Discard 200 random healthy instances. How do I implement this in Rstudio? This is the data frame: https://www.kaggle.com/code/jamaltariqcheema/model-performance
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 am using the cmprsk package to create a series of regressions. In the real models I used, I specified my models in the same way that is shown in the example t
I am using the word_associate package in R Markdown to create word clouds across a grouping variable with multiple categories. I would like the titles of each w
I'm not able to solve the following problem with shiny app: a reactive object will be created after some procedures. In the middle of the way there is an action
My data looks like this newdata APPLICATION USER APPLICANT 25428X. P991. A1 25428X. P929. A2 26619L. P929. A1 26619L. P991. A2 This is what I am looking for
I know the question was asked many times but still i'm copying empty file. let's assume i have 50000k files and i have around 3000 file names as a vector so i w
This is my shiny application: ui.R # values to show, or not show, these will be the 'choices' and 'selected' values # for the checkboxGroupInput() all_rows <
The code drops the columns that are not required from the table: inputData <- inputData[,!(colnames(inputData) %in% c('col1','col2',''))] Need help converti
I have asked a similar question before and tried to use the answers (which were very good) on my project, but I failed. I have the following dataframe: library(
I have the following data: date_range <- c('2020-01-31', '2020-02-28', '2020-03-31', '2020-04-30', '2020-05-31',
Since my question is similar to one that's been asked before, I'll steal the reprex (also below), for consistency's sake, from Summary Table (mean + std.error)
**UPDATE My data set contains 314090 observations in the following format: UPDATEDID BRIEF_ID gamma LDR_SUM LDR_Topic LDR_7Code 16 04999120040277 2.879744e-03
I'm making a table like this: basic_table() %>% split_cols_by("ARM") %>% analyze(vars = c("AGE", "BMRKR1"), afun = function(x) { in_rows( "M
Given the following R script: library(glue) library(ggplot2) library(tidyverse) library(magrittr) library(stringi) library(dplyr) ir.data <- read.csv(file="
I have this sampled code that I tried on RStudio these last days : library ('terra') binar <- rast("C:/Users/BIC_/Desktop/21_binarisation_SWIR.tif") poly_ra
I want to convert date of birth to age using the following code df$age <- round(as.numeric(Sys.Date()-as.Date(df$DOB),format="%d/%m/%y")/365) The format of
I have a task, which is too complex for my R-knowledge. I have a dataframe with Tweets-data, including a column that consists of the usernames, data of the Twee
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