utils_prepare_df

Convert Data Frame to a List of Data Frames

Fast C++ implementation of Dynamic Time Warping for time series dissimilarity analysis, with applications in environmental monitoring and sensor data analysis, climate science, signal processing and pattern recognition, and financial data analysis. Built upon the ideas presented in Benito and Birks (2020) <doi:10.1111/ecog.04895>, provides tools for analyzing time series of varying lengths and structures, including irregular multivariate time series. Key features include individual variable contribution analysis, restricted permutation tests for statistical significance, and imputation of missing data via GAMs. Additionally, the package provides an ample set of tools to prepare and manage time series data.

Blas M. Benito

distantia

Advanced Toolset for Efficient Time Series Dissimilarity
Analysis

utils_prepare_df function

<dl><dt>x</dt>
<dd>(required, data frame) Input data frame. Default: NULL.</dd>
<dt>name_column</dt>
<dd>(optional, column name) Column name used to split <code>x</code> to a list of data frames. If omitted, the split is done by column instead. Default: NULL</dd>
<dt>time_column</dt>
<dd>(optional, column name) Name of the column representing time, if any. Default: NULL.</dd></dl>

Arguments

Convert Data Frame to a List of Data Frames — utils_prepare_df

<dl>

<dt>x</dt>
<dd>(required, data frame) Input data frame. Default: NULL.</dd>


<dt>name_column</dt>
<dd>(optional, column name) Column name used to split <code>x</code> to a list of data frames. If omitted, the split is done by column instead. Default: NULL</dd>


<dt>time_column</dt>
<dd>(optional, column name) Name of the column representing time, if any. Default: NULL.</dd>

</dl>

utils_prepare_df: Convert Data Frame to a List of Data Frames

Description

Usage

Value

Arguments

See Also