How to write a small function to extract mean month from dataset

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Summary

The error in the provided R function month_mean occurs because the filter function from the dplyr package expects a logical vector as its first argument, but it is being passed a numeric value 5. This is due to a misunderstanding of how to properly use the filter function in conjunction with the function’s parameters.

Root Cause

The root cause of this issue is the incorrect usage of the filter function within the month_mean function. The filter function is used to subset a data frame based on conditions, but in this case, it is being passed a numeric value tframe directly, which is not a valid condition. The correct approach would be to create a condition that compares a column in the data frame to the tframe value.

Why This Happens in Real Systems

This type of error can occur in real systems when:

  • Developers are new to using dplyr and its functions.
  • There is a lack of understanding of how to properly pass conditions to the filter function.
  • The function is not tested thoroughly with different types of inputs.

Real-World Impact

The real-world impact of this error includes:

  • Inability to correctly filter data based on specific conditions.
  • Potential for incorrect analysis or insights due to improperly filtered data.
  • Wasted time and resources trying to debug and fix the issue.

Example or Code

library(dplyr)

fish <- structure(list(month = c(5, 5, 5, 5, 5, 6, 6, 6, 7, 7, 7, 7, 8, 8), 
                     xd = c(NA, NA, NA, 0.023094, 0.027764, 0.030157, 0.03237, 0.031203, 0.032884, 0.030312, 0.039739, 0.043248, 0.039717, 0.037961 ), 
                     pd = c(NA, NA, NA, 7, 2, 8, 4, 25, 36, 45, 1, 2, 9, 0)), 
                class = c("tbl_df", "tbl", "data.frame"), row.names = c(NA, -14L))

month_mean <- function(dat, tframe, column) {
  m <- filter(dat, month == tframe)
  mean(m[[column]], na.rm = TRUE)
}

month_mean(fish, 5, "pd")

How Senior Engineers Fix It

Senior engineers fix this issue by:

  • Correctly using the filter function with a logical condition that compares the month column to the tframe value.
  • Ensuring that the function is properly tested with different inputs and edge cases.
  • Using dplyr functions correctly and efficiently.

Why Juniors Miss It

Juniors may miss this issue because:

  • Lack of experience with dplyr and its functions.
  • Insufficient understanding of how to properly create and use logical conditions in the filter function.
  • Inadequate testing of the function with different types of inputs.