
## ----install1, eval = FALSE---------------------------------------------------
# install.packages ('bikedata')
## ----install2, eval = FALSE---------------------------------------------------
# devtools::install_github ("mpadge/bikedata")
## ---- eval = TRUE-------------------------------------------------------------
library (bikedata)
## ---- eval = FALSE, echo = FALSE, message = FALSE-----------------------------
# devtools::load_all ()
## ----store-la-data, eval = FALSE----------------------------------------------
# bikedb <- file.path (tempdir (), "bikedb.sqlite") # or whatever
# dl_bikedata (city = 'la', dates = 2016, quiet = TRUE)
# store_bikedata (data_dir = tempdir (), bikedb = bikedb, quiet = TRUE)
## ----store-la-data-dummy, echo = FALSE----------------------------------------
98138
## ---- eval = FALSE------------------------------------------------------------
# dl_bikedata (city = 'divvy', dates = 2016, quiet = TRUE)
# store_bikedata (bikedb = bikedb, data_dir = tempdir (), quiet = TRUE)
## ---- echo = FALSE------------------------------------------------------------
3595383
## ---- eval = FALSE------------------------------------------------------------
# bike_db_totals (bikedb = bikedb)
## ---- echo = FALSE------------------------------------------------------------
3693521
## ---- eval = FALSE------------------------------------------------------------
# index_bikedata_db (bikedb = bikedb)
## ---- eval = FALSE------------------------------------------------------------
# tm <- bike_tripmat (bikedb = bikedb, city = 'la')
# class (tm); dim (tm); sum (tm)
## -----------------------------------------------------------------------------
## ---- echo = FALSE------------------------------------------------------------
x <- "matrix"; y <- c (64, 64); z <- 98138
x; y; z
## ---- eval = FALSE------------------------------------------------------------
# bike_tripmat (bikedb = bikedb, city = 'la', long = TRUE)
## ---- echo = FALSE------------------------------------------------------------
n <- 4096
ss <- c (rep ('la3005', 10), rep (NA, n - 10))
es <- c ('la3005', 'la3006', 'la3007', 'la3008', 'la3010', 'la3011',
'la3014', 'la3016', 'la3018', 'la3019', rep (NA, n - 10))
nt <- c (252, 93, 23, 153, 5, 63, 40, 10, 31, 36, rep (NA, n - 10))
tm <- tibble::tibble (start_station_id = ss,
end_station_id = es, numtrips = nt)
tm
## ---- eval = FALSE------------------------------------------------------------
# bike_stations (bikedb = bikedb)
## ---- echo = FALSE------------------------------------------------------------
n <- 660
id <- seq (n)
city <- rep ('la', n)
ids <- c ('la3005', 'la3006', 'la3007', 'la3008', 'la3009',
'la3010', 'la3011', 'la3013', 'la3014', 'la3016', rep (NA, n - 10))
x <- c (34.04855, 34.04554, 34.05048, 34.04661, 33.98738,
34.03705, 34.04113, 34.05661, 34.05290, 34.04373, rep (NA, n - 10))
y <- c (-118.2590, -118.2567, -118.2546, -118.2627, -118.4728,
-118.2549, -118.2680, -118.2372, -118.2416, -118.2601, rep (NA, n - 10))
stations1 <- tibble::tibble (id = id, city = city, stn_id = ids,
name = rep ('', n), longitude = x, latitude = y)
stations1
## ---- eval = FALSE------------------------------------------------------------
# st <- bike_stations (bikedb = bikedb, city = 'ch')
## ---- eval = FALSE------------------------------------------------------------
# bike_write_test_data ()
# store_bikedata (bikedb = 'testdb')
# bike_summary_stats (bikedb = 'testdb')
## ---- eval = FALSE------------------------------------------------------------
# dl_bikedata (city = 'chicago', data_dir = '/data/bikedata/')
## ---- eval = FALSE------------------------------------------------------------
# dl_bikedata (city = 'dc', dates = 16)
## ---- eval = FALSE------------------------------------------------------------
# dl_bikedata (city = 'ny', dates = 201604:201608)
## ---- eval = FALSE------------------------------------------------------------
# dl_bikedata (city = 'ny', dates = '2016/04:2016/08')
# dl_bikedata (city = 'new york', dates = '201604:201608')
# dl_bikedata (city = 'n.y.c.', dates = '2016-04:2016-08')
# dl_bikedata (city = 'new', dates = '2016 Apr-Aug')
## ---- eval = FALSE------------------------------------------------------------
# dl_bikedata (city = 