convert_columns: Check and Convert Columns in Dataset

In CBASSED50: Process CBASS-Derived PAM Data

Check and Convert Columns in Dataset

Description

This function checks the data types of specific columns in the provided dataset and converts them to the desired data type if necessary. The function is designed to ensure that certain columns are represented as factors or numeric values, as required for further analysis.

Usage

convert_columns(dataset)

Arguments

dataset

A data frame containing the dataset to be checked and modified.

Value

A modified version of the input dataset with the specified columns converted to factors or numeric types, as appropriate.

Examples

# Sample dataset
data <- data.frame(
                Project = c("Project A", "Project A", "Project B"),
                Date = c("2023-07-31", "2023-08-01", "2023-08-02"),
                Site = c("Site X", "Site Y", "Site Z"),
                Country = c("Country A", "Country B", "Country C"),
                Latitude = c(34.05, 36.16, 40.71),
                Longitude = c(-118.24, -115.15, -74.01),
                Species = c("Species 1", "Species 2", "Species 3"),
                Genotype = c("Genotype A", "Genotype B", "Genotype C"),
                Condition = c("Condition 1", "Condition 2", "Condition 3"),
                Timepoint = c("Timepoint 1", "Timepoint 1", "Timepoint 2"),
                Temperature = c(30.2, 31.5, 29.8),
                Pam_value = c(0.5, 0.6, 0.8)
                )

# Convert columns in the dataset
modified_data <- convert_columns(data)

# The 'Site', 'Condition', 'Species', and 'Genotype' columns are now factors,
# and 'Temperature' and 'PAM' columns are now numeric in the modified_data.

CBASSED50 documentation built on June 8, 2025, 10:27 a.m.