diff --git a/ch420_statistics/external_data/be-b-00.04-osv-01.xls b/ch420_statistics/external_data/be-b-00.04-osv-01.xls
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diff --git a/ch420_statistics/external_data/su-d-01.02.03.07.xls b/ch420_statistics/external_data/su-d-01.02.03.07.xls
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diff --git a/ch420_statistics/statistics_city_participation_by_zip.R b/ch420_statistics/statistics_city_participation_by_zip.R
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+++ b/ch420_statistics/statistics_city_participation_by_zip.R
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+library(mongolite)
+library(plyr)
+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 town names
+mainTable <- read.xlsx(file = "external_data/be-b-00.04-osv-01.xls", sheetIndex = 2, startRow = 1, colIndex = c(2,4,8,6))
+colnames(mainTable) <- c('OHW','GWH','name', 'zip') 
+mainTable <- subset(mainTable, is.na(OHW))
+mainTable <- subset(mainTable, is.na(GWH))
+mainTable <- unique(mainTable)
+
+
+# Read BFS-Data with statistics of population from 2014
+dataTable <- read.xlsx(file = "external_data/su-d-01.02.03.07.xls", sheetName = "2014", startRow = 5, endRow = 3189, colIndex = c(1,2))
+colnames(dataTable) <- c('zip', 'total') 
+
+# Merge town names with statistics of population
+mainTable <- merge(mainTable,dataTable, by="zip", all.y = T)
+
+# Count number of total participants grouped by zip
+participants_by_zip <- ddply(dt,~zip,summarise,participants=length(zip))
+
+# Calculate the ration between participants and the total amount of habitants
+mainTable$participant_ratio = mainTable$participants/mainTable$total
+
+# Merge number of participants with main table
+mainTable <- merge(mainTable,participants_by_zip, by="zip", all.x=T)
+
+# Count number of total signers grouped by zip
+signer_by_zip <- ddply(subset(dt, support=="signer"),~zip,summarise,signers=length(zip))
+
+# Merge number of signers with main table
+mainTable <- merge(mainTable,signer_by_zip, by="zip", all.x=T)
+
+# Count number of total signers grouped by zip
+supporter_by_zip <- ddply(subset(dt, support=="supporter"),~zip,summarise,supporters=length(zip))
+
+# Merge number of signers with main table
+mainTable <- merge(mainTable,supporter_by_zip, by="zip", all.x=T)
+
+# Calculate the ration between signer and supporter
+mainTable$supporter_signer_ratio = mainTable$supporters/mainTable$participants
+
+# Replace Na's with 0
+mainTable[is.na(mainTable)] <- 0
+
+
+write.xlsx(mainTable, file = "statistics_city_participation_by_zip.xls", row.names=F)
diff --git a/ch420_statistics/statistics_city_participation_by_zip.xls b/ch420_statistics/statistics_city_participation_by_zip.xls
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