r - Using dcast to widen a data frame - Stack Overflow
Jul 19, 2013 · Using dcast to widen a data frame Asked 12 years, 6 months ago Modified 6 years, 2 months ago Viewed 31k times
Long to wide format using dcast in r - Stack Overflow
Nov 4, 2022 · The main issue here would be calling the dcast function i.e. dcast is available in data.table and reshape2 packages. If the data is data.table, it calls the data.table::dcast instead of the …
dcast warning: ‘Aggregation function missing: defaulting to length’
Therefore dcast wants to aggregate these values into one value. The default aggregation function is length, but you can use other aggregation functions like sum, mean, sd or a custom function by …
How can I use dcast based on multiple columns? - Stack Overflow
Feb 8, 2016 · And I want to create new columns based first on the order within a specific year, but then sequentially on the order if I shift it. As you can see value=16 which starts as order=3 on row 1, is …
R: Melt and Dcast - Stack Overflow
Apr 14, 2017 · R: Melt and Dcast Asked 9 years ago Modified 8 years, 10 months ago Viewed 2k times
Customize names of columns created by dcast.data.table
Customize names of columns created by dcast.data.table Asked 11 years, 4 months ago Modified 1 year, 7 months ago Viewed 13k times
Reshape multiple value columns to wide format - Stack Overflow
Jul 23, 2012 · Reshaping from long to wide format with multiple value/measure columns is now possible with the new function pivot_wider() introduced in tidyr 1.0.0. This is superior to the previous tidyr …
r - Error using dcast with multiple value.var - Stack Overflow
The answer/problem is that you need to "force" the data.table dcast function otherwise it will use the reshape2 function The only way I was successfull was running dcast as follows:
r - Reshape data using dcast? - Stack Overflow
Aug 8, 2013 · I don't know if using dcast() is the right way, but I want to reshape the following data.frame:
r - on dcast () argument "value.var" - Stack Overflow
So, I used dcast() on a dataframe last time in which one column was ID and the other multiple codes assigned per id. My df1 looked like this: ID codes gfreq 123 FGV34 0.988 123 FGV34 ...