I'm trying to make an example for a table where you have the parameters to analyze the trend:
dat <- data.frame(
x = c(-56.1645, -55.7594, -57.9515), #Longitude
y = c(-34.9011, -34.9033, -31.7333), # Latitude
slope = rnorm(3), # trend
p_value = c(0.002, 0.0001, 0.1) # significance
)
Then I add a column to indicate if the trend is significant or not:
dat_sf$sig <- ifelse(dat$p_value < 0.001, "Significance", "Not significance")
So, now I need to add another column that contains information whether the trend is positive, negative or does not exist from the p_value and slope
I wrote it:
if (dat$p_value < 0.001 & dat$slope >= 0) {
dat_sf$tendencia <- "Increase"
} else if(dat$pvalue < 0.001 & dat$slope <= 0) {
dat_sf$tendencia <- "Decrease"
} else if(dat$pvalue > 0.001) {
dat_sf$tendencia <- "Not trend"
}
But it gives me an error:in if (datos$p_value < 0.001 & datos$slope >= 0) { : the condition has length > 1
The error occurs because
if()is not vectorised. You may instead want to useifelse(). Using this, you could e.g. modifydatsimilar to