'dc', dates = '2016.03-2016.05')
## ---- eval = FALSE------------------------------------------------------------
# dl_bikedata (city = 'sf', data_dir = '/data/stored/here')
## ---- eval = FALSE------------------------------------------------------------
# store_bikedata (city = 'sf', data_dir = '/data/stored/here', bikedb = bikedb)
## ---- eval = FALSE------------------------------------------------------------
# bike_stored_files (bikedb = bikedb = city = 'sf')
## ---- eval = FALSE------------------------------------------------------------
# dl_bikedata (bikedb = bikedb, city = 'ny', dates = '2014 aug - 2015 dec')
# ntrips <- store_bikedata (bikedb = bikedb, city = 'ny',
# data_dir = '/data/stored/here')
## ---- eval = FALSE------------------------------------------------------------
# dim (bike_tripmat (bikedb = bikedb, city = 'ch'))
## ---- echo = FALSE------------------------------------------------------------
c (581, 581)
## ---- eval = FALSE------------------------------------------------------------
# dim (bike_stations (bikedb = bikedb, city = 'ch'))
## ---- echo = FALSE------------------------------------------------------------
c (596, 6)
## ---- eval = FALSE------------------------------------------------------------
# args0 <- list (bikedb = bikedb, city = 'ny', args)
# args1 <- list (start_date = 16, end_time = 12, weekday = 1)
# tm <- do.call (bike_tripmat, c (args0, args1))
## ---- eval = FALSE------------------------------------------------------------
# args1 <- list (start_date = '2016 May', end_time = '12:39', weekday = 2:6)
# args1 <- list (end_date = 20160720, end_time = 123915, weekday = c ('mo', 'we'))
# args1 <- list (end_date = '2016-07-20', end_time = '12:39:15', weekday = 2:6)
## -----------------------------------------------------------------------------
bike_demographic_data ()
## ---- eval = FALSE------------------------------------------------------------
# tm <- bike_tripmat (bikedb = bikedb, city = 'ny', start_date = 2016,
# start_time = 9, end_time = 24, weekday = 2:6, gender = 'xx',
# birth_year = 1900:1950)
## ---- eval = FALSE------------------------------------------------------------
# bike_stations (bikedb = bikedb)
## ---- echo = FALSE------------------------------------------------------------
stations1
## ---- eval = FALSE------------------------------------------------------------
# bike_stations (bikedb = bikedb, city = 'ch')
## ---- echo = FALSE------------------------------------------------------------
n <- 596
id <- 66 + seq (n)
city <- rep ('ch', n)
ids <- c ('ch456', 'ch101', 'ch109', 'ch21', 'ch80',
'ch346', 'ch341', 'ch444', 'ch511', 'ch376', rep (NA, n - 10))
nms <- c ('2112 W Peterson Ave', '63rd St Beach', '900 W Harrison St',
'Aberdeen St & Jackson Blvd', 'Aberdeen St & Monroe St',
'Ada St & Washington Blvd', 'Adler Planetarium',
'Albany Ave & 26th St', 'Albany Ave & Bloomingdale Ave',
'Artesian Ave & Hubbard St', rep (NA, n - 10))
x <- c (-87.68359, -87.57612, -87.65002, -87.65479, -87.65393,
-87.66121, -87.60727, -87.70201, -87.70513, -87.68822, rep (NA, n - 10))
y <- c (41.99118, 41.78102, 41.87468, 41.87773, 41.88046,
41.88283, 41.86610, 41.84448, 41.91403, 41.88949, rep (NA, n - 10))
stations2 <- tibble::tibble (id = id, city = city, stn_id = ids,
name = nms, longitude = x, latitude = y)
stations2
## ---- eval = FALSE------------------------------------------------------------
# bike_summary_stats (bikedb)
## ---- echo = FALSE------------------------------------------------------------
ntr <- c (3693521, 3595383, 98138)
nst <- c (662, 596, 66)
startd <- c ('2016-01-01 00:07:00', '2016-01-01 00:07:00',
'2016-07-07 04:17:00')
endd <- rep ('2016-12-31 23:57:52', 3)
fls <- c (NA, TRUE, TRUE)
tbl <- tibble::tibble (city = c ("total", "ch", "la"),
num_trips = ntr, num_stations = nst,
first_trip = as.factor (startd),
last_trip = as.factor (endd), latest_files = fls)
tbl
## ---- eval = FALSE------------------------------------------------------------
# bike_db_totals (bikedb = bikedb)
## ---- echo = FALSE------------------------------------------------------------
3693521
## ---- eval = FALSE------------------------------------------------------------
# bike_db_totals (bikedb = bikedb, city = "ch")
## ---- echo = FALSE------------------------------------------------------------
3595383
