I am tyring to take the top x results from a group of nested data. Adding map(data, slice(seq(n()*0.2))) to the end of the pipe function gives me errors.
So I am trying to get the top 20% of each tbl_df and return them.
Secondly How can I nest the data based on the date column? I am also trying to nest the data based on all observations between July of year t and June of year t-1. Instead of nesting them based on Yrs I would like to nest them based on a specific data range from the date column.
Data looks like (I changed all the years to 2007/2008 for this illustration):
id Yrs date var NESTID
1 1144215 2006_2007 2007-02-23 0.7897917 1
2 352510 2011_2012 2007-02-27 0.9626791 1
3 793952 2008_2009 2007-11-27 0.8186645 2
4 1368457 2014_2015 2007-03-02 0.9151516 1
5 319201 2012_2013 2007-07-20 0.9816049 2
6 882095 2017_2018 2008-03-19 0.9924851 2
So all the 1s would be in one nest and all the 2s would be in another nest, since and finally the 2008 obseration which is less tan july would be in the same nest as 2.
Code:
nested_result <- x %>%
as_tibble() %>%
group_by(Yrs) %>%
nest(.key = "data")
Data:
x <- structure(list(id = c(1144215L, 352510L, 793952L, 1368457L, 319201L,
882095L, 28412L, 1048911L, 109198L, 42293L, 97854L, 764180L,
53117L, 1038357L, 310158L, 1324404L, 1133421L, 1646383L, 1095073L,
1166691L, 1133421L, 721083L, 28412L, 1171825L, 764622L, 40493L,
27904L, 109198L, 1039684L, 916457L, 72741L, 800240L, 1168054L,
16918L, 4447L, 885639L, 1066806L, 1156039L, 732485L, 63754L,
1310067L, 720005L, 1168054L, 92122L, 310158L, 1601712L, 42582L,
70858L, 789388L, 21344L, 310764L, 835910L, 1065696L, 835541L,
863157L, 51253L, 1137774L, 1018963L, 217346L, 945436L, 1058290L,
84792L, 50104L, 8868L, 200406L, 929887L, 200406L, 64803L, 709804L,
41077L, 785161L, 1585689L, 1037868L, 769397L, 63754L, 720005L,
63541L, 33213L, 723527L, 1021860L, 4904L, 832428L, 915389L, 356028L,
1361658L, 929887L, 40987L, 352541L, 1518832L, 100893L, 1004440L,
1633917L, 14693L, 783325L, 92380L, 1043277L, 797468L, 922224L,
1018963L, 205520L), Yrs = c("2006_2007", "2011_2012", "2008_2009",
"2014_2015", "2012_2013", "2017_2018", "2008_2009", "2010_2011",
"2018_2019", "2016_2017", "2011_2012", "2018_2019", "2017_2018",
"2017_2018", "2013_2014", "2013_2014", "2014_2015", "2018_2019",
"2008_2009", "2011_2012", "2012_2013", "2010_2011", "2017_2018",
"2006_2007", "2013_2014", "2008_2009", "2015_2016", "2006_2007",
"2006_2007", "2010_2011", "2015_2016", "2012_2013", "2017_2018",
"2011_2012", "2011_2012", "2010_2011", "2006_2007", "2008_2009",
"2007_2008", "2011_2012", "2016_2017", "2008_2009", "2008_2009",
"2013_2014", "2008_2009", "2008_2009", "2006_2007", "2013_2014",
"2008_2009", "2013_2014", "2008_2009", "2009_2010", "2013_2014",
"2017_2018", "2016_2017", "2006_2007", "2011_2012", "2018_2019",
"2013_2014", "2012_2013", "2012_2013", "2011_2012", "2013_2014",
"2017_2018", "2010_2011", "2017_2018", "2018_2019", "2009_2010",
"2017_2018", "2007_2008", "2012_2013", "2008_2009", "2009_2010",
"2006_2007", "2009_2010", "2011_2012", "2015_2016", "2007_2008",
"2007_2008", "2010_2011", "2018_2019", "2007_2008", "2012_2013",
"2011_2012", "2015_2016", "2006_2007", "2007_2008", "2014_2015",
"2013_2014", "2009_2010", "2011_2012", "2016_2017", "2011_2012",
"2007_2008", "2008_2009", "2017_2018", "2014_2015", "2017_2018",
"2014_2015", "2008_2009"), date = c("2007-02-23", "2012-02-27",
"2009-11-27", "2015-03-02", "2013-02-20", "2018-03-19", "2009-02-20",
"2011-03-01", "2019-02-15", "2017-07-24", "2012-02-29", "2019-02-26",
"2018-03-20", "2018-02-21", "2014-02-27", "2014-02-06", "2015-02-26",
"2019-02-21", "2009-02-27", "2012-02-28", "2013-02-27", "2011-03-01",
"2018-02-16", "2007-02-27", "2014-12-10", "2009-08-26", "2016-08-30",
"2007-02-28", "2007-03-01", "2011-02-17", "2016-02-26", "2013-06-17",
"2018-02-23", "2012-11-16", "2012-02-24", "2011-02-24", "2007-02-28",
"2009-10-27", "2008-02-22", "2012-05-21", "2017-03-21", "2009-02-17",
"2009-03-02", "2014-02-27", "2009-02-27", "2009-02-26", "2007-02-16",
"2014-02-26", "2009-02-19", "2014-02-27", "2009-12-14", "2010-12-20",
