## ----include = FALSE---------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) ## ----setup-------------------------------------------------------------------- knitr::opts_chunk$set(warning = FALSE, message = FALSE) library(mtaOpenData) library(ggplot2) library(dplyr) ## ----mta-list-datasets-------------------------------------------------------- mta_list_datasets() |> head() ## ----mta-pull----------------------------------------------------------------- mta_bus_stops_id <- mta_pull_dataset( dataset = "2ucp-7wg5", limit = 2) mta_bus_stops_key <- mta_pull_dataset( dataset = "mta_bus_stops", limit = 2) ## ----filter-qm15-------------------------------------------------------------- qm15_info <- mta_pull_dataset(dataset = "2ucp-7wg5",limit = 2, filters = list(route_id = "QM15")) qm15_info # Checking to see the filtering worked qm15_info |> distinct(route_id) ## ----tbl-qm15-17-info--------------------------------------------------------- qm15_17_info <- mta_pull_dataset(dataset = "2ucp-7wg5",limit = 2, filters = list(route_id = c("QM15","QM17"))) qm15_17_info ## ----tbl-qm15-17-info-in-effect----------------------------------------------- qm15_17_info_in_effect <- mta_pull_dataset(dataset = "2ucp-7wg5",limit = 2, filters = list(route_id = c("QM15","QM17"), in_effect = "true")) qm15_17_info_in_effect ## ----compaint-type-graph, fig.alt="Horizontal bar chart displaying the distribution of NYC bus route directions. The y-axis lists directions (e.g., Northbound, Southbound), and the x-axis shows the frequency of routes currently in effect for each. Bars are ordered by frequency to highlight which directions are most common in the dataset.", fig.cap="Distribution of active NYC bus route directions. Data retrieved via the mtaOpenData package from the MTA Bus Route info dataset (ID: 2ucp-7wg5).", fig.height=5, fig.width=7---- # Visualizing the distribution, ordered by frequency mta_bus_info <- mta_pull_dataset(dataset = "2ucp-7wg5", filters = list(in_effect = "true")) mta_bus_info |> count(direction) |> ggplot(aes( x = n, y = reorder(direction, n) )) + geom_col(fill = "steelblue") + theme_minimal() + labs( title = "Top Directions NYC Buses Go On Their Routes", x = "Count", y = "Direction" )