Remember to

• Load surveys.csv data into surveys

Basic aggregation

• Aggregation combines rows into groups based on one of more columns.
• Calculates combined values for each group.
• First, group the data frame.

group_by(surveys, species_id)

• Different looking kind of data.frame
  • Source, grouping, and data type information

surveys_by_species <- group_by(surveys, species_id)

• Use summarize() to calculate values for each group.
• Count the number of rows for each group (individuals in each species).

summarize(surveys_by_species, abundance = n())

• Can group by multiple columns

surveys_by_species_plot <- group_by(surveys, species_id, plot_id)
summarize(surveys_by_species, abundance = n())

• Use any function that returns a single value from a vector.
• E.g., mean, max, min

species_weight <- summarize(surveys_by_species_plot, avg_weight = mean(weight))

• Open table
• Why did we get NA?
  • mean(weight) returns NA when weight has missing values (NA)
• Can fix using mean(weight, na.rm = TRUE)

species_weight <- summarize(surveys_by_species,
                            avg_weight = mean(weight, na.rm = TRUE))

• Still has NaN for species that have never been weighed
• Can use na.omit() to drop rows with NA or NaN in any column

na.omit(surveys_weight)

Do Shrub Volume Aggregation.