This is an extremely useful function that lets you create different summaries of columns. You can also nest other functions within it to apply them to your columns.
sum_data <- summarise(weeds, mean(flowers)) # We'll start simple. Generates the mean of the flower column
sum_data <- summarise(group_by(weeds, species), mean(flowers))
# Using the group_by() function within summarise lets you get summaries for groups, in this case "species"
sum_data <- summarise(group_by(weeds,species, soil), mean(flowers), sd(flowers), se=sd(flowers/sqrt(n())))
# Grouped by with species & soil, generating mean, standard deviation & standard error of flowersThe last example generates the mean, sd and se for each factor combination in our dataset. This is pretty useful, particularly for generating bar graphs.
However, its a little complex and can be in a much nicer format.
Use the summarise() function on the “insecticide”” dataset to answer the following question
Question: In the large fragment, what is the median species richness
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