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rsunlight - R client for Sunlight Labs APIs

    R API government
 Source: .Rmd/.md

My last blog post on this package was so long ago the package wrapped both New York Times APIs and Sunlight Labs APIs and the package was called govdat. I split that package up into rsunlight for Sunlight Labs APIs and rtimes for some New York Times APIs. rtimes is in development at Github.

We’ve updated the package to include four sets of functions, one set for each of four Sunlight Labs APIs (with a separate prefix for each API):

Then there are many methods for each API.

rsunlight intro

Installation

First, installation

devtools::install_github("ropengov/rsunlight")

Load the library

library("rsunlight")

Congress API

Search for Fed level bills that include the term health care in them.

res <- cg_bills(query='health care')
head(res$results[,1:4])
##          nicknames congress last_version_on sponsor_id
## 1        obamacare      111      2010-08-25    S000749
## 2 obamacare, ppaca      111      2010-08-25    R000053
## 3             NULL      113      2013-10-09    K000220
## 4             NULL      111      2009-01-06    I000056
## 5             NULL      112      2011-01-05    I000056
## 6             NULL      111      2009-05-05    D000197

Search for bills that have the two terms transparency and accountability within 5 words of each other in the bill.

res <- cg_bills(query='transparency accountability'~5)
head(res$results[,1:4])
##   congress last_version_on sponsor_id
## 1      111      2009-01-15    R000435
## 2      113      2013-07-17    R000595
## 3      112      2011-12-08    R000435
## 4      113      2013-09-19    R000435
## 5      112      2011-11-10    R000595
## 6      113      2013-07-23    C000560
##                                       urls.govtrack
## 1   http://www.govtrack.us/congress/bills/111/hr557
## 2  https://www.govtrack.us/congress/bills/113/s1313
## 3  http://www.govtrack.us/congress/bills/112/hr2829
## 4 https://www.govtrack.us/congress/bills/113/hr3155
## 5   http://www.govtrack.us/congress/bills/112/s1848
## 6  https://www.govtrack.us/congress/bills/113/s1347
##                                 urls.opencongress
## 1  http://www.opencongress.org/bill/111-h557/show
## 2      http://www.opencongress.org/bill/s1313-113
## 3 http://www.opencongress.org/bill/112-h2829/show
## 4     http://www.opencongress.org/bill/hr3155-113
## 5 http://www.opencongress.org/bill/112-s1848/show
## 6      http://www.opencongress.org/bill/s1347-113
##                                          urls.congress
## 1   http://beta.congress.gov/bill/111th/house-bill/557
## 2 http://beta.congress.gov/bill/113th/senate-bill/1313
## 3  http://beta.congress.gov/bill/112th/house-bill/2829
## 4  http://beta.congress.gov/bill/113th/house-bill/3155
## 5 http://beta.congress.gov/bill/112th/senate-bill/1848
## 6 http://beta.congress.gov/bill/113th/senate-bill/1347

Open States API

Search State Bills, in this case search for the term agriculture in Texas.

