Eliminating Observations with No Variation Over Time Using R

Elimination of observations that do not vary over the period with R (r-cran)

Introduction

In this article, we will explore how to eliminate observations in a dataset that do not exhibit variation over time. This is a common task in data analysis and statistics, particularly when working with panel or longitudinal data.

Suppose we have a dataset containing information on various countries, including their source and destination countries. We are interested in analyzing the changes in a specific variable (HS04) across different years for each country pair. However, some observations do not show any change in the value of HS04 over time. In this case, we want to exclude these observations from our analysis.

Understanding the Problem

To approach this problem, let’s first understand what it means for an observation to exhibit variation over time. An observation exhibits variation if its value changes between two consecutive years or periods. In other words, if the initial and final values of a variable are different, then that observation is considered to have varied.

For example, consider the country pair ARG and BRA. If HS04 varies from 1 in 1989 to 0 in 2010 (or vice versa), we would expect that observation to exhibit variation. On the other hand, if both initial and final values of HS04 are 1 (as seen in our sample data for HS04 0101), it means there is no change in the value over time.

Solution

We can use R’s dplyr package to achieve this task. Here’s how we can do it:

# Load required libraries
library(dplyr)

# Create a sample dataset (Note: actual dataset may vary)
data <- read.table(text = "
               Year   source   destination   HS04   value
               1989    ARG        BRA        0101     1
               1989    ARG        BRA        0102     0
               1989    ARG        BRA        0103     0
               1989    ARG        BRA        0104     1
               2010    ARG        BRA        0101     1
               2010    ARG        BRA        0102     1
               2010    ARG        BRA        0103     1
               2010    ARG        BRA        0104     1
",header=T)

Step-by-Step Solution

Here’s the step-by-step solution to eliminate observations that do not vary over time:

Grouping by HS04

# Group data by HS04 variable
data %&gt;% group_by(HS04)

We start by grouping our dataset by the HS04 variable. This is because we are interested in analyzing changes in the value of HS04 for each unique value of HS04.

Creating a flag column

# Create a new column 'flag' to indicate if the value varied over time
mutate(flag = ifelse(min(value) &amp; max(value)==1, 1, 0))

Next, we create a new column called ‘flag’. We use the ifelse function in R to assign a value of 1 to observations where the minimum and maximum values are equal (i.e., no change occurred). Conversely, we assign a value of 0 to observations where the initial and final values differ.

Filtering non-variable observations

# Filter out observations with 'flag'==0 (non-variable observations)
filter(flag==0)

Now that we have a flag column indicating if an observation exhibits variation, we filter our dataset to exclude those observations with flag equal to 0. These are the observations where no change in HS04 occurred over time.

Un grouping

# Ungroup data (not required but often useful for further analysis)
ungroup()

Finally, we ungroup our dataset to restore its original structure before further analysis.

Full Code

Here’s the full code snippet combining all the steps:

library(dplyr)

data <- read.table(text = "
               Year   source   destination   HS04   value
               1989    ARG        BRA        0101     1
               1989    ARG        BRA        0102     0
               1989    ARG        BRA        0103     0
               1989    ARG        BRA        0104     1
               2010    ARG        BRA        0101     1
               2010    ARG        BRA        0102     1
               2010    ARG        BRA        0103     1
               2010    ARG        BRA        0104     1
",header=T)

data %&gt;% group_by(HS04) %&gt;% 
mutate(flag = ifelse(min(value) &amp; max(value)==1, 1, 0)) %&gt;% 
filter(flag==0) %&gt;% ungroup()

This code snippet provides a concise solution to eliminate observations that do not vary over time. We use the dplyr package in R for data manipulation and grouping operations.

Last modified on 2023-08-22