Some statistics

ch420_statistics/20170703_tagi_export.R

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+library(mongolite)
+library(xlsx)
+
+Sys.setlocale("LC_ALL", "de_DE")
+
+# Connect to the databes with the supporter collection
+m <- mongo(db="heroku_t242kdp0", collection = "supporters")
+
+# Find all datasets not marked as dublicates
+dt <- m$find('{"duplicate":  { "$ne": true }}')
+dt$created_at <- as.Date(dt$created_at)
+# Filter erroneous data
+dt <- subset(dt, zip >=1000)
+dt <- subset(dt, zip < 10000)
+
+# Read BFS-Data with statistics of population from 2014
+population_per_plz4 <- read.xlsx(file = "external_data/su-d-01.02.03.07.xls", sheetName = "2014", startRow = 5, endRow = 3189, colIndex = c(1,2))
+colnames(population_per_plz4) <- c('zip', 'popuplation')
+
+# Read canton name and zip from 
+ktkz_plz4 <- read.xlsx(file = "external_data/be-b-00.04-osv-01.xls", sheetName = "PLZ4 -> GDE - NPA4 -> COM", startRow = 12,colIndex = c(1,2,4,5))
+colnames(ktkz_plz4) <- c('zip', 'percent_of_community', 'canton', 'name')
+
+ktkz_plz4 <- ktkz_plz4[order(100-ktkz_plz4$percent_of_community),] 
+ktkz_plz4_uniq <- ktkz_plz4[!duplicated(ktkz_plz4$zip),]
+
+# Merge population and canton by zip together
+location_description <- merge(ktkz_plz4_uniq, population_per_plz4, by='zip')
+
+# Total participants per zip
+participants <- as.data.frame(table(dt$zip))
+colnames(participants) <- c('zip','total_participants')
+
+# Signers only
+signers <- as.data.frame(table(subset(dt, support=="signer")$zip))
+colnames(signers) <- c('zip','signers')
+
+# Supporters only
+supporters <- as.data.frame(table(subset(dt, support=="supporter")$zip))
+colnames(supporters) <- c('zip','supporters')
+
+# Merge everything to one big table
+main_table <- merge(location_description, participants, by="zip", all.x=T)
+main_table <- merge(main_table, signers, by="zip", all.x=T)
+main_table <- merge(main_table, supporters, by="zip", all.x=T)
+
+# Calculate ratio in population
+main_table$total_participants_ratio <- main_table$total_participants / main_table$popuplation
+main_table$total_signers_ratio <- main_table$signers / main_table$popuplation
+main_table$total_supporters_ratio <- main_table$supporters / main_table$popuplation
+
+# Export as xlsx
+write.xlsx2(main_table, file = "20170703_tagi_export.xlsx", row.names=F)