res <- os_billsearch(terms = 'agriculture', state = 'tx')
head(res)
##                                                                                                                                                 title
## 1 Relating to authorizing the issuance of revenue bonds to fund capital projects at public institutions of higher education; making an appropriation.
## 2                          Relating to authorizing the issuance of revenue bonds to fund capital projects at public institutions of higher education.
## 3                          Relating to authorizing the issuance of revenue bonds to fund capital projects at public institutions of higher education.
## 4                          Relating to authorizing the issuance of revenue bonds to fund capital projects at public institutions of higher education.
## 5 Relating to authorizing the issuance of revenue bonds to fund capital projects at public institutions of higher education; making an appropriation.
## 6                                Relating to access to certain facilities by search and rescue dogs and their handlers; providing a criminal penalty.
##            created_at          updated_at          id chamber state
## 1 2013-08-01 03:33:40 2013-08-07 03:10:10 TXB00034894   upper    tx
## 2 2013-08-01 03:33:38 2013-08-02 03:20:14 TXB00034893   upper    tx
## 3 2013-07-21 03:03:53 2013-07-28 03:28:30 TXB00034814   upper    tx
## 4 2013-07-03 02:44:03 2013-07-14 03:00:31 TXB00034514   upper    tx
## 5 2013-06-16 03:48:13 2013-06-23 04:02:49 TXB00033988   upper    tx
## 6 2013-03-03 04:47:26 2013-07-01 21:25:36 TXB00027556   upper    tx
##   session type
## 1     833 bill
## 2     833 bill
## 3     832 bill
## 4     832 bill
## 5     831 bill
## 6      83 bill
##                                                                             subjects
## 1                                   Commerce, Education, Budget, Spending, and Taxes
## 2                                   Commerce, Education, Budget, Spending, and Taxes
## 3                                   Commerce, Education, Budget, Spending, and Taxes
## 4                                   Commerce, Education, Budget, Spending, and Taxes
## 5                                   Commerce, Education, Budget, Spending, and Taxes
## 6 Commerce, Business and Consumers, Animal Rights and Wildlife Issues, Health, Crime
##   bill_id
## 1    SB 3
## 2   SB 10
## 3   SB 40
## 4    SB 6
## 5   SB 44
## 6 SB 1010

Search for legislators in California (ca) and in the democratic party

res <- os_legislatorsearch(state = 'ca', party = 'democratic', fields = c('full_name','+capitol_office.phone'))
head(res)
##            phone        id       full_name
## 1 (916) 319-2014 CAL000058   Nancy Skinner
## 2 (916) 319-2015 CAL000059   Joan Buchanan
## 3 (916) 319-2022 CAL000084       Paul Fong
## 4 (916) 319-2046 CAL000089      John Pérez
## 5 (916) 319-2080 CAL000098 V. Manuel Pérez
## 6 (916) 319-2001 CAL000101  Wesley Chesbro

Now you can call each representative, yay!

Capitol Words API

Search for phrase climate change used by politicians between September 5th and 16th, 2011:

head(cw_text(phrase='climate change', start_date='2011-09-05', end_date='2011-09-16', party='D')[,c('speaker_last','origin_url')])
##   speaker_last
## 1      Tsongas
## 2       Inslee
## 3        Costa
## 4        Boxer
## 5       Durbin
## 6        Boxer
##                                                                                   origin_url
## 1 http://origin.www.gpo.gov/fdsys/pkg/CREC-2011-09-14/html/CREC-2011-09-14-pt1-PgH6149-5.htm
## 2   http://origin.www.gpo.gov/fdsys/pkg/CREC-2011-09-15/html/CREC-2011-09-15-pt1-PgH6186.htm
## 3 http://origin.www.gpo.gov/fdsys/pkg/CREC-2011-09-13/html/CREC-2011-09-13-pt1-PgE1609-2.htm
## 4   http://origin.www.gpo.gov/fdsys/pkg/CREC-2011-09-15/html/CREC-2011-09-15-pt1-PgS5650.htm
## 5   http://origin.www.gpo.gov/fdsys/pkg/CREC-2011-09-13/html/CREC-2011-09-13-pt1-PgS5510.htm
## 6 http://origin.www.gpo.gov/fdsys/pkg/CREC-2011-09-13/html/CREC-2011-09-13-pt1-PgS5513-2.htm

Plot mentions of the term climate change over time for Democrats vs. Republicans

library('ggplot2')
dat_d <- cw_timeseries(phrase='climate change', party="D")
dat_d$party <- rep("D", nrow(dat_d))
dat_r <- cw_timeseries(phrase='climate change', party="R")
dat_r$party <- rep("R", nrow(dat_r))
dat_both <- rbind(dat_d, dat_r)
ggplot(dat_both, aes(day, count, colour=party)) +
   geom_line() +
   theme_grey(base_size=20) +
   scale_colour_manual(values=c("blue","red"))

plot of chunk unnamed-chunk-9

Influence Explorer API

Search for contributions of equal to or more than $20,000,000.

