Calculating Average Age for Each Year Class in R Using Dplyr and Ggplot2

Understanding the Problem and Background

The problem presented is a common one in data analysis, particularly when working with multiple datasets that share similar variables but have different values. In this case, we are given a dataset with information on individuals from 50 different year classes, including age, length, maturity, quarter, area, and sex. The goal is to calculate the average age for each year class without having to input separate data sets for each class.

Introduction to R and Data Frames

To approach this problem in R, we need to understand how to work with data frames. A data frame is a two-dimensional table that can store data of any type, including numbers, text, and logical values. In R, data frames are created using the data.frame() function.

Understanding the Structure of the Data Frame

The data frame provided has seven variables: maturity, year, quarter, area, lngth (length), age, and sex. The maturity variable is an ordered factor with two levels (“0” and “1”), while the other variables are either factors or integers.

Creating a Subset of Rows for Each Year Class

To find the average age for each year class, we need to create a subset of rows that correspond to individuals in each specific year class. We can achieve this using the dplyr package, which provides various functions for data manipulation and analysis.

Installing and Loading Required Packages

# Install required packages
install.packages("dplyr")

# Load required packages
library(dplyr)

Creating a Subset of Rows for Each Year Class

We can use the group_by() function to group the rows by the year variable, and then select only those rows using the slice() function.

# Group rows by year and slice (select) one row per year class
year_class_data <- data %>%
  group_by(year) %>%
  slice(1)

This code groups the rows by the year variable, which creates a subset of rows that correspond to individuals in each specific year class. The slice() function then selects only those rows.

Calculating Average Age for Each Year Class

To calculate the average age for each year class, we can use the summarise() function from the dplyr package.

# Calculate average age for each year class
average_age <- data %>%
  group_by(year) %>%
  summarise(avg_age = mean(age))

This code groups the rows by the year variable, and then calculates the average age using the mean() function. The result is a new data frame with one row per year class, containing the average age.

Plotting Average Age for Each Year Class

Finally, we can use the ggplot2 package to create a plot that shows the average age for each year class.

# Install required packages
install.packages("ggplot2")

# Load required packages
library(ggplot2)

# Create a bar plot of average age by year class
ggplot(average_age, aes(x = reorder(year, avg_age), y = avg_age)) +
  geom_bar(stat = "identity") +
  labs(x = "Year Class", y = "Average Age")

This code creates a bar plot where the x-axis represents the year classes and the y-axis represents the average age. The reorder() function is used to sort the year classes in descending order of their average ages.

Conclusion

In this article, we discussed how to find the average age for each year class in R without having to input separate data sets for each class. We covered the basics of working with data frames and used various functions from the dplyr package to create a subset of rows for each year class and calculate the average age. Finally, we created a bar plot using the ggplot2 package to visualize the results.

Additional Resources

For more information on R and data analysis, check out the following resources:

The official R documentation: https://cran.r-project.org/doc/manuals/r-release/intro.html
The dplyr package documentation: https://dplyr.tidyverse.org/
The ggplot2 package documentation: https://ggplot2.tidyverse.org/

Last modified on 2025-02-13