summarize()

This lesson is called summarize(), part of the Fundamentals of R course. This lesson is called summarize(), part of the Fundamentals of R course.

Transcript

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# Load Packages -----------------------------------------------------------

library(tidyverse)

# Import Data -------------------------------------------------------------

penguins <-
  read_csv("penguins.csv")

# summarize() -------------------------------------------------------------

# With summarize(), we can go from a complete dataset down to a summary.

# We use any of the summary functions with summarize().
# Here's how we calculate the mean bill length.

penguins |>
  summarize(mean_bill_length = mean(bill_length_mm))

# This doesn't work! Notice what the result is.

# We need to add na.rm = TRUE to tell R to drop NA values.

penguins |>
  summarize(mean_bill_length = mean(bill_length_mm, na.rm = TRUE))

# Another option is to drop NA values before calling summarize().

penguins |>
  drop_na(bill_length_mm) |>
  summarize(mean_bill_length = mean(bill_length_mm))

# We can have multiple arguments in each usage of summarize().

penguins |>
  summarize(
    mean_bill_length = mean(bill_length_mm, na.rm = TRUE),
    max_bill_depth = max(bill_depth_mm, na.rm = TRUE)
  )

penguins |>
  summarize(mean_bill_length = mean(bill_length_mm, na.rm = TRUE)) |>
  summarize(mean_bill_depth = mean(bill_depth_mm, na.rm = TRUE))

Your Turn

# Load Packages -----------------------------------------------------------

# Load the tidyverse package

library(tidyverse)

# Import Data -------------------------------------------------------------

penguins <- read_csv("penguins.csv")
			
# Calculate the weight of the heaviest penguin.
# Don't forget to drop NAs!

# YOUR CODE HERE

# Calculate the minimum and maximum weight of penguins in the dataset.

# YOUR CODE HERE