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https://github.com/gvegayon/googlepublicdata
An R package to build Google's Public Data Explorer DSPL Metadata files
https://github.com/gvegayon/googlepublicdata
dspl gapminder google google-public-data r-package xml
Last synced: 4 months ago
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An R package to build Google's Public Data Explorer DSPL Metadata files
- Host: GitHub
- URL: https://github.com/gvegayon/googlepublicdata
- Owner: gvegayon
- License: other
- Created: 2015-03-24T15:19:43.000Z (almost 10 years ago)
- Default Branch: master
- Last Pushed: 2021-06-06T07:25:52.000Z (over 3 years ago)
- Last Synced: 2024-09-26T15:47:57.072Z (5 months ago)
- Topics: dspl, gapminder, google, google-public-data, r-package, xml
- Language: R
- Homepage:
- Size: 1.25 MB
- Stars: 8
- Watchers: 2
- Forks: 3
- Open Issues: 1
-
Metadata Files:
- Readme: readme.md
- Changelog: ChangeLog
- License: LICENSE
Awesome Lists containing this project
README
googlePublicData
================An *R* package for building *Google's* *Data Sets Publication Language* (DSPL) metadata files used in *Public Data Explorer*.
[](http://cran.rstudio.com/package=googlePublicData) [](https://travis-ci.org/gvegayon/googlePublicData) [](https://ci.appveyor.com/project/gvegayon/googlePublicData) [](https://codecov.io/gh/gvegayon/googlePublicData)
[](https://cran.r-project.org/package=googlePublicData)Features:
- Reads tab, csv, xls and xlsx from a folder.
- Identifies data types and distinguishes between dimensional and metric concepts.
- Identifies dimensional data tabs.
- Auto generates conceps id.
- Auto data sorting on dimensional (no time) concepts.
- Prints XML and csv files to upload to Public Data Explorer.
- Some bug trackers before final printing XML.
- Builds ZIP file containing CSV and XML files.
So you don't need to mess with the XML coding at all!
``` r
library(googlePublicData)# This path has some csv files that we will use
data.path <-try(paste(.libPaths()[1],'/googlePublicData/data',sep=''), silent=T)
data.path
```## [1] "/home/george/R/x86_64-pc-linux-gnu-library/3.4/googlePublicData/data"
``` r
# The dspl function looks for csv files in that paths, and analyzes them
mydspl <- dspl(path=data.path, sep=";")
```## 6 files found...
## /home/george/R/x86_64-pc-linux-gnu-library/3.4/googlePublicData/data/countries.csv analyzed correctly
## /home/george/R/x86_64-pc-linux-gnu-library/3.4/googlePublicData/data/country_slice.csv analyzed correctly
## /home/george/R/x86_64-pc-linux-gnu-library/3.4/googlePublicData/data/gender_country_slice.csv analyzed correctly
## /home/george/R/x86_64-pc-linux-gnu-library/3.4/googlePublicData/data/genders.csv analyzed correctly
## /home/george/R/x86_64-pc-linux-gnu-library/3.4/googlePublicData/data/states.csv analyzed correctly
## /home/george/R/x86_64-pc-linux-gnu-library/3.4/googlePublicData/data/state_slice.csv analyzed correctly
``` r
# If we wanted to write the zip file... ready to be uploaded to
# http://publicdata.google.com
# dspl(path=data.path, sep=";", output= "mydspl.zip")# Printing the data
mydspl
```##
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## No description
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## Country
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## Population
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##``` r
# Summary of the dspl class object
summary(mydspl)
```## Attributes
## $names
## [1] "dspl" "concepts.by.table" "dimtabs"
## [4] "slices" "concepts" "dimentions"
## [7] "statistics"
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## $class
## [1] "dspl"
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## Dataset contents## $dimtabs
## [1] "countries" "genders" "states"
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## $slices
## [1] "countries" "country_slice" "gender_country_slice"
## [4] "genders" "states" "state_slice"
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## $concepts
## [1] "Country" "name" "latitude"
## [4] "longitude" "Year" "Population"
## [7] "Gender" "State" "Unemployment Rate"
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## $dimentions
## label
## 1 Country
## 12 Gender
## 14 State
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## $statistics
## slices concepts dimentions
## [1,] 6 9 3