How do I combine data taken separately into a single dataset? - r

Question

I have a dataset comprised of leaves which I've weighed individually in order of emergence (first emerged through final emergence), and I'd like to combine these masses so that I have the entire mass of all the leaves for each individual plant.
How would I add these up using R programming language, or what would I need to google to get started on figuring this out?
structure(list(Tray = c(1, 1, 1, 1, 1, 1), Plant = c(2, 2, 2,
2, 3, 3), Treatment = structure(c(4L, 4L, 4L, 4L, 4L, 4L), .Label = c("2TLH",
"E2TL", "EH", "WL"), class = "factor"), PreSwitch = c("Soil",
"Soil", "Soil", "Soil", "Soil", "Soil"), PostSwitch = c("Soil",
"Soil", "Soil", "Soil", "Soil", "Soil"), Pellet = c(1, 1, 1,
1, 1, 1), Rep = c(1, 1, 1, 1, 1, 1), Date = structure(c(1618963200,
1618963200, 1618963200, 1618963200, 1618963200, 1618963200), tzone = "UTC", class = c("POSIXct",
"POSIXt")), DAP = c(60, 60, 60, 60, 60, 60), Position = c(2,
1, 3, 4, 4, 3), Whorl = structure(c(1L, 1L, 2L, 2L, 2L, 2L), .Label = c("1",
"2", "3", "4", "5"), class = "factor"), PetioleLength = c(1.229,
1.365, 1.713, 1.02, 0, 1.408), BladeLength = c(1.604, 1.755,
2.466, 2.672, 0.267, 2.662), BladeWidth = c(1.023, 1.185, 1.803,
1.805, 0.077, 1.771), BladeArea = c(1.289, 1.634, 3.492, 3.789,
0.016, 3.704), BladePerimeter = c(6.721, 7.812, 11.61, 12.958,
1.019, 14.863), BladeCircularity = c(0.359, 0.336, 0.326, 0.284,
0.196, 0.211), BPR = c(1.30512611879577, 1.28571428571429, 1.43957968476357,
2.61960784313725, NA, 1.890625), Leaf.Mass = c(9, 11, 31, 33,
32, 33), BladeAR = c(1.56793743890518, 1.48101265822785, 1.36772046589018,
1.4803324099723, 3.46753246753247, 1.50310559006211), Subirrigation = c(0,
0, 0, 0, 0, 0), Genotype = c(1, 1, 1, 1, 1, 1), Location = c(0,
0, 0, 0, 0, 0)), row.names = c(NA, -6L), class = c("tbl_df",
"tbl", "data.frame"))

Answer 1

I may be missing something but isn't this a sum by Plant?
One solution below sums it for each plant into a separate table with just the totals and the second summarizes and adds it back to the main data set in a single step.
library(tidyverse)
#summary data set
plant_total <- df %>% group_by(Plant) %>% summarize(plant_weight = sum(Leaf.Mass, na.rm= TRUE))
#add plant_weight column to df data set
plant_total <- df %>% group_by(Plant) %>% mutate(plant_weight = sum(Leaf.Mass, na.rm = TRUE))