dave_in_newengland
Reputation: 251
Using intervals to identify if a column of dates is within a vector of other dates
I was trying to take a vector of dates (recession dates), create an interval, and then use this interval to create a new column in an existing data frame indicating whether a date fell within a recession period.
I am sure there are multiple ways to do this, but the way I was trying did not work and I wasn't sure how to fix. I was trying to use this approach but to no avail.
Reproducible Example
library(tidyverse)
library(lubridate)
# dput data
recession_dates <- structure(list(start = structure(c(4199, 7486, 11382, 13848), class = "Date"),
stop = structure(c(4687, 7729, 11627, 14396), class = "Date")), class = c("tbl_df",
"tbl", "data.frame"), row.names = c(NA, -4L))
my_df <- structure(list(Date = structure(c(3742, 3833, 3925, 4017, 4107,
4198, 4290, 4382, 4472, 4563, 4655, 4747, 4837, 4928, 5020, 5112,
5203, 5294, 5386, 5478, 5568, 5659, 5751, 5843, 5933, 6024, 6116,
6208, 6298, 6389, 6481, 6573, 6664, 6755, 6847, 6939, 7029, 7120,
7212, 7304, 7394, 7485, 7577, 7669, 7759, 7850, 7942, 8034, 8125,
8216, 8308, 8400, 8490, 8581, 8673, 8765, 8855, 8946, 9038, 9130,
9220, 9311, 9403, 9495, 9586, 9677, 9769, 9861, 9951, 10042,
10134, 10226, 10316, 10407, 10499, 10591, 10681, 10772, 10864,
10956, 11047, 11138, 11230, 11322, 11412, 11503, 11595, 11687,
11777, 11868, 11960, 12052, 12142, 12233, 12325, 12417, 12508,
12599, 12691, 12783, 12873, 12964, 13056, 13148, 13238, 13329,
13421, 13513, 13603, 13694, 13786, 13878, 13969, 14060, 14152,
14244, 14334, 14425, 14517, 14609, 14699, 14790, 14882, 14974,
15064, 15155, 15247, 15339, 15430, 15521, 15613, 15705, 15795,
15886, 15978, 16070, 16160, 16251, 16343, 16435, 16525, 16616,
16708, 16800, 16891, 16982, 17074, 17166, 17256, 17347, 17439,
17531, 17621, 17712, 17804, 17896, 17986, 18077, 18169), class = "Date"),
Asset = c("real_gdp_usd2012", "real_gdp_usd2012", "real_gdp_usd2012",
"real_gdp_usd2012", "real_gdp_usd2012", "real_gdp_usd2012",
"real_gdp_usd2012", "real_gdp_usd2012", "real_gdp_usd2012",
"real_gdp_usd2012", "real_gdp_usd2012", "real_gdp_usd2012",
"real_gdp_usd2012", "real_gdp_usd2012", "real_gdp_usd2012",
"real_gdp_usd2012", "real_gdp_usd2012", "real_gdp_usd2012",
"real_gdp_usd2012", "real_gdp_usd2012", "real_gdp_usd2012",
"real_gdp_usd2012", "real_gdp_usd2012", "real_gdp_usd2012",
"real_gdp_usd2012", "real_gdp_usd2012", "real_gdp_usd2012",
"real_gdp_usd2012", "real_gdp_usd2012", "real_gdp_usd2012",
"real_gdp_usd2012", "real_gdp_usd2012", "real_gdp_usd2012",
"real_gdp_usd2012", "real_gdp_usd2012", "real_gdp_usd2012",
"real_gdp_usd2012", "real_gdp_usd2012", "real_gdp_usd2012",
"real_gdp_usd2012", "real_gdp_usd2012", "real_gdp_usd2012",
"real_gdp_usd2012", "real_gdp_usd2012", "real_gdp_usd2012",
"real_gdp_usd2012", "real_gdp_usd2012", "real_gdp_usd2012",
"real_gdp_usd2012", "real_gdp_usd2012", "real_gdp_usd2012",
"real_gdp_usd2012", "real_gdp_usd2012", "real_gdp_usd2012",
