问题
I have annual financial data for several stocks. I needed to blow it out to become monthly data and, thanks to an answer to this question I'd asked earlier, I have a solution which involves mutating the date
column into lists of dates:
library(tidyverse)
library(lubridate)
factors.subset.raw = structure(list(
sec_id = c(1572L, 1572L, 1572L, 1572L, 1572L, 1572L, 1572L, 1572L, 1572L, 1572L, 1572L, 1572L, 1572L, 1572L, 1572L, 1572L, 1572L, 1572L, 1572L, 1572L, 1572L, 1572L, 1676L, 1676L, 1676L, 1676L, 1676L, 1676L, 1676L, 1676L, 1676L, 1676L, 1676L, 1676L, 1676L, 1676L, 1676L, 1676L, 1676L, 1572L, 1572L, 1572L, 1572L, 1572L, 1572L, 1572L, 1572L, 1572L, 1572L, 1572L, 1572L, 1572L, 1572L, 1572L, 1572L, 1572L, 1572L, 1572L, 1572L, 1572L, 1572L, 1676L, 1676L, 1676L, 1676L, 1676L, 1676L, 1676L, 1676L, 1676L, 1676L, 1676L, 1676L, 1676L, 1676L, 1676L, 1676L, 1676L),
metric = c("EPS_GROWTH", "EPS_GROWTH", "EPS_GROWTH", "EPS_GROWTH", "EPS_GROWTH", "EPS_GROWTH", "EPS_GROWTH", "EPS_GROWTH", "EPS_GROWTH", "EPS_GROWTH", "EPS_GROWTH", "EPS_GROWTH", "EPS_GROWTH", "EPS_GROWTH", "EPS_GROWTH", "EPS_GROWTH", "EPS_GROWTH", "EPS_GROWTH", "EPS_GROWTH", "EPS_GROWTH", "EPS_GROWTH", "EPS_GROWTH", "EPS_GROWTH", "EPS_GROWTH", "EPS_GROWTH", "EPS_GROWTH", "EPS_GROWTH", "EPS_GROWTH", "EPS_GROWTH", "EPS_GROWTH", "EPS_GROWTH", "EPS_GROWTH", "EPS_GROWTH", "EPS_GROWTH", "EPS_GROWTH", "EPS_GROWTH", "EPS_GROWTH", "EPS_GROWTH", "EPS_GROWTH", "ND_EQUITY", "ND_EQUITY", "ND_EQUITY", "ND_EQUITY", "ND_EQUITY", "ND_EQUITY", "ND_EQUITY", "ND_EQUITY", "ND_EQUITY", "ND_EQUITY", "ND_EQUITY", "ND_EQUITY", "ND_EQUITY", "ND_EQUITY", "ND_EQUITY", "ND_EQUITY", "ND_EQUITY", "ND_EQUITY", "ND_EQUITY", "ND_EQUITY", "ND_EQUITY", "ND_EQUITY", "ND_EQUITY", "ND_EQUITY", "ND_EQUITY", "ND_EQUITY", "ND_EQUITY", "ND_EQUITY", "ND_EQUITY", "ND_EQUITY", "ND_EQUITY", "ND_EQUITY", "ND_EQUITY", "ND_EQUITY", "ND_EQUITY", "ND_EQUITY", "ND_EQUITY", "ND_EQUITY", "ND_EQUITY"),
date = structure(c(9464, 9829, 10193, 10560, 10925, 11291, 11656, 12020, 12384, 12752, 13117, 13482, 13847, 14211, 14578, 14943, 15308, 15674, 16038, 16402, 16769, 17135, 9342, 9708, 10073, 10438, 10802, 11200, 11565, 13756, 14120, 14487, 14852, 15217, 15583, 15947, 16311, 16678, 17044, 9464, 9829, 10193, 10560, 10925, 11291, 11656, 12020, 12384, 12752, 13117, 13482, 13847, 14211, 14578, 14943, 15308, 15674, 16038, 16402, 16769, 17135, 9342, 9708, 10073, 10438, 10802, 11200, 11565, 13756, 14120, 14487, 14852, 15217, 15583, 15947, 16311, 16678, 17044),
class = "Date"), value = c(0.250468, 0.091548, -0.100863, 0.058375, 0.24784, 0.178765, 0.099276, 0.25472, -0.033291, 0.124165, 0.050947, 0.243008, 0.1205, -0.239625, -0.231221, 0.365649, 0.163779, 0.024976, 0.08388, 0.154777, 0.016473, -0.272928, -0.018711, -0.162076, -0.599241, -4.071504, -0.37761, 1.694085, 0.045113, 0.329818, 0.199564, -0.616418, 1.164773, 0.877078, -0.325099, -0.294199, 0.272016, -0.706077, -2.57027, 4.500261, 4.734375, 4.090376, 3.322846, 3.640895, 4.645253, 4.783054, 3.946184, 3.847828, 4.077601, 4.778736, 5.453883, 5.14355, 5.084551, 3.370378, 3.076065, 2.812879, 2.87688, 2.430692, 3.029766, 3.062665, 3.349906, 0.396299, 0.60174, 0.527478, 1.048755, 1.136417, 0.668333, 0.523115, 0.259175, 0.164024, 0.118469, 0.061141, 0.096251, 0.346829, 0.401832, 0.300988, 0.344943, 0.432505)),
row.names = c(NA, -78L), class = c("tbl_df", "tbl", "data.frame"), .Names = c("sec_id", "metric", "date", "value"))
factors.subset.monthly = factors.subset.raw %>%
group_by(sec_id, metric) %>%
mutate(date = ceiling_date(date, 'month')) %>%
mutate(date = map2(date, lead(date - 1, default = today()), seq, by = 'month'))
Now it suffices to add %>% unnest() %>% mutate(date = date - 1)
to the above to transform my annual data to monthly, with all dates being end of month.
My problem occurs when there is a big gap in the data. When this happens, I only want to fill forward at most 18 months.
I've tried adding pipes which cutoff the date
column, but so far I can't seem to figure it out. This little gem gives me incompatible size errors, for example:
factors.subset.monthly %>%
mutate(count.date = as.numeric(lapply(date, length))) %>%
mutate(count.cutoff = ifelse(count.date <= 18, count.date, 18)) %>%
mutate(date = date[1:count.cutoff])
回答1:
You need to use map
/lapply
to iterate over the list column, but then you can simply use head
to limit it to 18 observations:
library(tidyverse)
library(lubridate)
df <- factors.subset.monthly %>% mutate(date = map(date, head, 18))
any(lengths(factors.subset.monthly$date) > 18)
#> [1] TRUE
any(lengths(df$date) > 18)
#> [1] FALSE
You could also just include head
when you make factors.subset.monthly
:
factors.subset.raw %>%
group_by(sec_id, metric) %>%
mutate(date = ceiling_date(date, 'month'),
date = map2(date, lead(date - 1, default = today()),
~head(seq(.x, .y, by = 'month'), 18)))
You could also use the minimum of the target date or 18 months past the start date for the to
parameter of seq
, but adding 18 months is somewhat difficult due to their irregular length.
来源:https://stackoverflow.com/questions/43991620/how-to-take-subsets-of-lists-in-a-tibble