I saw a link to a list with all rocket launches into space the other day. This post contains some plots concerning day of launch made from that.

Data

Data is a fixed format file with eleven columns. Reading fixed format is not very difficult, however, it requires a bit of preparation. In this case, the first row contains a description of the columns, the second a number of ‘#’signs to denote the start of the columns. I found it most logical to first get the column widths, use these to create the variable names and then read the data. There is an interesting detail, the first two rows have ‘#’ as first character, read.fwf has this as default comment character and skips them.
library(dplyr)
library(ggplot2)
library(lme4)
r1 <- readLines('launchlog.txt')
colwidth  <- gregexpr('#',r1[2])[[1]] %>%
    c(.,max(nchar(r1))) %>%
    diff(.)

cols <- read.fwf(textConnection(r1[1]),
        widths=colwidth,
        header=FALSE,
        comment.char=’@’) %>%
    unlist(.) %>%
    make.names(.) %>%
    gsub(‘\.+$’,”,.) # remove extra . at end of string

r2 <- read.fwf('launchlog.txt',
    widths=colwidth,
    col.names=cols) 
Some launches contain more than one pay load. These are represented by rows containing just pay load information. These are removed by removing all records without a success value. In addition, a date variable is created using the launch date. Extra spaces, a consequence of the fixed input format, are removed from the suc variable.
r3 <- filter(r2,!is.na(Suc))
Sys.setlocale(category = “LC_TIME”, locale = “C”)
r3$Launch.Date..UTC[1:3]
r3$Date <- as.Date(r3$Launch.Date..UTC,format='%Y %b %d')
levels(r3$Suc) <- gsub(' *','',levels(r3$Suc))

Plots

Preparation

Since I wanted proportion of days with a launch, I created a few extra data frames. alldays contains all dates. monthorder and wdorder provide additional variables intended to arrange the months and week days in a reasonable order.
alldays <- data.frame(
    Date=seq(
        min(r3$Date),
        max(r3$Date) ,
        by=1 ))
monthorder <- alldays %>%
    mutate(.,
        month=months(Date),
        mn=format(Date,’%m’)) %>%
    select(.,month,mn) %>%
    unique(.) %>%
    arrange(.,mn)

wdorder <- alldays %>%
    mutate(.,
        wd=weekdays(Date),
        wdn=format(Date,’%u’)) %>%
    select(.,wd,wdn) %>%    
    unique(.) %>%
    arrange(.,wdn)

By month

January seems to get least launches. On the other hand December most. I wonder if that is publicity seeking in December of the well know January 1st deadline.

By weekdays

As expected, middle of the week gets most launches. The lower value for Monday than Saturday suggests the day before a launch is just as busy as the day of launch itself.
numlawd <-    mutate(r3,
        wd =factor(weekdays(Date),levels=wdorder$wd)) %>%
    xtabs( ~ wd,.) %>%
    as.data.frame(.) %>%
    rename(.,Occur=Freq)
numwd <-    mutate(alldays,
        wd =factor(weekdays(Date),levels=wdorder$wd)) %>%
    xtabs( ~ wd,.) %>%
    as.data.frame(.) %>%
    rename(.,NM=Freq)
propbwd <- merge(numlawd,numwd) %>%
    mutate(prop=Occur/NM)
qplot(y=prop,x= wd,data=propbwd) +
    ylab(‘Proportion’) +
    xlab(‘Day of Week’) +
    ggtitle(‘Proportion Week Days with Launch’) +
    coord_flip()

Most busy day?

Once there were four launches on a day.
r3 %>% xtabs(~factor(Date,levels=as.character(alldays$Date)),.) %>%
    as.data.frame(.) %>%
    rename(.,Nlaunch=Freq) %>%
    xtabs(~Nlaunch,.) %>%
    as.data.frame(.) 
  Nlaunch  Freq
1       0 16154
2       1  4224
3       2   562
4       3    44
5       4     1