r tag stackoverflow.r

# query run here: https://data.stackexchange.com/stackoverflow/query/edit/543286
# 
# select 
#   TagName, 
#   str(DATEPART(yyyy, p.CreationDate ))  + '-' + str(DATEPART(mm, p.CreationDate )) as postmonth,
#   count(pt.PostId) as Num
# from
#   Tags, 
#   PostTags pt, 
#   Posts as p
#   where Tags.Id = pt.TagId 
#   and p.Id = pt.PostId
#   AND tags.tagname = 'r'
# group by 
#   TagName ,
#   str(DATEPART(yyyy, p.CreationDate ))  + '-' + str(DATEPART(mm, p.CreationDate ));

## data downloaded and saved to '~/Downloads/QueryResults-r.csv'

library(stringr)
library(ggplot2)
library(plyr)


soData <- read.csv('~/Downloads/QueryResults-r.csv')

soData$postmonth <- gsub("\\s+", " ", str_trim(soData$postmonth))

soData$yearNum <- as.numeric(substr(soData$postmonth,1,4))

soData$monthNum <- substr(soData$postmonth, nchar(soData$postmonth)-2 , nchar(soData$postmonth))
soData$monthNum <- as.numeric(gsub('![[:alnum:]]*[[:space:]]|[[:punct:]]', '', soData$monthNum))

soData$postmonth <- factor(soData$postmonth, levels = soData$postmonth)


theme_set(theme_gray(base_size = 18))

ggplot(data = subset(soData, yearNum <= 2009), aes( x=postmonth, y=Num)) +
  geom_bar(stat="identity") +
  theme(axis.text.x=element_text(angle=90,hjust=1,vjust=0.5)
  )


ggplot(data = soData, aes( x=postmonth, y=Num)) +
  geom_bar(stat="identity") +
  theme(axis.text.x=element_text(angle=90,hjust=1,vjust=0.5)
  )

write.csv(soData, '~/Downloads/QueryResults-r-soData.csv' )

## linear trend

soDataSubset <- subset(soData, yearNum >= 2012 & postmonth != '2016- 10')
soDataSubset$index <- 1:length(soDataSubset$Num)
reg <- lm(Num ~ index, data =soDataSubset )

soDataSubset$modeled <- predict(reg)

# calculate percent deviation of modeled
soDataSubset$dev <- (soDataSubset$Num - soDataSubset$modeled) / soDataSubset$modeled

## plot errors
ggplot(data = soDataSubset, aes( x=postmonth, y=dev)) +
  geom_bar(stat="identity") +
  theme(axis.text.x=element_text(angle=90,hjust=1,vjust=0.5)
  )


monthlyAvgDev <- ddply(soDataSubset, 'monthNum', function(df)mean(df$dev) )

colnames(monthlyAvgDev) <- c('monthNum','avgErr')
monthlyAvgDev$monthNum <- factor( monthlyAvgDev$monthNum )

## plot average error by month
ggplot(data = monthlyAvgDev, aes( x=monthNum, y=avgErr)) +
  geom_bar(stat="identity") +
  theme(axis.text.x=element_text(angle=90,hjust=1,vjust=0.5)
  )