## ---- eval = FALSE------------------------------------------------------------
# bike_db_totals (bikedb = bikedb, city = "la")
## ---- echo = FALSE------------------------------------------------------------
93138
## ---- eval = FALSE------------------------------------------------------------
# bike_db_totals (bikedb = bikedb, trips = FALSE)
## ---- echo = FALSE------------------------------------------------------------
660
## ---- eval = FALSE------------------------------------------------------------
# bike_db_totals (bikedb = bikedb, trips = FALSE, city = "ch")
## ---- echo = FALSE------------------------------------------------------------
596
## ---- eval = FALSE------------------------------------------------------------
# bike_db_totals (bikedb = bikedb, trips = FALSE, city = "la")
## ---- echo = FALSE------------------------------------------------------------
64
## ---- eval = FALSE------------------------------------------------------------
# bike_datelimits (bikedb = bikedb)
## ---- echo = FALSE------------------------------------------------------------
c ('first' = "2016-01-01 00:07:00", 'last' = "2016-12-31 23:57:52")
## ---- eval = FALSE------------------------------------------------------------
# bike_datelimits (bikedb = bikedb, city = 'ch')
## -----------------------------------------------------------------------------
c ('first' = "2016-01-01 00:07:00", 'last' = "2016-12-31 23:57:52")
## ---- eval = FALSE------------------------------------------------------------
# bike_latest_files (bikedb = bikedb)
## -----------------------------------------------------------------------------
c ('la' = TRUE, 'ch' = FALSE)
## ---- eval = FALSE------------------------------------------------------------
# bike_daily_trips (bikedb = bikedb, city = 'ch')
## ---- echo = FALSE------------------------------------------------------------
n <- 366
dates <- c ('2016-01-01', '2016-01-02', '2016-01-03', '2016-01-04',
'2016-01-05', '2016-01-06', '2016-01-07', '2016-01-08',
'2016-01-09', '2016-01-10', rep (NA, n - 10))
nt <- c (935, 1421, 1399, 3833, 4189, 4608, 5028, 3425, 1733, 993,
rep (NA, n - 10))
tibble::tibble (date = dates, numtrips = nt)
## ---- eval = FALSE------------------------------------------------------------
# bike_daily_trips (bikedb = bikedb, city = 'ch', standardise = TRUE)
## ---- echo = FALSE------------------------------------------------------------
nt <- c (2468.925, 2481.939, 2200.766, 5509.787, 5884.207, 6298.229, 6630.111,
4476.455, 2265.021, 1297.845, rep (NA, n - 10))
tibble::tibble (date = dates, numtrips = nt)
## ---- eval = FALSE------------------------------------------------------------
# db <- dplyr::src_sqlite (bikedb, create=F)
# dplyr::src_tbls (db)
## -----------------------------------------------------------------------------
c ("datafiles", "stations", "trips")
## ---- eval = FALSE------------------------------------------------------------
# dplyr::collect (dplyr::tbl (db, 'datafiles'))
## ---- echo = FALSE------------------------------------------------------------
city <- c ('la', 'la', 'la', 'ch', 'ch')
nms <- c ('la_metro_gbfs_trips_Q1_2017.zip', 'MetroBikeShare_2016_Q3_trips.zip',
'Metro_trips_Q4_2016.zip', 'Divvy_Trips_2016_Q1Q2.zip',
'Divvy_Trips_2016_Q3Q4.zip')
tibble::tibble (id = 0:4, city = city, name = nms)
## ---- eval = FALSE------------------------------------------------------------
# dplyr::collect (dplyr::tbl (db, 'stations'))
## ---- echo = FALSE------------------------------------------------------------
stations1
## ---- eval = FALSE------------------------------------------------------------
# dplyr::collect (dplyr::tbl (db, 'trips'))
## ---- echo = FALSE------------------------------------------------------------
n <- 3693511
id <- seq (n)
city <- rep ('la', n)
dur <- c (180, 1980, 300, 10860, 420, 780, 600, 600, 2880, 960,
rep (NA, n - 10))
st <- c ('2016-01-01 00:15:00', '2016-01-01 00:24:00', '2016-01-01 00:28:00',
'2016-01-01 00:38:00', '2016-01-01 00:38:00', '2016-01-01 00:39:00',
'2016-01-01 00:43:00', '2016-01-01 00:56:00', '2016-01-01 00:57:00',
'2016-01-01 01:54:00', rep (NA, n - 10))
et <- c ('2017-01-01 00:23:00', '2017-01-01 00:36:00', '2017-01-01 00:45:00',
