,
Juuso Parkkinen [aut],
Joona Lehtomaki [aut],
Pyry Kantanen [aut] | Title: | Functions for Finnish Open Data |
|---|---|
| Description: | Misc support functions for rOpenGov and open data downloads. |
| Authors: | Leo Lahti [aut, cre] ,
Juuso Parkkinen [aut],
Joona Lehtomaki [aut],
Pyry Kantanen [aut] |
| Maintainer: | Leo Lahti <[email protected]> |
| License: | BSD_2_clause + file LICENSE |
| Version: | 0.8.21 |
| Built: | 2024-09-14 02:51:26 UTC |
| Source: | https://github.com/rOpenGov/sorvi |
The sorvi package hosts various functions that are mainly helpful in rOpenGov package maintenance, package authoring and drawing graphs for presentations. Additionally it has some functions that do not (yet) have their own package but are useful in some contexts.
Leo Lahti, Juuso Parkkinen, Jussi Paananen, Joona Lehtomaki, Einari Happonen, Juuso Haapanen, and Pyry Kantanen [email protected]
See citation("sorvi") https://github.com/rOpenGov/sorvi
library(sorvi)library(sorvi)
Produces a tibble or a visualization of package download statistics.
cran_downloads( pkgs = "all", output = "tibble", sum = "by_month", plot.scale = 11, use.cache = TRUE )cran_downloads( pkgs = "all", output = "tibble", sum = "by_month", plot.scale = 11, use.cache = TRUE )
pkgs |
Package name(s). Default is "all", which prints statistics for all rOpenGov packages. You can also input 1 or more package names as a vector. |
output |
"tibble" (default) or "plot". With sum "by_month" and "by_year" "plot" outputs a line chart, with "total" it outputs a bar chart. |
sum |
"by_month" (default), "by_year" or "total" |
plot.scale |
integer, default is 11. Smaller numbers decrease the size of plot elements, larger numbers make them larger. |
use.cache |
Cache downloaded statistics. Default is TRUE |
This function is intended for easy retrieval and visualization of rOpenGov package download statistics from CRAN. It is an evolution of an R script by antagomir. As such it retains some features that were present in the original R script and were deemed useful for rOpenGov's internal use. This function may or may not be useful in other instances.
tibble or a ggplot2 line chart or a bar chart
Leo Lahti, Pyry Kantanen <[email protected]>
## Not run: df <- cran_downloads(pkgs = "eurostat", sum = "total", use.cache = FALSE) kable(df) ## Compare two packages p1 <- cran_downloads(pkgs = "eurostat", sum = "by_year", output = "plot") p2 <- cran_downloads(pkgs = "osmar", sum = "by_year", output = "plot") gridExtra::grid.arrange(p1, p2, nrow = 2) ## End(Not run)## Not run: df <- cran_downloads(pkgs = "eurostat", sum = "total", use.cache = FALSE) kable(df) ## Compare two packages p1 <- cran_downloads(pkgs = "eurostat", sum = "by_year", output = "plot") p2 <- cran_downloads(pkgs = "osmar", sum = "by_year", output = "plot") gridExtra::grid.arrange(p1, p2, nrow = 2) ## End(Not run)
Download chart position data from ifpi.fi
get_ifpi_charts(channel = "radio", year = NA, week = NA)get_ifpi_charts(channel = "radio", year = NA, week = NA)
channel |
Options: "radio", "albumit", "singlet", "fyysiset-albumit" |
year |
year as numeric. Default is NA, returning charts from current year. Charts are available from 2014 onwards. |
week |
week as numeric. Default is NA, returning most last possible charts. Week cannot be the current week. Please note that number of weeks differ between years. For simplicity's sake valid weeks are set to be between 1 and 53. Use e.g. 'lubridate::isoweek' to check how many weeks a given year has. |
Web scraping function that is inspired by Sauravkaushik8 Kaushik's blog post "Beginner's Guide on Web Scraping in R" on analyticsvidhya.com. Downloads chart data from Musiikkituottajat - IFPI Finland ry website. Please note that this function works only with IFPI Finland website!
The output has the following columns:
rank: Rank on chart
artist: Artist name
song_title: Song title
rank_last_week: Rank on chart on the previous week. RE if the song has re-entered the chart
chart_woc: Weeks on chart
week: Week number of observation
year: Year of observation
tibble
Pyry Kantanen <[email protected]>
Original tutorial in https://www.analyticsvidhya.com/blog/2017/03/beginners-guide-on-web-scraping-in-r-using-rvest-with-hands-on-knowledge/
From a larger dataset containing historical municipalities, pick a certain year and return an output that contains the most recent information on each municipality.
get_municipalities(year = 2002, type = "sf")get_municipalities(year = 2002, type = "sf")
year |
a year between 1865-2020 |
type |
either "data.frame", "tibble" or "sf" |
See dataset "kunnat1865_2021"
a data.frame or sf object
Pyry Kantanen
Data attribution: FinnONTO Consortium: https://seco.cs.aalto.fi/projects/finnonto/
Get statistics about GitHub issues from GitHub API.
