sparklyr - Active Bugs 2017

Downloads bugs from https://s3.amazonaws.com/gitbugs/index.html for rstudio/sparklyr then, import:

library(readr)
gitbugs <- read_csv("~/Downloads/gitbugs.csv", 
    col_types = cols_only(closed_at = col_datetime(format = "%Y-%m-%dT%H:%M:%SZ"), 
        created_at = col_datetime(format = "%Y-%m-%dT%H:%M:%SZ"), 
        title = col_guess(),
        labels_0_name = col_guess()))

first create a range of dates:

bugsRange <- seq(as.Date("2016/1/1"), as.Date("2017/10/1"), "days")

get all labels,

labels <- unique(gitbugs$labels_0_name)

then calculate active bugs per day,

activeBugs <- sapply(bugsRange, function(i) {
      nrow(gitbugs[
        gitbugs$created_at <= as.POSIXct(i) &
          (is.na(gitbugs$closed_at) | gitbugs$closed_at > as.POSIXct(i)), ])
  })

bugsTable <- data.frame(date = bugsRange, total = activeBugs, label = "all")

and plot active bugs per day:

library(ggplot2)
allBugs <- bugsTable[bugsTable$label == "all",]
ggplot(allBugs, aes(x = date, y = total)) + geom_line()

library(dplyr)

## 
## Attaching package: 'dplyr'

## The following objects are masked from 'package:stats':
## 
##     filter, lag

## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

openBugs <- gitbugs %>% filter(is.na(closed_at)) %>% transmute(label = labels_0_name)
ggplot(openBugs, aes(label)) + coord_flip() + geom_bar()