The set_read_fn(), remove_read_fn(), and remove_tbl() functions were removed since the read_fn argument has been deprecated (and there's virtually no need to remove a table from an object with remove_tbl() now). pointblank 0.9.0 New features The new rows_complete() validation functi...
blankagentis given a collection of validation functions to define validation steps. We can get extracts of data rows that failed validation, set up custom functions that are invoked by exceeding set threshold failure rates, etc. Want to email the report regularly (or, only if certain conditions...
Let’s look at an example with the Dow Jones daily return data in djx. Because 5 values are used to calculate each moving sum, the first 4 values in the result are NA. In this instance, we will use indexing to remove them: Hide dj <- DJ["2008/2011"] djx <- diff(log(dj))[-...
Replacing values in xts objects is just as easy as extracting them. You can use either ISO-8601 strings, date objects, logicals, or integers to locate the rows you want to replace. One reason you may want to do this would be to replace known intervals or observations with NA, say due ...
5.2 Filter rows with filter() filter() can help find certain values in a chain argument and help filter out certain variables you want to look at. filter(flights, month == 1, day == 1) ## # A tibble: 842 x 19 ## year month day dep_time sched_dep_time dep_delay arr_time ...
So lets tie everything back together and see what you were asking when it did work, and what are the TRUE/FALSE values Given your request to group by Time == 0, tapply has assigned a group of TRUE/FALSE values to keep track of what it should do with the function you pass in. In...
# Since the sparsity is so high, i.e. a proportion of cells with 0s/ cells with other values is too large,# let's remove some of these low frequency termstweets_tdm_rm_sparse<-removeSparseTerms(tweets_tdm,0.99)# Print out tweets_dtm datatweets_tdm_rm_sparse ...
6 rows | 1-10 of 17 columnsScan I As mentioned before, I intentially assigned some NA values, and now I will work on replacing with the appropriate values. Considering the type of the data: device readings taken hourly. this data might change from day to day or by months. So replacing...