enigma
An R client for Enigma.io
Enigma holds government data and provides a really nice set of APIs for data, metadata, and stats on each of the datasets. That is, you can request a dataset itself, metadata on the dataset, and summary statistics on the columns of each dataset.
Enigma.io
License
MIT, see LICENSE file and MIT text
Install
Stable version from CRAN
install.packages("enigma")Or development version from GitHub
devtools::install_github("ropengov/enigma")library("enigma")Get data
out <- enigma_data(
dataset = 'us.gov.whitehouse.visitor-list',
select = c('namelast', 'visitee_namelast', 'last_updatedby')
)Some metadata on the results
out$info
#> $rows_limit
#> [1] 500
#>
#> $total_results
#> [1] 5994713
#>
#> $total_pages
#> [1] 11990
#>
#> $current_page
#> [1] 1
#>
#> $calls_remaining
#> [1] 49764
#>
#> $seconds_remaining
#> [1] 957301Look at the data, first 6 rows for readme brevity
head(out$result)
#> # A tibble: 6 × 3
#> namelast visitee_namelast last_updatedby
#> <chr> <chr> <chr>
#> 1 Adamopoulos <NA> <NA>
#> 2 Brosman <NA> <NA>
#> 3 Brumfield <NA> <NA>
#> 4 Chipman <NA> <NA>
#> 5 Chubb <NA> <NA>
#> 6 Colasante <NA> <NA>Statistics on dataset columns
out <- enigma_stats(
dataset = 'us.gov.whitehouse.visitor-list',
select = 'total_people'
)Some summary stats
out$result[c('sum','avg','stddev','variance','min','max')]
#> $sum
#> [1] "1626083121"
#>
#> $avg
#> [1] "272.5916137604454583"
#>
#> $stddev
#> [1] "599.377962130311"
#>
#> $variance
#> [1] "359253.941487484525"
#>
#> $min
#> [1] "0"
#>
#> $max
#> [1] "5730"Frequency details
head(out$result$frequency)
#> total_people count
#> 1 1 286296
#> 2 6 224602
#> 3 2 197491
#> 4 4 181489
#> 5 3 160771
#> 6 5 151562Metadata on datasets
out <- enigma_metadata(dataset = 'us.gov.whitehouse')Paths
out$info$paths
#> [[1]]
#> [[1]]$level
#> [1] "us"
#>
#> [[1]]$label
#> [1] "United States"
#>
#> [[1]]$description
#> [1] "Data concerning, or published by, the federal government of the United States of America."
#>
#> [[1]]$description_lead
#> [1] "Data concerning, or published by, the federal government of the United States of America."
#>
#> [[1]]$citations
#> list()
#>
#>
#> [[2]]
#> [[2]]$level
#> [1] "gov"
#>
#> [[2]]$label
#> [1] "U.S. Federal Government"
#>
#> [[2]]$description
#> [1] "Government from the Legislative, Executive, and Judicial branches of the United States of America."
#>
#> [[2]]$description_lead
#> [1] "Government comprising the Legislative, Executive, and Judicial branches of the United States of America."
#>
#> [[2]]$citations
#> list()
#>
#>
#> [[3]]
#> [[3]]$level
#> [1] "whitehouse"
#>
#> [[3]]$label
#> [1] "The White House"
#>
#> [[3]]$description
#> [1] "Located at 1600 Pennsylvania Avenue in Washington D.C., the White House has served as the home and office for every U.S. president since John Adams."
#>
#> [[3]]$description_lead
#> [1] "Located at 1600 Pennsylvania Avenue in Washington D.C., the White House has served as the home and office for every U.S. president since John Adams."
#>
#> [[3]]$citations
#> list()Immediate nodes
out$info$immediate_nodes
#> [[1]]
#> [[1]]$datapath
#> [1] "us.gov.whitehouse.salaries"
#>
#> [[1]]$label
#> [1] "White House Salaries"
#>
#> [[1]]$description
#> [1] "The White House has been required to deliver a report to Congress listing the title and salary of every White House Office employee since 1995. Consistent with President Obama's commitment to transparency, this report is being publicly disclosed on our website as it is transmitted to Congress. In addition, this report also contains the title and salary details of administration officials who work at the Office of Policy Development, including the Domestic Policy Council and the National Economic Council -- along with White House Office employees."Children tables
out$info$children_tables[[1]]
#> $datapath
#> [1] "us.gov.whitehouse.visitor-list"
#>
#> $label
#> [1] "White House Visitor Records"
#>
#> $description
#> [1] "Records of visitors to the White House from September 2009 to present."
#>
#> $db_boundary_datapath
#> [1] "us.gov.whitehouse"
#>
#> $db_boundary_label
#> [1] ""Use case: Plot frequency of flight distances
First, get columns for the air carrier dataset
dset <- 'us.gov.dot.rita.trans-stats.air-carrier-statistics.t100d-market-all-carrier'
head(enigma_metadata(dset)$columns$table[,c(1:4)])
#> id label type index
#> 1 passengers Passengers type_numeric 0
#> 2 freight Freight (Lbs.) type_numeric 1
#> 3 mail Mail (Lbs.) type_numeric 2
#> 4 distance Distance (Mi.) type_numeric 3
#> 5 unique_carrier Unique Carrier type_varchar 4
#> 6 airline_id Airline ID type_varchar 5Looks like there's a column called distance that we can search on. We by default for varchar type columns only frequency bake for the column.
out <- enigma_stats(dset, select = 'distance')
head(out$result$frequency)
#> distance count
#> 1 0.00 16456
#> 2 296.00 13595
#> 3 59.00 13504
#> 4 16.00 13101
#> 5 95.00 12669
#> 6 94.00 12354Then we can do a bit of tidying and make a plot
library("ggplot2")
df <- out$result$frequency
df <- data.frame(distance = as.numeric(df$distance),
count = as.numeric(df$count))
ggplot(df, aes(distance, count)) +
geom_bar(stat = "identity") +
geom_point() +
theme_grey(base_size = 18) +
labs(y = "flights", x = "distance (miles)")Direct dataset download
Enigma provides an endpoint .../export/<datasetid> to download a zipped csv file of the entire dataset.
enigma_fetch() gives you an easy way to download these to a specific place on your machine. And a message tells you that a file has been written to disk.
enigma_fetch(dataset='com.crunchbase.info.companies.acquisition')Meta
- Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.