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The SensoryDataSets package provides a curated and
diverse collection of datasets focused on sensory evaluation,
consumer science, food quality assessment, product characterization, and
preference analysis. It includes data covering topics such as
hedonic and liking scores, descriptive sensory profiles, product
preferences, sensory attributes, physicochemical measurements, wine
quality and bitterness assessments, consumer evaluations, and sensory
panel studies.
The package contains a variety of data structures and sensory applications, including consumer acceptance and hedonic studies, descriptive sensory evaluations, product profiling, ordinal sensory responses, physicochemical and sensory measurements, panel evaluations, and multivariate sensory data. The datasets encompass evaluations of products such as brown and white bread, olive oil, orange juice, grape blends, wine, chocolate, perfume, and smoothies, providing useful examples for teaching, exploratory data analysis, statistical modeling, multivariate analysis, consumer studies, preference analysis, and methodological research in sensory and consumer science.
You can install the SensoryDataSets package from CRAN
with the following R function:
install.packages("SensoryDataSets")You can install the SensoryDataSets package from its
GitHub repository with the following R function:
devtools::install_github("lightbluetitan/SensoryDataSets")library(SensoryDataSets)# Load the package
library(SensoryDataSets)
# List all datasets in the package
view_datasets_SensoryDataSets()
# Load dataset
data(olive_oil_df)
# Preview the dataset
head(olive_oil_df)
# Open in Viewer
View(olive_oil_df)All datasets in this package are provided under their respective
original licenses, as documented in LICENSES_DETAILS.md.
Users must comply with the licensing terms specified by each original
source.
This package, SensoryDataSets, is licensed under the
GPL (>= 2) | GPL-3 license.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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