I am looking for a method that will look at each date in "Date A" and find the next nearest date after that value in "Date B" by ID (group_by). I then want to c
I'd like to add a new variable to a dataframe for plotting labels, as seen in the top voted answer here Here's the data: small <- structure(list(Site = stru
vertejumi_ceturksnos <- data.frame( Vertejumi = c("0", "1", "2", "3"), Pirmais = c(Pirmaiss), Otrais = c(Otraiss), Tresais = c(Tresaiss), Ce
If i have the following table: tibble(year = c("2020", "2020", "2020","2021", "2021", "2021"), website = c("facebook", "google", "youtube","facebook", "
I have a column which list timestamps and I am in need of converting that to corresponding date for all rows in that column. Listing the code below app21_csv &
I frequently use the dplyr piping to get a column from a tibble into a vector as below iris %>% .$Sepal.Length iris %>% .$Sepal.Length %>% cut(5) How
I have binary data in a dataframe with a time feature and I'm looking to produce a dataframe like below with a new column "duration since =1". I was able to fi
I am trying to use the n_distinct function from dplyr inside a pipe in a function and am finding it to be sensitive to my choice of syntax in a way I didn't exp
I try to conditionally replace multiple values in a data frame. In the following data set, I want to replace in columns 3:5 all values of 2 by "X" and all value
I have the following data frame as an example: match_id <- c("match_1", "match_1","match_1","match_2","match_2","match_2","match_3","match_3","match_3", "mat
I would like to filter using multiple variables in R. I got a way of doing so. How about if I only want to select the variables that meet the filtering criteria
I would like to perform following operation in Pandas: library(tidyverse) df <- tibble(mtcars) df %>% select(ends_with('t')) %>% head(3) # A
I want to get a Mahalanobis difference for each set of two scores, after being grouped by another variable. In this case, it would be a Mahalanobis difference f
Let's say I have the following dataset: dat <- read.table(text="id_1 id_2 123 NA 456 NA NA 3
I'm scraping data from a website and depending on the structure of the page. I have an inner join in my final table that either joins clean on WON and LOST vari
Hello and thank you for you time and consideration, I'd like to recreate this graph with ggplot. The top blue dots are the predicted values from my fitted model
I have a dataframe of US zipcodes and I want to add a sequence of numbers to each unique zipcode while repeating the rest of the rows. Right now, my data looks
I'm trying to utilize the uniroot function inside a piping scheme. I have root data by depth, and I fit a model for each crop-year set and put the fitted parame
I'm trying to utilize the uniroot function inside a piping scheme. I have root data by depth, and I fit a model for each crop-year set and put the fitted parame
I want to keep the order of the output variables the same as the order they were created in the mutate statement. How do I accomplish this? It seems to be reor