"real_gdp_usd2012", "real_gdp_usd2012", "real_gdp_usd2012",
"real_gdp_usd2012", "real_gdp_usd2012", "real_gdp_usd2012",
"real_gdp_usd2012", "real_gdp_usd2012", "real_gdp_usd2012",
"real_gdp_usd2012", "real_gdp_usd2012", "real_gdp_usd2012",
"real_gdp_usd2012", "real_gdp_usd2012", "real_gdp_usd2012",
"real_gdp_usd2012", "real_gdp_usd2012", "real_gdp_usd2012",
"real_gdp_usd2012", "real_gdp_usd2012", "real_gdp_usd2012",
"real_gdp_usd2012", "real_gdp_usd2012", "real_gdp_usd2012",
"real_gdp_usd2012", "real_gdp_usd2012", "real_gdp_usd2012",
"real_gdp_usd2012", "real_gdp_usd2012", "real_gdp_usd2012",
"real_gdp_usd2012", "real_gdp_usd2012", "real_gdp_usd2012",
"real_gdp_usd2012", "real_gdp_usd2012", "real_gdp_usd2012",
"real_gdp_usd2012", "real_gdp_usd2012", "real_gdp_usd2012",
"real_gdp_usd2012", "real_gdp_usd2012", "real_gdp_usd2012",
"real_gdp_usd2012", "real_gdp_usd2012", "real_gdp_usd2012",
"real_gdp_usd2012", "real_gdp_usd2012", "real_gdp_usd2012",
"real_gdp_usd2012", "real_gdp_usd2012", "real_gdp_usd2012",
"real_gdp_usd2012", "real_gdp_usd2012", "real_gdp_usd2012",
"real_gdp_usd2012", "real_gdp_usd2012", "real_gdp_usd2012",
"real_gdp_usd2012", "real_gdp_usd2012", "real_gdp_usd2012",
"real_gdp_usd2012", "real_gdp_usd2012", "real_gdp_usd2012",
"real_gdp_usd2012", "real_gdp_usd2012", "real_gdp_usd2012",
"real_gdp_usd2012", "real_gdp_usd2012", "real_gdp_usd2012",
"real_gdp_usd2012", "real_gdp_usd2012", "real_gdp_usd2012",
"real_gdp_usd2012", "real_gdp_usd2012", "real_gdp_usd2012",
"real_gdp_usd2012", "real_gdp_usd2012", "real_gdp_usd2012",
"real_gdp_usd2012", "real_gdp_usd2012", "real_gdp_usd2012",
"real_gdp_usd2012", "real_gdp_usd2012", "real_gdp_usd2012",
"real_gdp_usd2012", "real_gdp_usd2012", "real_gdp_usd2012",
"real_gdp_usd2012", "real_gdp_usd2012", "real_gdp_usd2012",
"real_gdp_usd2012", "real_gdp_usd2012", "real_gdp_usd2012",
"real_gdp_usd2012", "real_gdp_usd2012", "real_gdp_usd2012",
"real_gdp_usd2012", "real_gdp_usd2012", "real_gdp_usd2012",
"real_gdp_usd2012", "real_gdp_usd2012", "real_gdp_usd2012",
"real_gdp_usd2012", "real_gdp_usd2012", "real_gdp_usd2012"
), Value = c(6837.6, 6696.8, 6688.8, 6813.5, 6947, 6895.6,
6978.1, 6902.1, 6794.9, 6825.9, 6799.8, 6802.5, 6892.1, 7049,
7189.9, 7339.9, 7483.4, 7612.7, 7686.1, 7749.2, 7824.2, 7893.1,
8013.7, 8073.2, 8148.6, 8185.3, 8263.6, 8308, 8369.9, 8460.2,
8533.6, 8680.2, 8725, 8839.6, 8891.4, 9009.9, 9101.5, 9171,
9238.9, 9257.1, 9358.3, 9392.3, 9398.5, 9312.9, 9269.4, 9341.6,
9388.8, 9421.6, 9534.3, 9637.7, 9733, 9834.5, 9851, 9908.3,
9955.6, 10091, 10189, 10327, 10387.4, 10506.4, 10543.6, 10575.1,
10665.1, 10737.5, 10817.9, 10998.3, 11097, 11212.2, 11284.6,
11472.1, 11615.6, 11715.4, 11832.5, 11942, 12091.6, 12287,
12403.3, 12498.7, 12662.4, 12877.6, 12924.2, 13160.8, 13178.4,
13260.5, 13222.7, 13300, 13244.8, 13280.9, 13397, 13478.2,
13538.1, 13559, 13634.3, 13751.5, 13985.1, 14145.6, 14221.1,
14329.5, 14465, 14609.9, 14771.6, 14839.8, 14972.1, 15066.6,