'2017-01-01 00:43:00', '2017-01-01 00:43:00', '2017-01-01 00:59:00',
'2017-01-01 00:55:00', '2017-01-01 01:44:00', '2017-01-01 01:44:00',
'2017-01-01 02:19:00', rep (NA, n - 10))
nachr <- rep ('a', n)
naint <- rep (1L, n)
tibble::tibble (id = id, city = city, trip_duration = dur,
start_time = st, stop_time = et,
start_station_id = nachr, end_station_id = nachr,
bike_id = nachr, user_type = nachr, birth_year = naint,
gender = naint)
## ---- eval = FALSE------------------------------------------------------------
# db <- RSQLite::dbConnect(RSQLite::SQLite(), bikedb, create = FALSE)
# qry <- "SELECT stn_id, name FROM stations WHERE city = 'ch'"
# stns <- RSQLite::dbGetQuery(db, qry)
# RSQLite::dbDisconnect(db)
# head (stns)
## ---- echo = FALSE------------------------------------------------------------
data.frame (stn_id = c ('ch456', 'ch101', 'ch109', 'ch21', 'ch80', 'ch346'),
name = c ('2112 W Peterson Ave', '63rd St Beach',
'900 W Harrison St', 'Aberdeen St & Jackson Blvd',
'Aberdeen St & Monroe St', 'Ada St & Washington Blvd'))
## ----plot-la-out, echo = TRUE, eval = FALSE-----------------------------------
# stns <- bike_stations (bikedb = bikedb, city = 'la')
# ntrips <- bike_tripmat (bikedb = bikedb, city = 'la', long = TRUE)
# x1 <- stns$longitude [match (ntrips$start_station_id, stns$stn_id)]
# y1 <- stns$latitude [match (ntrips$start_station_id, stns$stn_id)]
# x2 <- stns$longitude [match (ntrips$end_station_id, stns$stn_id)]
# y2 <- stns$latitude [match (ntrips$end_station_id, stns$stn_id)]
# # Set plot area to central region of bike system
# xlims <- c (-118.27, -118.23)
# ylims <- c (34.02, 34.07)
# plot (stns$longitude, stns$latitude, xlim = xlims, ylim = ylims)
# cols <- rainbow (100)
# nt <- ceiling (ntrips$numtrips * 100 / max (ntrips$numtrips))
# for (i in seq (x1))
# lines (c (x1 [i], x2 [i]), c (y1 [i], y2 [i]), col = cols [nt [i]],
# lwd = ntrips$numtrips [i] * 10 / max (ntrips$numtrips))
## ----get-la-highways, eval = FALSE--------------------------------------------
# library (magrittr)
# xlims_la <- range (stns$longitude, na.rm = TRUE)
# ylims_la <- range (stns$latitude, na.rm = TRUE)
# # expand those limits slightly
# ex <- 0.1
# xlims_la <- xlims_la + c (-ex, ex) * diff (xlims_la)
# ylims_la <- ylims_la + c (-ex, ex) * diff (ylims_la)
# bbox <- c (xlims_la [1], ylims_la [1], xlims_la [2], ylims_la [2])
# bbox <- c (xlims [1], xlims [2], ylims [1], ylims [2])
# # Then the actual osmdata query to extract all OpenStreetMap highways
# highways <- osmdata::opq (bbox = bbox) %>%
# osmdata::add_osm_feature (key = 'highway') %>%
# osmdata::osmdata_sp (quiet = FALSE)
## ----convert-stns-to-spdf, eval = FALSE---------------------------------------
# stns_tbl <- bike_stations (bikedb = bikedb)
# stns <- sp::SpatialPointsDataFrame (coords = stns_tbl[,c('longitude','latitude')],
# proj4string = sp::CRS("+init=epsg:4326"),
# data = stns_tbl)
# stns <- sp::spTransform (stns, highways$osm_lines@proj4string)
## ----map-stns-to-streetnet, eval = FALSE--------------------------------------
# la_net <- stplanr::SpatialLinesNetwork (sl = highways$osm_lines)
# # Find the closest node to each station
# nodeid <- stplanr::find_network_nodes (la_net, stns$longitude, stns$latitude)
# # Convert start and end station IDs in trips table to node IDs in `la_net`
# startid <- nodeid [match (ntrips$start_station_id, stns$stn_id)]
# endid <- nodeid [match (ntrips$end_station_id, stns$stn_id)]
# ntrips$start_station_id <- startid
# ntrips$end_station_id <- endid
## ---- eval = FALSE------------------------------------------------------------
# bike_usage <- stplanr::sum_network_links (la_net, data.frame (ntrips))
## ----plot-tmat, eval = FALSE--------------------------------------------------
# tmap::tm_shape (bike_usage, xlim = xlims, ylim = ylims, is.master=TRUE) +
# tmap::tm_lines (col="numtrips", lwd="numtrips", title.col = "Number of trips",
# breaks = c(0, 200, 400, 600, 800, 1000, Inf),
# legend.lwd.show = FALSE, scale = 5) +
# tmap::tm_layout (bg.color="gray95", legend.position = c ("right", "bottom"),
# legend.bg.color = "white", legend.bg.alpha = 0.5)
# #tmap::save_tmap (filename = "la_map.png")
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## ----install1, eval = FALSE---------------------------------------------------
