How to identify missing months from a column vector?

Let's assume I have a dataframe with one column - Date - that goes from 2000 to 2019. The problem is that I don't have perfect monthly frequence (in fact I should have 245 observations, instead I only have 215). My aim is to detect what are the missing months in the column.

Let's take this example. This is a sample dataframe:

df <- data.frame(Date = c("2015-01-22", "2015-03-05", "2015-04-15", "2015-06-03", "2015-07-16", "2015-09-03", "2015-10-22", "2015-12-03", "2016-01-21", "2016-03-10", "2016-04-21", "2016-06-02", "2016-07-21", "2016-09-08", "2016-10-20", "2016-12-08", "2017-01-19", "2017-03-09", "2017-04-27", "2017-06-08", "2017-07-20", "2017-09-07", "2017-10-26", "2017-12-14", "2018-01-25", "2018-03-08", "2018-04-26", "2018-06-14", "2018-07-26", "2018-09-13", "2018-10-25", "2018-12-13", "2019-01-24", "2019-03-07", "2019-04-10", "2019-06-06", "2019-07-25", "2019-09-12", "2019-10-24", "2019-12-12"))

df

I would like to find a code that gives me what are the missing months in my column vector of dates.

Can anyone help me?

Thanks a lot

Here are two types of results to see the missing months, with base R:

• If you want to see the missing month regardless of years, you can try the following code

missingMonths <- month.name[setdiff(seq(12),as.numeric(format(as.Date(df$Date),"%m")))]

such that

> missingMonths
[1] "February" "May"      "August"   "November"

• If you want to check the missing months by year, you can try the code below:

missingMonths <- lapply(split(df,format(as.Date(df$Date),"%Y")), 
                        function(x) month.name[setdiff(seq(12),as.numeric(format(as.Date(x$Date),"%m")))])

such that

> missingMonths
$`2015`
[1] "February" "May"      "August"   "November"

$`2016`
[1] "February" "May"      "August"   "November"

$`2017`
[1] "February" "May"      "August"   "November"

$`2018`
[1] "February" "May"      "August"   "November"

$`2019`
[1] "February" "May"      "August"   "November"

Not as succinct as above, but still does the trick in a couple of steps:

month_date_strings <- unique(paste0(sub("-[^-]+$", "", 
                           sapply(df$Date, as.character)), "-01"))


month_seq_strings <- unique(as.character(seq.Date(as.Date("2000-01-01", "%Y-%m-%d"),
                      as.Date("2019-12-31", "%Y-%m-%d"), by = "month")))

month_seq_strings[!(month_seq_strings %in% month_date_strings)]