Comments (1)
periods
is the parameter to the standard evaluation version interpolate_missing_periods_()
, listing which periods should be interpolated (e.g. 2005
, 2010
, …) and how they are named in the data frame data
(e.g. period
, year
, …).
period
is the name of the temporal dimension in quitte
data frames, and as such the default value if no name is given. But any name is possible.
(data <- tibble(
group = rep(c('A', 'B'), c(8, 4)),
item = c(rep('x', 4), rep('y', 4), rep('x', 4)),
year = rep(c(2015, 2025, 2030, 2035), 3),
value = c(2, 4, 5, 6, 20, NA, 50, 60, NA, 400, 500, NA)))
interpolate_missing_periods(data, year = c(2015, 2020, 2025, 2030, 2035))
from quitte.
Related Issues (18)
- quitte::read.quitte() return object not recognized by tidyr::pivot_wider() as tibble HOT 2
- character.data.frame returns malformed column names HOT 1
- bug in calc_addVariable causing wrong additional output HOT 1
- sum_total() subsets wrong groups
- calc_addVariable(): problem with "completeMissing = TRUE"
- [Feature request] fast way to read subset of variables into quitte df HOT 3
- vignette review HOT 3
- add a comment header in mif file with a few lines of metadata (if mif is produced on the cluster)
- warning from replace_column with ambigous mask HOT 4
- Too much filling by completeMissing in calc_addVariable? HOT 2
- write.mif could support append
- inpolate_missing_periods falsly extrapolates in particular cases HOT 1
- default handling of Inf in read.quitte HOT 2
- New variable in calc_addVariable cannot be named as exisitng variable HOT 2
- build fail - depreciation warning from forcats HOT 2
- Requirement for forcats >= 1.0.0 missing
- in quitteSort, sort levels alphabetically
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from quitte.