# install.packages ('bikedata')
## ----install2, eval = FALSE---------------------------------------------------
# devtools::install_github ("mpadge/bikedata")
## ---- eval = TRUE-------------------------------------------------------------
library (bikedata)
## ---- eval = FALSE, echo = FALSE, message = FALSE-----------------------------
# devtools::load_all ()
## ----store-la-data, eval = FALSE----------------------------------------------
# bikedb <- file.path (tempdir (), "bikedb.sqlite") # or whatever
# dl_bikedata (city = 'la', dates = 2016, quiet = TRUE)
# store_bikedata (data_dir = tempdir (), bikedb = bikedb, quiet = TRUE)
## ----store-la-data-dummy, echo = FALSE----------------------------------------
98138
## ---- eval = FALSE------------------------------------------------------------
# dl_bikedata (city = 'divvy', dates = 2016, quiet = TRUE)
# store_bikedata (bikedb = bikedb, data_dir = tempdir (), quiet = TRUE)
## ---- echo = FALSE------------------------------------------------------------
3595383
## ---- eval = FALSE------------------------------------------------------------
# bike_db_totals (bikedb = bikedb)
## ---- echo = FALSE------------------------------------------------------------
3693521
## ---- eval = FALSE------------------------------------------------------------
# index_bikedata_db (bikedb = bikedb)
## ---- eval = FALSE------------------------------------------------------------
# tm <- bike_tripmat (bikedb = bikedb, city = 'la')
# class (tm); dim (tm); sum (tm)
## -----------------------------------------------------------------------------
## ---- echo = FALSE------------------------------------------------------------
x <- "matrix"; y <- c (64, 64); z <- 98138
x; y; z
## ---- eval = FALSE------------------------------------------------------------
# bike_tripmat (bikedb = bikedb, city = 'la', long = TRUE)
## ---- echo = FALSE------------------------------------------------------------
n <- 4096
ss <- c (rep ('la3005', 10), rep (NA, n - 10))
es <- c ('la3005', 'la3006', 'la3007', 'la3008', 'la3010', 'la3011',
'la3014', 'la3016', 'la3018', 'la3019', rep (NA, n - 10))
nt <- c (252, 93, 23, 153, 5, 63, 40, 10, 31, 36, rep (NA, n - 10))
tm <- tibble::tibble (start_station_id = ss,
end_station_id = es, numtrips = nt)
tm
## ---- eval = FALSE------------------------------------------------------------
# bike_stations (bikedb = bikedb)
## ---- echo = FALSE------------------------------------------------------------
n <- 660
id <- seq (n)
city <- rep ('la', n)
ids <- c ('la3005', 'la3006', 'la3007', 'la3008', 'la3009',
'la3010', 'la3011', 'la3013', 'la3014', 'la3016', rep (NA, n - 10))
x <- c (34.04855, 34.04554, 34.05048, 34.04661, 33.98738,
34.03705, 34.04113, 34.05661, 34.05290, 34.04373, rep (NA, n - 10))
y <- c (-118.2590, -118.2567, -118.2546, -118.2627, -118.4728,
-118.2549, -118.2680, -118.2372, -118.2416, -118.2601, rep (NA, n - 10))
stations1 <- tibble::tibble (id = id, city = city, stn_id = ids,
name = rep ('', n), longitude = x, latitude = y)
stations1
## ---- eval = FALSE------------------------------------------------------------
# st <- bike_stations (bikedb = bikedb, city = 'ch')
## ---- eval = FALSE------------------------------------------------------------
# bike_write_test_data ()
# store_bikedata (bikedb = 'testdb')
# bike_summary_stats (bikedb = 'testdb')
## ---- eval = FALSE------------------------------------------------------------
# dl_bikedata (city = 'chicago', data_dir = '/data/bikedata/')
## ---- eval = FALSE------------------------------------------------------------
# dl_bikedata (city = 'dc', dates = 16)
## ---- eval = FALSE------------------------------------------------------------
# dl_bikedata (city = 'ny', dates = 201604:201608)
## ---- eval = FALSE------------------------------------------------------------
# dl_bikedata (city = 'ny', dates = '2016/04:2016/08')
# dl_bikedata (city = 'new york', dates = '201604:201608')
# dl_bikedata (city = 'n.y.c.', dates = '2016-04:2016-08')
# dl_bikedata (city = 'new', dates = '2016 Apr-Aug')
## ---- eval = FALSE------------------------------------------------------------
# dl_bikedata (city = 