I would like to compare the values inside a grouped data.frame using dplyr, and create a dummy variable, or something similar, indicating which is bigger. Couldn't figure it out!
Here is some reproducible code:
table <- structure(list(species = structure(c(1L, 1L, 1L, 2L, 2L, 2L), .Label = c("Adelophryne adiastola",
"Adelophryne gutturosa"), class = "factor"), scenario = structure(c(3L,
1L, 2L, 3L, 1L, 2L), .Label = c("future1", "future2", "present"
), class = "factor"), amount = c(5L, 3L, 2L, 50L, 60L, 40L)), .Names = c("species",
"scenario", "amount"), class = "data.frame", row.names = c(NA,
-6L))
> table
species scenario amount
1 Adelophryne adiastola present 5
2 Adelophryne adiastola future1 3
3 Adelophryne adiastola future2 2
4 Adelophryne gutturosa present 50
5 Adelophryne gutturosa future1 60
6 Adelophryne gutturosa future2 40
I would group the df by species.
I want to create a new column, can be increase_amount, where the amount in every "future" is compared to the "present". I could get 1 when the value has increased and 0 when it has decreased.
I have been trying with a for loop that goes throw each of the species, but the df contains over 50,000 of them and it takes too long for the times I will have to re-do the operation...
Someone know a way? Thanks a lot!
You can do something like that:
table %>%
group_by(species) %>%
mutate(tmp = amount[scenario == "present"]) %>%
mutate(increase_amount = ifelse(amount > tmp, 1, 0))
# Source: local data frame [6 x 5]
# Groups: species [2]
#
# species scenario amount tmp increase_amount
# <fctr> <fctr> <int> <int> <dbl>
# 1 Adelophryne adiastola present 5 5 0
# 2 Adelophryne adiastola future1 3 5 0
# 3 Adelophryne adiastola future2 2 5 0
# 4 Adelophryne gutturosa present 50 50 0
# 5 Adelophryne gutturosa future1 60 50 1
# 6 Adelophryne gutturosa future2 40 50 0
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