Readme.md

r511 Readme

Tom Buckley 7/9/2018

Installation

Until the package is published on CRAN, you can install this package from GitHub using the devtools package:

if (!require(devtools)) {
    install.packages('devtools')
}
devtools::install_github('r-gtfs/r511')

Usage

• Set your api key as an environmental variable
• Get MTC 511 Operator List
• Get URL for GTFS Data
• Import Data
• Example: Summarise Stops Per Route

Set your api key as an environmental variable

If you don't have a key, you can get one here: https://511.org/developers/list/tokens/create

#Sys.setenv(APIKEY511="yourkeyhere")

Get MTC 511 Operator List

This function pulls a list of operator names, modes, and private codes. The latter we use to make requests for GTFS data.

operator_df <- get_511_metadata()
head(operator_df)
#> # A tibble: 6 x 3
#>   privatecode name                      primarymode
#>   <chr>       <chr>                     <chr>      
#> 1 5E          511 Emergency             other      
#> 2 5F          511 Flap Sign             other      
#> 3 5O          511 Operations            other      
#> 4 5S          511 Staff                 other      
#> 5 AC          AC Transit                bus        
#> 6 CE          Altamont Corridor Express rail

Get URL for GTFS Data

You can use the get_511_url() function to build a URL from which you can directly download GTFS data for an operator.

bart_code <- operator_df[operator_df$name=='Bay Area Rapid Transit',]$privatecode
bart_gtfs_url <- get_511_url(bart_code)

Import Data

Using trread, load BART data into R as a list of dataframes.

library(trread)
bart_gtfs_data <- import_gtfs(bart_gtfs_url)
#>  [1] "agency.txt"              "calendar_attributes.txt"
#>  [3] "calendar_dates.txt"      "calendar.txt"           
#>  [5] "directions.txt"          "fare_attributes.txt"    
#>  [7] "fare_rules.txt"          "farezone_attributes.txt"
#>  [9] "feed_info.txt"           "rider_categories.txt"   
#> [11] "routes.txt"              "shapes.txt"             
#> [13] "stop_times.txt"          "stops.txt"              
#> [15] "trips.txt"

Example: Summarise Stops Per Route

Summarise the number of stops per route on BART.

library(dplyr)
attach(bart_gtfs_data)

routes_df %>% inner_join(trips_df, by="route_id") %>%
  inner_join(stop_times_df, by="trip_id") %>% 
    inner_join(stops_df, by="stop_id") %>% 
      group_by(route_long_name) %>%
        summarise(stop_count=n_distinct(stop_id)) %>%
  arrange(desc(stop_count))
#> # A tibble: 6 x 2
#>   route_long_name                        stop_count
#>   <chr>                                       <int>
#> 1 Antioch - SFIA/Millbrae                        28
#> 2 Richmond - Daly City/Millbrae                  23
#> 3 Warm Springs/South Fremont - Daly City         20
#> 4 Warm Springs/South Fremont - Richmond          19
#> 5 Dublin/Pleasanton - Daly City                  18
#> 6 Oakland Airport - Coliseum                      2