'dc', dates = '2016.03-2016.05')
## ---- eval = FALSE------------------------------------------------------------
# dl_bikedata (city = 'sf', data_dir = '/data/stored/here')
## ---- eval = FALSE------------------------------------------------------------
# store_bikedata (city = 'sf', data_dir = '/data/stored/here', bikedb = bikedb)
## ---- eval = FALSE------------------------------------------------------------
# bike_stored_files (bikedb = bikedb = city = 'sf')
## ---- eval = FALSE------------------------------------------------------------
# dl_bikedata (bikedb = bikedb, city = 'ny', dates = '2014 aug - 2015 dec')
# ntrips <- store_bikedata (bikedb = bikedb, city = 'ny',
# data_dir = '/data/stored/here')
## ---- eval = FALSE------------------------------------------------------------
# dim (bike_tripmat (bikedb = bikedb, city = 'ch'))
## ---- echo = FALSE------------------------------------------------------------
c (581, 581)
## ---- eval = FALSE------------------------------------------------------------
# dim (bike_stations (bikedb = bikedb, city = 'ch'))
## ---- echo = FALSE------------------------------------------------------------
c (596, 6)
## ---- eval = FALSE------------------------------------------------------------
# args0 <- list (bikedb = bikedb, city = 'ny', args)
# args1 <- list (start_date = 16, end_time = 12, weekday = 1)
# tm <- do.call (bike_tripmat, c (args0, args1))
## ---- eval = FALSE------------------------------------------------------------
# args1 <- list (start_date = '2016 May', end_time = '12:39', weekday = 2:6)
# args1 <- list (end_date = 20160720, end_time = 123915, weekday = c ('mo', 'we'))
# args1 <- list (end_date = '2016-07-20', end_time = '12:39:15', weekday = 2:6)
## -----------------------------------------------------------------------------
bike_demographic_data ()
## ---- eval = FALSE------------------------------------------------------------
# tm <- bike_tripmat (bikedb = bikedb, city = 'ny', start_date = 2016,
# start_time = 9, end_time = 24, weekday = 2:6, gender = 'xx',
# birth_year = 1900:1950)
## ---- eval = FALSE------------------------------------------------------------
# bike_stations (bikedb = bikedb)
## ---- echo = FALSE------------------------------------------------------------
stations1
## ---- eval = FALSE------------------------------------------------------------
# bike_stations (bikedb = bikedb, city = 'ch')
## ---- echo = FALSE------------------------------------------------------------
n <- 596
id <- 66 + seq (n)
city <- rep ('ch', n)
ids <- c ('ch456', 'ch101', 'ch109', 'ch21', 'ch80',
'ch346', 'ch341', 'ch444', 'ch511', 'ch376', rep (NA, n - 10))
nms <- c ('2112 W Peterson Ave', '63rd St Beach', '900 W Harrison St',
'Aberdeen St & Jackson Blvd', 'Aberdeen St & Monroe St',
'Ada St & Washington Blvd', 'Adler Planetarium',
'Albany Ave & 26th St', 'Albany Ave & Bloomingdale Ave',
'Artesian Ave & Hubbard St', rep (NA, n - 10))
x <- c (-87.68359, -87.57612, -87.65002, -87.65479, -87.65393,
-87.66121, -87.60727, -87.70201, -87.70513, -87.68822, rep (NA, n - 10))
y <- c (41.99118, 41.78102, 41.87468, 41.87773, 41.88046,
41.88283, 41.86610, 41.84448, 41.91403, 41.88949, rep (NA, n - 10))
stations2 <- tibble::tibble (id = id, city = city, stn_id = ids,
name = nms, longitude = x, latitude = y)
stations2
## ---- eval = FALSE------------------------------------------------------------
# bike_summary_stats (bikedb)
## ---- echo = FALSE------------------------------------------------------------
ntr <- c (3693521, 3595383, 98138)
nst <- c (662, 596, 66)
startd <- c ('2016-01-01 00:07:00', '2016-01-01 00:07:00',
'2016-07-07 04:17:00')
endd <- rep ('2016-12-31 23:57:52', 3)
fls <- c (NA, TRUE, TRUE)
tbl <- tibble::tibble (city = c ("total", "ch", "la"),
num_trips = ntr, num_stations = nst,
first_trip = as.factor (startd),
last_trip = as.factor (endd), latest_files = fls)
tbl
## ---- eval = FALSE------------------------------------------------------------
# bike_db_totals (bikedb = bikedb)
## ---- echo = FALSE------------------------------------------------------------
3693521
## ---- eval = FALSE------------------------------------------------------------
# bike_db_totals (bikedb = bikedb, city = "ch")
## ---- echo = FALSE------------------------------------------------------------
3595383
