Call pivot_longer but give it two column names in the names_to argument: One for what you are calling these objects (Var in this case), and ".value" to indicate that there should be as many new columns are there are unique tags after the _ separator: The code doesn't necessarily fail but return a warning since you have more than one value in each cell. If the number of values in each column are going to be the same you can unnest the list output. library (dplyr) library (tidyr) df %>% pivot_longer (starts_with ('Data'), values_drop_na = TRUE) %>% arrange (name) %>% pivot_wider (names_from How to use Pivot_longer to reshape from wide-type data to long-type data with multiple variables (1 answer) Closed 2 years ago . I am quite new to the whole programing stuff, but i need to skript reproducable for large datasets. A character vector specifying the new column or columns to create from the information stored in the column names of data specified by cols . If length 0, or if NULL is supplied, no columns will be created. If length 1, a single column will be created which will contain the column names specified by cols . If length >1, multiple columns will be Accounting for NA using Pivot_longer in R. 0. In `dplyr`, when use `pivot_wide` ,I want to replace 'NA' at the same time. 2. Pivot table from wide to long gives Now, I would like to usepivot_wider to keep the name and age_group but "compute" a new variable with the t2 result of the parents_total. In this example, age_group may change. If possible, I would like to compute this "t2" variable if age_group remained the same. 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). Use mutate() with across() to create the TRUE / FALSE versions of the x variables. Note that across() requires dplyr 1.0.0, which is currently in development but due for production release the week of May 25th. Use pivot_longer() to allow us to summarise() multiple measures without a lot of complicated code.
How long till we run out of fresh data to train the latest AI? Summarise after using pivot_wider. 3. Pivot_wider function (tidyr r package) from multiple
