opendatatoronto 
opendatatoronto is an R interface to the City of Toronto Open Data
Portal. The goal of the package is to help
read data directly into R without needing to manually download it via
the portal.
For more information, please visit the package website and vignettes:
- Introduction to
opendatatoronto - Retrieving multi-sheet XLS/XLSX resources
- Retrieving multi-file ZIP resources
- Retrieving multiple resources using
purrr - Working with spatial data from the portal
Installation
You can intall the released version of opendatatoronto from CRAN:
install.packages("opendatatoronto")or the development version from GitHub with:
# install.packages("devtools")
devtools::install_github("sharlagelfand/opendatatoronto")Usage
In the Portal, datasets are called packages. You can see a list of
available packages by using list_packages(). This will show metadata
about the package, including what topics (i.e. tags) the package covers,
any civic issues it addresses, a description of it, how many resources
there are (and their formats), how often it is is refreshed and when it
was last refreshed.
library(opendatatoronto)
packages <- list_packages(limit = 10)
packages
#> # A tibble: 10 x 10
#> title id topics civic_issues excerpt dataset_category num_resources
#> <chr> <chr> <chr> <chr> <chr> <chr> <int>
#> 1 Body… c405… City … <NA> "This … Table 2
#> 2 Stre… 1db3… City … Mobility "Trans… Map 1
#> 3 Stre… 74f6… City … <NA> "Publi… Map 1
#> 4 Stre… 821f… City … <NA> "Publi… Map 1
#> 5 Stre… ccfd… City … <NA> "Poste… Map 1
#> 6 Stre… cf70… City … <NA> "Poste… Map 1
#> 7 Stre… 99b1… City … <NA> "Infor… Map 1
#> 8 Stre… 71e6… Trans… <NA> "Bike … Map 1
#> 9 Stre… 0c4e… City … <NA> "Bench… Map 1
#> 10 Poll… 7bce… City … <NA> "Polls… Table 2
#> # … with 3 more variables: formats <chr>, refresh_rate <chr>,
#> # last_refreshed <date>You can also search packages by title:
ttc_packages <- search_packages("ttc")
ttc_packages
#> # A tibble: 14 x 10
#> title id topics civic_issues excerpt dataset_category num_resources
#> <chr> <chr> <chr> <chr> <chr> <chr> <int>
#> 1 TTC … 7795… Trans… Mobility "Data … Document 1
#> 2 TTC … 996c… Trans… Mobility "TTC S… Document 35
#> 3 TTC … b68c… Trans… Mobility "TTC S… Document 7
#> 4 TTC … e271… Trans… Mobility "TTC B… Document 7
#> 5 TTC … aedd… Trans… Mobility "This … Website 2
#> 6 TTC … 1444… Trans… Mobility "This … Website 2
#> 7 TTC … 4b80… Trans… Mobility "This … Website 2
#> 8 TTC … d2a7… Trans… Mobility "This … Website 2
#> 9 TTC … d9dc… Trans… Mobility "This … Document 1
#> 10 TTC … ef35… Trans… Mobility "This … Document 1
#> 11 TTC … 2c4c… Finan… Mobility,Fi… "This … Website 2
#> 12 TTC … 4eb6… Trans… Mobility "This … Document 5
#> 13 TTC … c01c… <NA> Mobility "This … Document 1
#> 14 TTC … 8217… Trans… Mobility "The N… Document 1
#> # … with 3 more variables: formats <chr>, refresh_rate <chr>,
#> # last_refreshed <date>Or see metadata for a specific package:
show_package("996cfe8d-fb35-40ce-b569-698d51fc683b")
#> # A tibble: 1 x 10
#> title id topics civic_issues excerpt dataset_category num_resources formats
#> <chr> <chr> <chr> <chr> <chr> <chr> <int> <chr>
#> 1 TTC … 996c… Trans… Mobility TTC Su… Document 35 XLSX
#> # … with 2 more variables: refresh_rate <chr>, last_refreshed <date>Within a package, there are a number of resources - e.g. CSV, XSLX, JSON, SHP files, and more. Resources are the actual “data”.
For a given package, you can get a list of resources using
list_package_resources(). You can pass it the package id (which is
contained in marriage_license_packages
below):
marriage_licence_packages <- search_packages("Marriage Licence Statistics")
marriage_licence_resources <- marriage_licence_packages %>%
list_package_resources()
marriage_licence_resources
#> # A tibble: 1 x 4
#> name id format last_modified
#> <chr> <chr> <chr> <date>
#> 1 Marriage Licence Statistic… 4d985c1d-9c7e-4f74-9864-7321… CSV 2020-02-01But you can also get a list of resources by using the package’s URL from the Portal:
list_package_resources("https://open.toronto.ca/dataset/sexual-health-clinic-locations-hours-and-services/")
#> # A tibble: 2 x 4
#> name id format last_modified
#> <chr> <chr> <chr> <date>
#> 1 sexual-health-clinic-locations-ho… e958dd45-9426-4298-ac… XLSX 2019-08-15
#> 2 Sexual-health-clinic-locations-ho… 2edcc4a3-c095-4ce3-b0… XLSX 2019-08-15Finally (and most usefully!), you can download the resource (i.e., the
actual data) directly into R using get_resource():
marriage_licence_statistics <- marriage_licence_resources %>%
get_resource()
marriage_licence_statistics
#> # A tibble: 436 x 4
#> `_id` CIVIC_CENTRE MARRIAGE_LICENSES TIME_PERIOD
#> <int> <chr> <int> <chr>
#> 1 2941 ET 80 2011-01
#> 2 2942 NY 136 2011-01
#> 3 2943 SC 159 2011-01
#> 4 2944 TO 367 2011-01
#> 5 2945 ET 109 2011-02
#> 6 2946 NY 150 2011-02
#> 7 2947 SC 154 2011-02
#> 8 2948 TO 383 2011-02
#> 9 2949 ET 177 2011-03
#> 10 2950 NY 231 2011-03
#> # … with 426 more rows