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Create a New Data Frame

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View code shown in video 
# Load Packages -----------------------------------------------------------

library(tidyverse)

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

penguins <- read_csv("penguins.csv")

# Create a New Data Frame -------------------------------------------------

# Running pipelines simply displays the result

penguins |> 
  group_by(island, year) |> 
  summarize(mean_bill_length = mean(bill_length_mm, na.rm = TRUE)) |> 
  arrange(mean_bill_length)

# If we want to save the result, we need to use the assignment operator

# Most people use the left-hand assignment operator as follows:

penguin_weight_by_island <- penguins |> 
  group_by(island, year) |> 
  summarize(mean_bill_length = mean(bill_length_mm, na.rm = TRUE)) |> 
  arrange(mean_bill_length)

# You can also use the right-hand assignment operator as follows:

penguins |> 
  group_by(island, year) |> 
  summarize(mean_bill_length = mean(bill_length_mm, na.rm = TRUE)) |> 
  arrange(mean_bill_length) -> penguin_weight_by_island_v2

Your Turn

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

# Load the tidyverse package

library(tidyverse)

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

# Download data from https://rfor.us/penguins
# Copy the data into the RStudio project
# Create a new R script file and add code to import your data

penguins <- read_csv("penguins.csv")
			
# Create a new data frame -------------------------------------------------

# Take the pipeline that you just created and copy it below
# Then assign the result of the pipeline to an object called penguin_body_mass_by_sex

# YOUR CODE HERE

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