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 flowers
```

The 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**

Answer

**12**