15267, 15302.7, 15326.4, 15456.9, 15493.3, 15582.1, 15666.7,
15762, 15671.4, 15752.3, 15667, 15328, 15155.9, 15134.1,
15189.2, 15356.1, 15415.1, 15557.3, 15672, 15750.6, 15712.8,
15825.1, 15820.7, 16004.1, 16129.4, 16198.8, 16220.7, 16239.1,
16383, 16403.2, 16531.7, 16663.6, 16616.5, 16841.5, 17047.1,
17143, 17277.6, 17405.7, 17463.2, 17468.9, 17556.8, 17639.4,
17735.1, 17824.2, 17925.3, 18021, 18163.6, 18322.5, 18438.3,
18598.1, 18732.7, 18783.5, 18927.3, 19021.9, 19112.5)), row.names = c(NA,
-159L), class = "data.frame")
# Turn recession dates into recession intervals
recession_intervals <- interval(recession_dates$start, recession_dates$stop)
# Test to see if works
my_df %>% mutate(recession = Date %within% recession_intervals)
Does not work:
# partial output
> my_df %>% mutate(recession = Date %within% recession_intervals)
Date Asset Value recession
1 1980-03-31 real_gdp_usd2012 6837.6 FALSE
2 1980-06-30 real_gdp_usd2012 6696.8 FALSE
3 1980-09-30 real_gdp_usd2012 6688.8 FALSE
4 1980-12-31 real_gdp_usd2012 6813.5 FALSE
5 1981-03-31 real_gdp_usd2012 6947.0 FALSE
6 1981-06-30 real_gdp_usd2012 6895.6 FALSE
7 1981-09-30 real_gdp_usd2012 6978.1 FALSE
8 1981-12-31 real_gdp_usd2012 6902.1 FALSE
9 1982-03-31 real_gdp_usd2012 6794.9 TRUE
10 1982-06-30 real_gdp_usd2012 6825.9 FALSE
11 1982-09-30 real_gdp_usd2012 6799.8 FALSE
12 1982-12-31 real_gdp_usd2012 6802.5 FALSE
13 1983-03-31 real_gdp_usd2012 6892.1 FALSE
However, this doesn't work as the output does not return TRUE for any date within a recession period (plus it generates lots of warning messages).
If someone could tell me the correct way to use this approach (a different scalable approach using dplyr would be ok too) I would appreciate it!
Dave
Upvotes: 3
Views: 152
Answers (1)
thelatemail
Reputation: 93803
Looking at the help file you linked, you need to make sure the intervals are in a list for them to be compared properly.
recycled according to standard R rules. If
bis a list of intervals,ais checked if it falls within any of the intervals inb.
Therefore, this should work:
my_df %>% mutate(recession = Date %within% as.list(recession_intervals))
Upvotes: 3
Related Questions
- Part 2: Check if any dates within an Interval are within any of the dates in another Interval
- Check if any dates within an Interval are within any of the dates in another Interval
- R: Determine if each date interval overlaps with all other date intervals in a dataframe
- How to find if a date is within a given time interval
- Checking that a series of dates are within a series of different intervals
- How to check if several dates lie within a interval using data.table and lubridate?
- Is there a way in r to check if each date of a list of dates is within a list of intervals?
- Checking if there exists a value in vector of dates that lies within a given range
- Check if any dates in a group are within specific time intervals for that group in r
- Check if a date is within an interval in R