Multiple filter conditions

• We can filter on multiple conditions at once
• In computing we combine conditions in two ways “and” & “or”
• “and” means that all of the conditions must be true
• Do this in dplyr using either additional comma separate arguments

filter(surveys, species_id == "DS", year > 1995)

• Or by using &

filter(surveys, species_id == "DS" & year > 1995)

• “or” means that one or more of the conditions must be true
• Do this using |
• Say we wanted data on all of the Dipodomys species.

filter(surveys, species_id == "DS" | species_id == "DM" | species_id == "DO")

Filtering by aggregated properties

• You can also filter based on aggregated values
• If we wanted to estimate species weights only for species with > 100 individuals

species_weights <- surveys %>%
  group_by(species) %>%
  filter(n() > 100) %>%
  summarize(avg_weight = mean(weight, na.rm = TRUE))