scrape_wahlrecht | R Documentation |
Scrapes survey tables and performs sanitation to output tidy data
scrape_wahlrecht(
address = "https://www.wahlrecht.de/umfragen/emnid.htm",
parties = c("CDU", "SPD", "GRUENE", "FDP", "LINKE", "PIRATEN", "FW", "AFD",
"SONSTIGE")
)
scrape_by(
address = "https://www.wahlrecht.de/umfragen/landtage/bayern.htm",
parties = c("CSU", "SPD", "GRUENE", "FDP", "LINKE", "PIRATEN", "FW", "AFD",
"SONSTIGE")
)
scrape_rp(
address = "https://www.wahlrecht.de/umfragen/landtage/rheinland-pfalz.htm",
parties = c("CDU", "SPD", "GRUENE", "FDP", "LINKE", "AFD", "FW", "SONSTIGE"),
ind_row_remove = -c(1:3)
)
scrape_ltw(
address = "https://www.wahlrecht.de/umfragen/landtage/niedersachsen.htm",
parties = c("CDU", "SPD", "GRUENE", "FDP", "LINKE", "PIRATEN", "FW", "AFD",
"SONSTIGE"),
ind_row_remove = -c(1:2)
)
address |
http-address from which tables should be scraped. |
parties |
A character vector containing names of parties to collapse. |
ind_row_remove |
Negative vector of rows that will be skipped at the beginning. |
## Not run:
library(coalitions)
library(dplyr)
# select a polling agency from .pollster_df that should be scraped ...
coalitions:::.pollster_df
# ... here we choose Forsa
address <- coalitions:::.pollster_df %>% filter(pollster == "forsa") %>% pull(address)
scrape_wahlrecht(address = address) %>% slice(1:5)
## End(Not run)
## Not run:
# Niedersachsen
scrape_ltw() %>% slice(1:5)
# Hessen
scrape_ltw("https://www.wahlrecht.de/umfragen/landtage/hessen.htm", ind_row_remove=-c(1)) %>%
slice(1:5)
## End(Not run)
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