ie_contr(amount='>|20000000')[,c('amount','recipient_name','contributor_name')]
##         amount
## 1  25177212.00
## 2  20000000.00
## 3  20000000.00
## 4  20000000.00
## 5  20000000.00
## 6  20000000.00
## 7  50000000.00
## 8  34000000.00
## 9  28000000.00
## 10 20000000.00
##                                                   recipient_name
## 1                                       Republican National Cmte
## 2  CALIFORNIANS TO CLOSE THE OUT-OF-STATE CORPORATE TAX LOOPHOLE
## 3                                                   WHITMAN, MEG
## 4                                                   WHITMAN, MEG
## 5                                                   WHITMAN, MEG
## 6                                                   WHITMAN, MEG
## 7                                         GOLISANO, B THOMAS (G)
## 8                                         GOLISANO, B THOMAS (G)
## 9                                         GOLISANO, B THOMAS (G)
## 10                                        GOLISANO, B THOMAS (G)
##           contributor_name
## 1           Romney Victory
## 2         STEYER, THOMAS F
## 3  WHITMAN, MARGARET (MEG)
## 4  WHITMAN, MARGARET (MEG)
## 5  WHITMAN, MARGARET (MEG)
## 6  WHITMAN, MARGARET (MEG)
## 7       GOLISANO, B THOMAS
## 8       GOLISANO, B THOMAS
## 9       GOLISANO, B THOMAS
## 10      GOLISANO, B THOMAS

Top industries, by contributions given. UNKOWN is a very influential industry. Of course law firms are high up there, as well as real estate. I’m sure oil and gas is embarrased that they’re contributing less than pulic sector unions.

(res <- ie_industries(method='top_ind', limit=10))
##       count        amount                               id
## 1  14919818 3825359507.21 cdb3f500a3f74179bb4a5eb8b2932fa6
## 2   3600761 2787678962.95 f50cf984a2e3477c8167d32e2b14e052
## 3    329906 1717649914.58 9cac88377c3b400e89c2d6762e3f28f6
## 4   1386613 1707457092.04 7500030dffe24844aa467a75f7aedfd1
## 5    774496 1563637586.57 0af3f418f426497e8bbf916bfc074ebc
## 6    546367 1389220855.35 52e5d4c6c0fa47c3bdb199a28f96d434
## 7   2134350 1384221307.53 a05a0d06f6814b31bece35a81fcb40c7
## 8   1003850  986588892.83 8ada0fc2d6994f2ab06c7e025dff2284
## 9    567082  775241387.17 52766c4910a846f2813a1dda212b7027
## 10   151006  706747646.35 13718be68388456d9b6e8db753f06e72
##    should_show_entity                    name
## 1                TRUE                 UNKNOWN
## 2                TRUE       LAWYERS/LAW FIRMS
## 3                TRUE  CANDIDATE SELF-FINANCE
## 4                TRUE             REAL ESTATE
## 5                TRUE SECURITIES & INVESTMENT
## 6                TRUE    PUBLIC SECTOR UNIONS
## 7                TRUE    HEALTH PROFESSIONALS
## 8                TRUE               INSURANCE
## 9                TRUE               OIL & GAS
## 10               TRUE        CASINOS/GAMBLING
res$amount <- as.numeric(res$amount)
ggplot(res, aes(reorder(name, amount), amount)) +
  geom_bar(stat = "identity") +
  coord_flip() +
  scale_y_continuous(labels=dollar) +
  theme_grey(base_size = 14)

plot of chunk unnamed-chunk-11


Feedback

Please do use rsunlight, and let us know what you want fixed, new features, etc.

Still to come:

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