I have a really simple question but am not able to figure out at all. animal age cat 12 dog 8 Normally I'd apply data %>% mutate(diff = age[1] - age[2]), b
I have a datafram such as COL1 COL2 COL3 G1 1 6 G1 2 6 G1 3 7 G1 4 9 G1 5 9 G1 6 9 G1 7 6 G1 8 6 G1 9 7 G1 10 7 G1 11 7 G1 12 8 G1 13 7 and I would like to rem
I have dataset input with a couple of missing values. and I have to create dataset output with the following logic: If there is a missing in any of the columns
Each primary_citation may have multiple copublications. I would like to aggregate citation_id's associated with each primary citation. The following code works
I have the following data: date_range <- c('2020-01-31', '2020-02-28', '2020-03-31', '2020-04-30', '2020-05-31',
I'm making a table like this: basic_table() %>% split_cols_by("ARM") %>% analyze(vars = c("AGE", "BMRKR1"), afun = function(x) { in_rows( "M
Running regression with panel data on different geographical levels in the US and Euro area with weights that essentially look like this: lm(log(POP25) ~ log(EM
I have a data frame df<-data.frame(Name=c('H001', 'H002', 'H003', 'H004', 'H005', 'H006', 'H007', 'H008', 'H009', 'H010'),
I have a longitudinal data set with two people in which the rows of data are numbered as 'episodes', and some episodes have a test 'result'. The goal of the bel
I have the following dplyr code: df3 <- Table3%>% group_by(Q6,Q9,Q11) %>% summarise(count = n()) %>% mutate(per = paste0(round(100 *count/sum(
Using dplyr, I'm looking to summarise a new column of data as a lagged version of an existing column of grouped data. Reprex: dateidx <- as.Date(c("2019-
Apologies if this is obvious, I don't have much experience with R. I have a function contains_leap_year(date1, date2) that I want to pass in as a condition to d
I'd like to create several new columns. They should take their names from one vector and they should be computed by taking one column in the data and dividing i
I need to merge three separate DFs ("factors_sed", "resp", and "npoc_sed") based on the shared column "Samples". Each DF contains a different number of rows (s
I have a dataframe: n <- 50 df <- data.frame(id = seq (1:n), age = sample(c(20:90), n, rep = TRUE), s
I have the following R dataframe df: library(tidyquant) start_date <- as.Date('2022-01-01') end_date <- as.Date('2022-03-31') assets_list <- c('DGS30
I have the following dataframe: # A tibble: 8 x 5 Year Group Unit Profit Sales <dbl> <chr> <chr> <dbl> <dbl> 1 2021 One
I am using dplyr to create multiple variables in my data frame using mutate. At the same time, I am using zoo to calculate a rolling average. As an example, I h
I have a dataset where I sampled abundance of 4 species across 12 months, 6 sites (5 replicates within a site). I am trying to calculate various summary stats (
The problem is similar to what posted in Combine dataframe based on index R I am trying to copy one column from df2 (huge df) to df1 (small df) but based on ind