The package offers functions that calculate coalition probabilities in multi-party elections, based on a survey results:
To get started, see our workflow vignette
See our talk at the Munich AppliedR MeetUp
Check out our interacitve shiny app on German (state and federal) elections/surveys
Updates are available on our KOALA_LMU twitter account!
Install from GitHub using:
devtools::install_github("adibender/coalitions")Detailed workflow is outlined in the workflow vignette.
A short overview is presented below.
The wrapper get_surveys() which takes no arguments, downloads all surveys currently available at wahlrecht.de and stores them in a nested tibble:
library(coalitions)
library(dplyr)
library(tidyr)
surveys <- get_surveys()
surveys## # A tibble: 7 x 2
## pollster surveys
## <chr> <list>
## 1 allensbach <tibble [42 × 5]>
## 2 emnid <tibble [226 × 5]>
## 3 forsa <tibble [236 × 5]>
## 4 fgw <tibble [83 × 5]>
## 5 gms <tibble [96 × 5]>
## 6 infratest <tibble [110 × 5]>
## 7 insa <tibble [305 × 5]>Each row represents a polling agency and each row in the surveys column again contains a nested tibble with survey results from different time-points:
surveys %>%
filter(pollster == "allensbach") %>%
unnest()## # A tibble: 42 x 6
## pollster date start end respondents survey
## <chr> <date> <date> <date> <dbl> <list>
## 1 allensbach 2018-02-23 2018-02-02 2018-02-15 1271 <tibble [7 × 3…
## 2 allensbach 2018-01-25 2018-01-05 2018-01-18 1221 <tibble [7 × 3…
## 3 allensbach 2017-12-21 2017-12-01 2017-12-14 1443 <tibble [7 × 3…
## 4 allensbach 2017-11-30 2017-11-22 2017-11-27 1299 <tibble [7 × 3…
## 5 allensbach 2017-10-25 2017-10-07 2017-10-19 1454 <tibble [7 × 3…
## 6 allensbach 2017-09-22 2017-09-13 2017-09-20 1074 <tibble [7 × 3…
## 7 allensbach 2017-09-19 2017-09-06 2017-09-14 1083 <tibble [7 × 3…
## 8 allensbach 2017-09-06 2017-08-22 2017-08-31 1043 <tibble [7 × 3…
## 9 allensbach 2017-08-22 2017-08-04 2017-08-17 1421 <tibble [7 × 3…
## 10 allensbach 2017-07-18 2017-07-01 2017-07-12 1403 <tibble [7 × 3…
## # ... with 32 more rowssurvey <- surveys %>% unnest() %>% slice(1)
survey %>% unnest()## # A tibble: 7 x 8
## pollster date start end respondents party percent
## <chr> <date> <date> <date> <dbl> <chr> <dbl>
## 1 allensbach 2018-02-23 2018-02-02 2018-02-15 1271 cdu 32.0
## 2 allensbach 2018-02-23 2018-02-02 2018-02-15 1271 spd 17.5
## 3 allensbach 2018-02-23 2018-02-02 2018-02-15 1271 greens 12.0
## 4 allensbach 2018-02-23 2018-02-02 2018-02-15 1271 fdp 11.0
## 5 allensbach 2018-02-23 2018-02-02 2018-02-15 1271 left 9.50
## 6 allensbach 2018-02-23 2018-02-02 2018-02-15 1271 afd 13.0
## 7 allensbach 2018-02-23 2018-02-02 2018-02-15 1271 others 5.00
## # ... with 1 more variable: votes <dbl>For each survey (row) we can calculate the coalition probabilities
survey %>% get_probabilities(nsim=1e4) %>% unnest()## # A tibble: 6 x 4
## pollster date coalition probability
## <chr> <date> <chr> <dbl>
## 1 allensbach 2018-02-23 cdu 0
## 2 allensbach 2018-02-23 cdu_fdp 0.0400
## 3 allensbach 2018-02-23 cdu_fdp_greens 100.0
## 4 allensbach 2018-02-23 spd 0
## 5 allensbach 2018-02-23 left_spd 0
## 6 allensbach 2018-02-23 greens_left_spd 0