lubridate

来源： https://stackoverflow.com/questions/63563903/use-of-mutate-in-summarise-function-using-r

来源： https://stackoverflow.com/questions/63006201/mapping-sample-data-to-actual-csv-data

来源： https://stackoverflow.com/questions/63006201/mapping-sample-data-to-actual-csv-data

问题 I have a data frame like as shown below test_df <- data.frame("subject_id" = c(1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3), "date_1" = c("01/01/2003", "12/31/2007", "12/30/2008", "12/31/2005", "01/01/2007", "01/01/2013", "12/31/2008", "03/04/2006", "12/31/2009", "01/01/2015", "01/01/2009")) What I would like to do is Arrange the dates in ascending order for each subject (sort asc within groups) Remove date records for each subject based on below criteria (year doesn't matter): 2a. remove only Dec 31st

问题 For each date interval row in my dataframe, I would like to determine whether it overlaps with all other date intervals or not. Excluding itself. A dataframe with start and end date, representing intervals: `data <- read.table(header=TRUE,text=" start.date end.date 2019-09-01 2019-09-10 2019-09-05 2019-09-07 2019-08-25 2019-09-05 2019-10-10 2019-10-15 ")` This function lubridate::int_overlaps() checks if two date intervals overlap or not by returning logical TRUE or FALSE. `int_overlaps

问题 For each date interval row in my dataframe, I would like to determine whether it overlaps with all other date intervals or not. Excluding itself. A dataframe with start and end date, representing intervals: `data <- read.table(header=TRUE,text=" start.date end.date 2019-09-01 2019-09-10 2019-09-05 2019-09-07 2019-08-25 2019-09-05 2019-10-10 2019-10-15 ")` This function lubridate::int_overlaps() checks if two date intervals overlap or not by returning logical TRUE or FALSE. `int_overlaps

问题 I have the following dataset wherein, I have the person's ID, district and sub-district they live in along with the last date/time on which they uploaded data to the server. The variables "last_down_" contain the last date/time on which a person the uploaded data and are named in such a way that they show the date on which I had downloaded the data on the same. For example, "last_upload_2020-06-12" would mean I downloaded the data from the server on 12th June. For the below dataset, I would

问题 I have an R data frame like as shown below test_df <- data.frame("subbject_id" = c(1,2,3,4,5), "date_1" = c("01/01/2003","12/31/2007","12/30/2008","01/02/2007","01/01/2007")) I would like to get the no of days to prev year and next year. I was trying something like the below library(lubridate) test_df$current_yr = year(mdy(test_df$date_1)) prev_yr = test_df$current_yr - 1 #(subtract 1 to get the prev year) next_yr = test_df$current_yr + 1 #(add 1 to get the prev year) days_to_prev_yr = days

问题 I have a data frame like as shown below test_df <- data.frame("subbject_id" = c(1,2,3,4,5), "date_1" = c("01/01/2003","12/31/2007","12/30/2008","01/02/2007","01/01/2007")) test_df = test_df %>% mutate(date_1 = mdy(date_1), previous_year = floor_date(date_1, 'year'), next_year = ceiling_date(date_1, 'year') - 1, days_to_previous_year = as.integer(date_1 - previous_year), days_to_next_year = as.integer(next_year - date_1), rand_days_prev_year = sample.int(days_to_previous_year, 1), rand_days

问题 I have a data frame like as shown below test_df <- data.frame("subbject_id" = c(1,2,3,4,5), "date_1" = c("01/01/2003","12/31/2007","12/30/2008","01/02/2007","01/01/2007")) test_df = test_df %>% mutate(date_1 = mdy(date_1), previous_year = floor_date(date_1, 'year'), next_year = ceiling_date(date_1, 'year') - 1, days_to_previous_year = as.integer(date_1 - previous_year), days_to_next_year = as.integer(next_year - date_1), rand_days_prev_year = sample.int(days_to_previous_year, 1), rand_days