spec_select

This function selects user-specified columns from a spectral dataset, always ensuring that the wavenumber column (`wn_col`) is included, unless explicitly excluded.

Enables the analysis of spectroscopy data such as infrared ('IR'), Raman, and nuclear magnetic resonance ('NMR') using the tidy data framework from the 'tidyverse'. The 'tidyspec' package provides functions for data transformation, normalization, baseline correction, smoothing, derivatives, and both interactive and static visualization. It promotes structured, reproducible workflows for spectral data exploration and preprocessing. Implemented methods include Savitzky and Golay (1964) "Smoothing and Differentiation of Data by Simplified Least Squares Procedures" <doi:10.1021/ac60214a047>, Sternberg (1983) "Biomedical Image Processing" <https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1654163>, Zimmermann and Kohler (1996) "Baseline correction using the rolling ball algorithm" <doi:10.1016/0168-583X(95)00908-6>, Beattie and Esmonde-White (2021) "Exploration of Principal Component Analysis: Deriving Principal Component Analysis Visually Using Spectra" <doi:10.1177/0003702820987847>, Wickham et al. (2019) "Welcome to the tidyverse" <doi:10.21105/joss.01686>, and Kuhn, Wickham and Hvitfeldt (2024) "recipes: Preprocessing and Feature Engineering Steps for Modeling" <https://CRAN.R-project.org/package=recipes>.

Marcel Ferreira

tidyspec

Spectroscopy Analysis Using the Tidy Data Philosophy

Willian Zambuzzi

Julia Moraes

Emerson Araujo Alves dos Santos

spec_select function

<dl><dt>.data</dt>
<dd>A data frame containing spectral data.</dd>
<dt>...</dt>
<dd>Column selection helpers (e.g., column names, -column_to_exclude).</dd></dl>

Arguments

Select Specific Columns in a Spectral Data Frame — spec_select

<dl>

<dt>.data</dt>
<dd>A data frame containing spectral data.</dd>


<dt>...</dt>
<dd>Column selection helpers (e.g., column names, -column_to_exclude).</dd>

</dl>

spec_select: Select Specific Columns in a Spectral Data Frame

Description

Usage

Value

Arguments

See Also