## ---- eval = FALSE------------------------------------------------------------
# bike_db_totals (bikedb = bikedb, city = "la")
## ---- echo = FALSE------------------------------------------------------------
93138
## ---- eval = FALSE------------------------------------------------------------
# bike_db_totals (bikedb = bikedb, trips = FALSE)
## ---- echo = FALSE------------------------------------------------------------
660
## ---- eval = FALSE------------------------------------------------------------
# bike_db_totals (bikedb = bikedb, trips = FALSE, city = "ch")
## ---- echo = FALSE------------------------------------------------------------
596
## ---- eval = FALSE------------------------------------------------------------
# bike_db_totals (bikedb = bikedb, trips = FALSE, city = "la")
## ---- echo = FALSE------------------------------------------------------------
64
## ---- eval = FALSE------------------------------------------------------------
# bike_datelimits (bikedb = bikedb)
## ---- echo = FALSE------------------------------------------------------------
c ('first' = "2016-01-01 00:07:00", 'last' = "2016-12-31 23:57:52")
## ---- eval = FALSE------------------------------------------------------------
# bike_datelimits (bikedb = bikedb, city = 'ch')
## -----------------------------------------------------------------------------
c ('first' = "2016-01-01 00:07:00", 'last' = "2016-12-31 23:57:52")
## ---- eval = FALSE------------------------------------------------------------
# bike_latest_files (bikedb = bikedb)
## -----------------------------------------------------------------------------
c ('la' = TRUE, 'ch' = FALSE)
## ---- eval = FALSE------------------------------------------------------------
# bike_daily_trips (bikedb = bikedb, city = 'ch')
## ---- echo = FALSE------------------------------------------------------------
n <- 366
dates <- c ('2016-01-01', '2016-01-02', '2016-01-03', '2016-01-04',
'2016-01-05', '2016-01-06', '2016-01-07', '2016-01-08',
'2016-01-09', '2016-01-10', rep (NA, n - 10))
nt <- c (935, 1421, 1399, 3833, 4189, 4608, 5028, 3425, 1733, 993,
rep (NA, n - 10))
tibble::tibble (date = dates, numtrips = nt)
## ---- eval = FALSE------------------------------------------------------------
# bike_daily_trips (bikedb = bikedb, city = 'ch', standardise = TRUE)
## ---- echo = FALSE------------------------------------------------------------
nt <- c (2468.925, 2481.939, 2200.766, 5509.787, 5884.207, 6298.229, 6630.111,
4476.455, 2265.021, 1297.845, rep (NA, n - 10))
tibble::tibble (date = dates, numtrips = nt)
## ---- eval = FALSE------------------------------------------------------------
# db <- dplyr::src_sqlite (bikedb, create=F)
# dplyr::src_tbls (db)
## -----------------------------------------------------------------------------
c ("datafiles", "stations", "trips")
## ---- eval = FALSE------------------------------------------------------------
# dplyr::collect (dplyr::tbl (db, 'datafiles'))
## ---- echo = FALSE------------------------------------------------------------
city <- c ('la', 'la', 'la', 'ch', 'ch')
nms <- c ('la_metro_gbfs_trips_Q1_2017.zip', 'MetroBikeShare_2016_Q3_trips.zip',
'Metro_trips_Q4_2016.zip', 'Divvy_Trips_2016_Q1Q2.zip',
'Divvy_Trips_2016_Q3Q4.zip')
tibble::tibble (id = 0:4, city = city, name = nms)
## ---- eval = FALSE------------------------------------------------------------
# dplyr::collect (dplyr::tbl (db, 'stations'))
## ---- echo = FALSE------------------------------------------------------------
stations1
## ---- eval = FALSE------------------------------------------------------------
# dplyr::collect (dplyr::tbl (db, 'trips'))
## ---- echo = FALSE------------------------------------------------------------
n <- 3693511
id <- seq (n)
city <- rep ('la', n)
dur <- c (180, 1980, 300, 10860, 420, 780, 600, 600, 2880, 960,
rep (NA, n - 10))
st <- c ('2016-01-01 00:15:00', '2016-01-01 00:24:00', '2016-01-01 00:28:00',
'2016-01-01 00:38:00', '2016-01-01 00:38:00', '2016-01-01 00:39:00',
'2016-01-01 00:43:00', '2016-01-01 00:56:00', '2016-01-01 00:57:00',
'2016-01-01 01:54:00', rep (NA, n - 10))
et <- c ('2017-01-01 00:23:00', '2017-01-01 00:36:00', '2017-01-01 00:45:00',