gh_issue_stats( owner = "ropengov", repo = "geofi", issue.type = NA, time.from = NA, time.to = NA )gh_issue_stats( owner = "ropengov", repo = "geofi", issue.type = NA, time.from = NA, time.to = NA )
owner |
Repository owner / organization. Default is "ropengov" |
repo |
Repository name. Default is "geofi" |
issue.type |
Type of issues printed: "issue", "PR" or NA printing all (default). |
time.from |
Start date in ISO 8601 format: YYYY-MM-DDTHH:MM:SSZ. Default is "2010-09-01T00:00:00Z". |
time.to |
End date in ISO 8601 format: YYYY-MM-DDTHH:MM:SSZ. Default
is |
This function is intended for easy information retrieval about rOpenGov package issues and pull requests. More specifically, this function returns a tibble containing information on issue id, title, status (open or closed), number of comments, who opened it, when it was created, what was the openers status (rOpenGov organization member, package contributor or a regular user who opened e.g. a bug issue) and what is the type of the issue.
GitHub Issues API handles Pull Requests and Issues similarly and therefore this function returns both types by default. Different types of issues can be filtered by using the issue.type parameter.
Kudos for this function go to Jennifer Bryan. The changes made here are mostly related to adding additional fields (opener_type, issue_type) to the output tibble and writing a function around these original contributions. The scope of this function is to mainly help rOpenGov team analyze the type of user feedback we get via GitHub issues and therefore the scope of this function is very limited.
tibble
Original scripts by Jennifer Bryan (jennybc), function by Pyry Kantanen <[email protected]>
GitHub Issues API documentation: https://docs.github.com/en/rest/reference/issues
Original "analyze GitHub stuff with R" repository: https://github.com/jennybc/analyze-github-stuff-with-r
A dataset containing information about each instance of individual municipalities.
kunnat1865_2021kunnat1865_2021
A simple feature with 1337 rows and 10 variables:
Universal Resource Identifier (URI) for each municipality instance in time. For example: http://www.yso.fi/onto/sapo/Maalahti(1908-1972)
Municipality code, a unique number assigned for each municipality that stays the same as long as the municipality exists. For example: "475"
The official name of the municipality in Finnish. For example: Maalahti
The official name of the municipality in Swedish. For example: Malax
Start year of the municipality instance, e.g. founding year. For example: 1865
End year of the municipality instance, can be NA if still valid. For example: 1972
Area of the municipality, in square kilometers. For example 185.00
A description of the change that occurred at the beginning of this specific instance. For example: "Ahlainen erotettiin Ulvilasta 1908"
Type of the change. For example: "Jakaantuminen"
Identifiers for the changes that have happened, which can be used to link past and future instances of municipalities together. For example: "Jakaantuminen1534, Jakaantuminen2"
Most of the Finnish municipalities were formed after 1865 decree on municipal governance in the country Asetus kunnallishallituksesta maalla 1865 but the dataset contains some municipalities that were allegedly formed even before that. There are two instances of "illegal municipalities" (Mustio and Rutakko) that were not recognized as actual municipalities but functioned as such in late 1800s and early 1900s.
Raw data downloaded from ONKI.fi website on 04 Aug 2022: http://onki.fi/en/browser/overview/sapo Data attribution: FinnONTO Consortium: https://seco.cs.aalto.fi/projects/finnonto/
Information on abolished municipalities and municipality name changes from Statistics Finland website: Municipalities and regional divisions based on municipalities in files and classification publications
Load custom data sets.
load_sorvi_data(data.id, verbose = TRUE)load_sorvi_data(data.id, verbose = TRUE)
data.id |
data ID to download (see details) |
verbose |
verbose |
The following data sets are available:
translation_provincesTranslation of Finnish province (maakunta) names (Finnish, English).
Data set. The format depends on the data.
Leo Lahti [email protected]
See citation("sorvi")
translations <- load_sorvi_data("translation_provinces")translations <- load_sorvi_data("translation_provinces")
A simple feature containing the URIs, municipality codes and geometries of municipalities in time. The starting point and end point of each municipality can be determined by combining polygons1909_2009 with another dataset that contains such information.
polygons1909_2009polygons1909_2009
A simple feature with 860 rows and 3 variables:
Universal Resource Identifier (URI) for each municipality instance in time. For example: http://www.yso.fi/onto/sapo/Maalahti(1908-1972)
Municipality code, a unique 3-digit code (001-999) assigned for each municipality that stays the same as long as the municipality exists. For example: "475"
A single list column with geometries
Original data downloaded from ONKI.fi website on 04 Aug 2022: http://onki.fi/en/browser/overview/sapo Data attribution: FinnONTO Consortium: https://seco.cs.aalto.fi/projects/finnonto/