"2014-02-07", "2018-02-22", "2017-03-24", "2007-02-15", "2012-02-15",
"2019-02-25", "2014-02-27", "2013-05-30", "2013-02-25", "2012-06-27",
"2014-02-27", "2018-02-07", "2011-02-25", "2018-02-23", "2019-02-25",
"2010-02-26", "2018-05-02", "2008-03-14", "2013-02-19", "2009-02-25",
"2010-02-19", "2007-03-01", "2010-05-24", "2012-02-21", "2016-12-20",
"2008-02-27", "2008-02-28", "2011-03-11", "2019-02-21", "2008-02-28",
"2013-02-26", "2012-02-28", "2016-02-26", "2007-02-28", "2008-07-10",
"2015-03-02", "2014-02-24", "2010-05-07", "2012-02-23", "2017-03-16",
"2012-10-31", "2008-06-27", "2009-02-11", "2018-02-27", "2015-02-13",
"2018-02-15", "2015-02-23", "2009-02-25"), var = c(0.789791703652461,
0.962679090148091, 0.818664455488741, 0.915151626033204, 0.981604875838189,
0.992485078188146, 0.919096450897814, 1, 1, 0.999495268313767,
0.971549791181422, 0.142410091613585, 0.854300303926079, 0.963969335350853,
0.100915282090841, 0.788888929835236, 0.998838037754812, 1, 0.585900427740673,
0.99197864817115, 0.963194355499937, 0.665254900669739, 0.989803980097533,
0.989481867437919, 0.50494546710205, 1, 0.955496106519928, 0.926277449400448,
0.848103309375422, 1, 0.643463529314152, 0.480751853712661, 0.912805193910848,
0.980011721979559, 0.850678323003415, 0.97329136045642, 0.9463752199707,
0.984883553015867, 0.950093429532104, 0.694897812240191, 0.988148152699705,
0.909736787656526, 0.882419459468187, 1, 1, 0.602296327788106,
0.982390900591669, 0.832481527160082, 0.970062225639918, 0.93938848599177,
0.420104624462152, 0.822785559294837, 0.922609495465592, 1, 0.847618582834581,
1, 0.998884518357301, 0.856694145446766, 0.954934410586873, 0.999483529190324,
0.964333698862739, 0.000025317480951105, 1, 1, 0.988227892981814,
0.976453170572977, 0.897281824659027, 1, 0.991392575240258, 0.918719921619656,
0.308549664065154, 0.989794242194186, 0.984928826473983, 0.921184863501297,
0.993424278980621, 0.981441305437729, 1, 1, 0.945774347345707,
0.9593304680852, 0.944686323046023, 0.954719328141632, 0.996087437964504,
0.00723186083983232, 0.998107962441803, 1, 0.999992291359637,
0.954625273413497, 0.937925176467551, 0.840391718964617, 0.976419264342728,
0.994956214638493, 0.993807958583037, 0.929808089723338, 0.497183583710065,
0.826207496536073, 1, 1, 0.827230630432659, 0.714753109251633
)), row.names = c(NA, -100L), class = "data.frame")
I use year(as.Date(date) %m+% months(6) to move anything in July or later to the next year, then paste(mod_year-1,mod_year,sep = "_") to create the label for that year. I use group_by() to rank them prior to nesting, to avoid using a loop.
library(tidyverse)
library(lubridate)
x %>%
as_tibble() %>%
mutate(mod_year = year(as.Date(date) %m+% months(6)),
mod_year = paste(mod_year-1,mod_year,sep = "_")) %>%
group_by(mod_year) %>%
filter(percent_rank(var) >= .8) %>%
nest(.key = "data")
# A tibble: 13 x 2
mod_year data
<chr> <list>
1 2010_2011 <tibble [2 × 4]>
2 2018_2019 <tibble [2 × 4]>
3 2014_2015 <tibble [2 × 4]>
4 2011_2012 <tibble [2 × 4]>
5 2009_2010 <tibble [2 × 4]>
6 2013_2014 <tibble [2 × 4]>
7 2008_2009 <tibble [3 × 4]>
8 2017_2018 <tibble [3 × 4]>
9 2006_2007 <tibble [2 × 4]>
10 2012_2013 <tibble [2 × 4]>
11 2016_2017 <tibble [1 × 4]>
12 2007_2008 <tibble [2 × 4]>
13 2015_2016 <tibble [1 × 4]>
UPDATE
Here is a more detailed example showing how the dates are grouped:
data.frame(date = seq.Date(from = as.Date("2017-01-01"),by = "months",length.out = 24)) %>%
as_tibble() %>%
mutate(mod_year = year(as.Date(date) %m+% months(6)),
mod_year = paste(mod_year-1,mod_year,sep = "_")) %>%
as.data.frame()
date mod_year
1 2017-01-01 2016_2017
2 2017-02-01 2016_2017
3 2017-03-01 2016_2017
4 2017-04-01 2016_2017
5 2017-05-01 2016_2017
6 2017-06-01 2016_2017
7 2017-07-01 2017_2018
8 2017-08-01 2017_2018
9 2017-09-01 2017_2018
10 2017-10-01 2017_2018
11 2017-11-01 2017_2018
12 2017-12-01 2017_2018
13 2018-01-01 2017_2018
14 2018-02-01 2017_2018
15 2018-03-01 2017_2018
16 2018-04-01 2017_2018
17 2018-05-01 2017_2018
18 2018-06-01 2017_2018
19 2018-07-01 2018_2019
20 2018-08-01 2018_2019
21 2018-09-01 2018_2019
22 2018-10-01 2018_2019
23 2018-11-01 2018_2019
24 2018-12-01 2018_2019