'2017-01-01 00:43:00', '2017-01-01 00:43:00', '2017-01-01 00:59:00',
'2017-01-01 00:55:00', '2017-01-01 01:44:00', '2017-01-01 01:44:00',
'2017-01-01 02:19:00', rep (NA, n - 10))
nachr <- rep ('a', n)
naint <- rep (1L, n)
tibble::tibble (id = id, city = city, trip_duration = dur,
start_time = st, stop_time = et,
start_station_id = nachr, end_station_id = nachr,
bike_id = nachr, user_type = nachr, birth_year = naint,
gender = naint)
## ---- eval = FALSE------------------------------------------------------------
# db <- RSQLite::dbConnect(RSQLite::SQLite(), bikedb, create = FALSE)
# qry <- "SELECT stn_id, name FROM stations WHERE city = 'ch'"
# stns <- RSQLite::dbGetQuery(db, qry)
# RSQLite::dbDisconnect(db)
# head (stns)
## ---- echo = FALSE------------------------------------------------------------
data.frame (stn_id = c ('ch456', 'ch101', 'ch109', 'ch21', 'ch80', 'ch346'),
name = c ('2112 W Peterson Ave', '63rd St Beach',
'900 W Harrison St', 'Aberdeen St & Jackson Blvd',
'Aberdeen St & Monroe St', 'Ada St & Washington Blvd'))
## ----plot-la-out, echo = TRUE, eval = FALSE-----------------------------------
# stns <- bike_stations (bikedb = bikedb, city = 'la')
# ntrips <- bike_tripmat (bikedb = bikedb, city = 'la', long = TRUE)
# x1 <- stns$longitude [match (ntrips$start_station_id, stns$stn_id)]
# y1 <- stns$latitude [match (ntrips$start_station_id, stns$stn_id)]
# x2 <- stns$longitude [match (ntrips$end_station_id, stns$stn_id)]
# y2 <- stns$latitude [match (ntrips$end_station_id, stns$stn_id)]
# # Set plot area to central region of bike system
# xlims <- c (-118.27, -118.23)
# ylims <- c (34.02, 34.07)
# plot (stns$longitude, stns$latitude, xlim = xlims, ylim = ylims)
# cols <- rainbow (100)
# nt <- ceiling (ntrips$numtrips * 100 / max (ntrips$numtrips))
# for (i in seq (x1))
# lines (c (x1 [i], x2 [i]), c (y1 [i], y2 [i]), col = cols [nt [i]],
# lwd = ntrips$numtrips [i] * 10 / max (ntrips$numtrips))
## ----get-la-highways, eval = FALSE--------------------------------------------
# library (magrittr)
# xlims_la <- range (stns$longitude, na.rm = TRUE)
# ylims_la <- range (stns$latitude, na.rm = TRUE)
# # expand those limits slightly
# ex <- 0.1
# xlims_la <- xlims_la + c (-ex, ex) * diff (xlims_la)
# ylims_la <- ylims_la + c (-ex, ex) * diff (ylims_la)
# bbox <- c (xlims_la [1], ylims_la [1], xlims_la [2], ylims_la [2])
# bbox <- c (xlims [1], xlims [2], ylims [1], ylims [2])
# # Then the actual osmdata query to extract all OpenStreetMap highways
# highways <- osmdata::opq (bbox = bbox) %>%
# osmdata::add_osm_feature (key = 'highway') %>%
# osmdata::osmdata_sp (quiet = FALSE)
## ----convert-stns-to-spdf, eval = FALSE---------------------------------------
# stns_tbl <- bike_stations (bikedb = bikedb)
# stns <- sp::SpatialPointsDataFrame (coords = stns_tbl[,c('longitude','latitude')],
# proj4string = sp::CRS("+init=epsg:4326"),
# data = stns_tbl)
# stns <- sp::spTransform (stns, highways$osm_lines@proj4string)
## ----map-stns-to-streetnet, eval = FALSE--------------------------------------
# la_net <- stplanr::SpatialLinesNetwork (sl = highways$osm_lines)
# # Find the closest node to each station
# nodeid <- stplanr::find_network_nodes (la_net, stns$longitude, stns$latitude)
# # Convert start and end station IDs in trips table to node IDs in `la_net`
# startid <- nodeid [match (ntrips$start_station_id, stns$stn_id)]
# endid <- nodeid [match (ntrips$end_station_id, stns$stn_id)]
# ntrips$start_station_id <- startid
# ntrips$end_station_id <- endid
## ---- eval = FALSE------------------------------------------------------------
# bike_usage <- stplanr::sum_network_links (la_net, data.frame (ntrips))
## ----plot-tmat, eval = FALSE--------------------------------------------------
# tmap::tm_shape (bike_usage, xlim = xlims, ylim = ylims, is.master=TRUE) +
# tmap::tm_lines (col="numtrips", lwd="numtrips", title.col = "Number of trips",
# breaks = c(0, 200, 400, 600, 800, 1000, Inf),
# legend.lwd.show = FALSE, scale = 5) +
# tmap::tm_layout (bg.color="gray95", legend.position = c ("right", "bottom"),
# legend.bg.color = "white", legend.bg.alpha = 0.5)
# #tmap::save_tmap (filename = "la_map.png")
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