Is there a way to achieve the same goal while in a wide format? Or will I need to use pivot_longer to change the data. Thanks in advance! ETA had an edit here but was giving incorrect results and so have removed Still looking for some help on the arguments and same length. ETA Version 2. I did find a workaround using pairwise.t.test (code below). reshape to long format with pivot_longer - taking into account the pattern in names with either names_sep or names_pattern, specify the names_to as a vector of c (".value", "trait") in the same order we want the column values and the suffix value to be stored as separate columns. How to construct multiple columns at one time in R. So I have 6 columns. Sept2020, Oct2020, Nov2020, sept2020_rank, oct2020_rank, and nov2020_rank. it is my assumption that to produce a ggplot plot where time is the x axis and rank is the y-axis, I have to first make it into long (example below) My first attempt is above. You can then use simple tidyselect helper functions to grab the columns you would like to pivot_longer. For instance, replace all column names with e.g. YRxxxx where xxxx is the relevant year. For instance, replace all column names with e.g. YRxxxx where xxxx is the relevant year. I am trying to create a table from a data set that takes two factors from a variable, pivots them wider, and lines them up in a single row. Unfortunately, I either keep producing two separate lists, or I get this: dput (head (test1, 5)) # Edited section: test1 <- df %>% # Code used to create the table below select (`Incident ID`,`Device Time Viewed 705 times. Part of R Language Collective. 5. I'm trying to pivot to a longer format using dplyr::pivot_longer, but can't seem to get it to do what I want. I can manage with reshape::melt, but I'd also like to be able to achieve the same using pivot_longer. The data I'm trying to reformat is a correlation matrix of the mtcars-dataset: In the tidyverse, “tidy” data is a very opinionated term so that we can all talk about data with more common ground. The goal of the tidyr package is to help you create tidy data. Tidy data is data where: Every column is variable. Every row is an observation. Every cell is a single value. where each row is one country-year and the columns represent the different variables with a suffix for each group. I think I'll have to use pivot_wider() but couldn't figure out how to preserve the country-year combination. Can someone point me into the right direction? We will aim to reshape the tidy data to wider form such that year variable is on columns and the mobile_subs are values in the wide dataframe. We can reshape using tidyr’s pivot_wider () function. We first select only the variables of interest to reshape and then use pivot_wider () with arguments “names_from” and “values_from”. When manipulating your data, you might want to change the shape of our data from long data to wide data. This video will walk you through how to use pivot_wi 0jaay6.