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The Washington Explorer (WashEx) package creates an interface between R and the Washington State Legislative Web Services. It serves as a companion to Legislative Explorer: Washington, a project developed by John Wilkerson and Rohnin Randles at the University of Washington. The package contains functions to retrieve data regarding the following:
You can install the released version of washex from CRAN with:
install.packages("washex")And the development version from GitHub with:
# install.packages("devtools")
devtools::install_github("rwrandles/washex-r")Some possible implementations of the washex package
include
library(washex)
library(tidyverse)
sponsors_2007 <- getSponsors("2007-08")
sponsors_2007 %>%
group_by(District) %>%
summarize(prop_repub = round(mean(Party == "R"),3))
#> # A tibble: 49 x 2
#> District prop_repub
#> <chr> <dbl>
#> 1 1 0
#> 2 10 0.75
#> 3 11 0
#> 4 12 1
#> 5 13 1
#> 6 14 1
#> 7 15 1
#> 8 16 0.667
#> 9 17 0.667
#> 10 18 1
#> # ... with 39 more rows
head(getCommittees("2007-08")[,"Name"])
#> [1] "Agriculture & Natural Resources"
#> [2] "Appropriations"
#> [3] "Appropriations Subcommittee on Education"
#> [4] "Appropriations Subcommittee on General Government & Audit Review"
#> [5] "Appropriations Subcommittee on Health & Human Services"
#> [6] "Capital Budget"
head(getStatusChanges("2007-08", "1001") %>%
select("HistoryLine", "ActionDate"))
#> HistoryLine
#> 1 First reading, referred to Public Safety & Emerg Prep.
#> 2 PSEP - Executive action taken by committee.
#> 3 PSEP - Majority; 1st substitute bill be substituted, do pass.
#> 4 Referred to Human Services.
#> 5 HS - Executive action taken by committee.
#> 6 HS - Majority; 2nd substitute bill be substituted, do pass.
#> ActionDate
#> 1 2007-01-08T00:00:00
#> 2 2007-02-01T00:00:00
#> 3 2007-02-01T00:00:00
#> 4 2007-02-06T00:00:00
#> 5 2007-02-22T00:00:00
#> 6 2007-02-22T00:00:00
ag_bills <- getRCWBills("2007-08", c("15","16"))
getRollCalls.votes("2007-08", ag_bills$BillNumber) %>%
filter(str_detect("Final Passage", Motion)) %>%
mutate(Party = sponsors_2007$Party[match(MemberId, sponsors_2007$Id)]) %>%
group_by(BillId) %>%
summarize(repub_support = sum(Vote == "Yea" & Party == "R") / sum(Party == "R"),
dem_support = sum(Vote == "Yea" & Party == "D") / sum(Party == "D"))
#> # A tibble: 16 x 3
#> BillId repub_support dem_support
#> <chr> <dbl> <dbl>
#> 1 E2SHB 1303 0.457 1
#> 2 E2SHB 2798 0.943 0.984
#> 3 EHB 3381 0.0571 0.841
#> 4 ESB 5204 1 0.984
#> 5 ESHB 1151 1 1
#> 6 HB 1311 0.971 0.873
#> 7 HB 1418 0.114 0.937
#> 8 HB 1775 0.957 0.968
#> 9 HB 1888 0.971 1
#> 10 HB 2467 0.943 0.984
#> 11 HB 3106 0.886 0.952
#> 12 SB 6283 0.943 0.984
#> 13 SB 6284 0.943 0.921
#> 14 SHB 1128 0.0286 0.968
#> 15 SHB 1312 1 0.984
#> 16 SHB 1338 0.943 0.889If you encounter any bugs or issues while using the package, please file an issue with a minimum reproducible example on Github
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.