---
title: "Ford Go Bike API"
output:
  html_notebook: default
  pdf_document: default
  word_document: default
---

[General Bikeshare Feed Specification (GBFS)](https://github.com/NABSA/gbfs/blob/master/gbfs.md)

R Package that connects to the GBFS API

[R gbfs](https://github.com/ds-civic-data/gbfs)

North American Bike Share Association

[NBSA](https://github.com/NABSA) [system.csv](https://github.com/NABSA/gbfs/blob/master/systems.csv)



```{r, eval=FALSE}
# library(devtools)

# install_github("ds-civic-data/gbfs")
```

```{r message=FALSE}
library(gbfs)
library(tidyverse)
library(ggmap)
```

```{r}
get_gbfs_cities() %>% filter(Location == "San Francisco Bay Area, CA")

get_gbfs(city = "https://gbfs.baywheels.com/gbfs/gbfs.json", feeds = "dynamic", directory = "pdx_gbfs")

get_gbfs(city = "https://gbfs.baywheels.com/gbfs/gbfs.json", feeds = "static", directory = "pdx_gbfs")  # there is an error in this function.

list.files("pdx_gbfs")




```

```{r}
station_information <- readRDS("pdx_gbfs/station_information.rds")
head(station_information)

station_information %>% ggplot(aes(x=lon, y=lat, color=region_id)) + geom_point()

```

East Bay

```{r}
station_information <- readRDS("pdx_gbfs/station_information.rds")
head(station_information)

station_information %>% ggplot(aes(x=lon, y=lat)) + 
  geom_point() +
  scale_colour_gradient(low = "orange", high = "blue")

```

Oakland

```{r}
head(station_information)

```

Near real time data

```{r}
station_status <- readRDS("pdx_gbfs/station_status.rds")
head(station_status)
#tail(station_status) 
#dim(station_status)

#head(oakland.stations)
#dim(oakland.stations)

station_status %>% count(station_id)


station_information_02 <- station_information %>% left_join(station_status, by = "station_id" )
  
#head(oakland.status)
#tail(oakland.status)
#dim(oakland.status)

station_information_02 %>% 
  summarise(n=n(),mean=mean(num_bikes_available),min=min(num_bikes_available),max=max(num_bikes_available)) 

station_information_02 %>% group_by(name) %>%
  summarise(n=n(),mean=mean(num_bikes_available),min=min(num_bikes_available),max=max(num_bikes_available)) 

```

```{r}
system_information <- readRDS("pdx_gbfs/system_information.rds")
system_information %>% 
  head() 
```