Subsetting a Dataframe Based on Daily Maxima

Introduction

In this article, we will explore how to subset a dataframe in R based on daily maxima. This is a common problem in data analysis where we need to identify the maximum value for each day and the corresponding time.

Problem Statement

Given an excel csv file with a date/time column and a value associated with that date/time, we want to write a script that will go through this format:

and find:

1. The maximum value per day
2. The time on that day that the maximum occurs

preferably in a new dataframe.

Solution using plyr Package

A solution using the plyr package, which is widely used for data manipulation tasks, can be implemented as follows:

library(plyr)

# Read excel file into R
dat <- read.table(textConnection(dat.str), row.names=1, header=TRUE)

# Subset dataframe based on daily maxima
result <- ddply(dat, .(V1), function(x){
   x[which.max(x$V3), ]
})

# Print result
print(result)

In this code:

• We first load the plyr package.
• We then read the excel file into R using read.table.
• We use ddply to subset the dataframe based on daily maxima. The .( notation indicates that we want to group by the V1 column, and the function(x){...} block specifies the function to apply to each group.
• Inside the function, we find the maximum value using which.max(x$V3) and use it to index into the dataframe.

Explanation

The ddply function from the plyr package is a versatile tool for data manipulation. It allows us to perform various operations, such as grouping, aggregating, and transforming data.

In this case, we group by the V1 column (which represents the date) and apply a custom function to each group. The function finds the maximum value in the V3 column for each group and returns the corresponding row from the dataframe.

Alternative Solution using GroupBy Function

Alternatively, you can use the dplyr package’s group_by function to achieve the same result:

library(dplyr)

# Read excel file into R
dat <- read.table(textConnection(dat.str), row.names=1, header=TRUE)

# Subset dataframe based on daily maxima
result <- dat %>%
   group_by(V1) %>%
   slice(which.max(V3))

# Print result
print(result)

In this code:

• We load the dplyr package.
• We read the excel file into R using read.table.
• We use group_by to group by the V1 column and slice to select the row with the maximum value in the V3 column.

Both solutions produce the same result, but the dplyr package provides a more modern and concise syntax for data manipulation tasks.

Last modified on 2025-03-03