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<!DOCTYPE html>
<html lang="en-us">
<head>
<meta name="generator" content="Hugo 0.62.1" />
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<meta name="description" content="A website built through Hugo and blogdown.">
<title>Home</title>
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<h2 class="nav-title">Home</h2>
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<li><a href="/about">About</a></li>
<li><a href="/">Posts</a></li>
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<main>
<div class="catalogue">
<a href="/post/2021-03-07-comparison-of-different-for-loops-methods-in-parallel-distance-computation-with-r-c-and-openmp/" class="catalogue-item">
<div>
<time datetime="2021-03-07 00:00:00 +0000 UTC" class="catalogue-time">March 7, 2021</time>
<h1 class="catalogue-title">Comparison of different for loops methods in parallel distance computation with R, C, and OpenMP</h1>
<div class="catalogue-line"></div>
<p>
Based on the formulas presented in my previous article, I evaluate looping strategies in a parallel distance computation. A classic nested loop approach is compared to a single loop approach based on a linear index used to compute the indices of the rows being evaluated.
</p>
</div>
</a>
<a href="/post/2021-01-17-index_to_lower_triangular_subscripts/" class="catalogue-item">
<div>
<time datetime="2021-01-17 00:00:00 +0000 UTC" class="catalogue-time">January 17, 2021</time>
<h1 class="catalogue-title">Convert a linear index to lower triangular subscripts</h1>
<div class="catalogue-line"></div>
<p>
In this post, I present a way to convert a linear index to lower triangular subscripts, <em>i.e.</em> row and column number in a triangular matrix. The proposed functions work for different numbering directions (rowwise, colwise, and diagwise), including or excluding the diagonal.
</p>
</div>
</a>
<a href="/post/2020-06-17-datatable-introduction/" class="catalogue-item">
<div>
<time datetime="2020-06-17 00:00:00 +0000 UTC" class="catalogue-time">June 17, 2020</time>
<h1 class="catalogue-title">A gentle introduction to data.table</h1>
<div class="catalogue-line"></div>
<p>
This post presents a quick introduction to data.table, an indispensable package for data wrangling in R. The main objective is to present the data.table syntax, showing how to perform basic but essential data manipulation tasks.
</p>
</div>
</a>
<a href="/post/2020-06-14-datatable-pandas/" class="catalogue-item">
<div>
<time datetime="2020-06-14 00:00:00 +0000 UTC" class="catalogue-time">June 14, 2020</time>
<h1 class="catalogue-title">A data.table and pandas small stroll</h1>
<div class="catalogue-line"></div>
<p>
data.table and pandas are two major libraries for efficient manipulation of data frames in R and Python, respectively. Being quite familiar with data.table, I wrote this post as an exercice to learn more about pandas. Commands to execute common data munging tasks are presented side-by-side to facilitate the comparison.
</p>
</div>
</a>
<a href="/post/2019-06-16-learning-japanese/" class="catalogue-item">
<div>
<time datetime="2019-06-16 00:00:00 +0000 UTC" class="catalogue-time">June 16, 2019</time>
<h1 class="catalogue-title">Learning Japanese with data.table and ggplot2</h1>
<div class="catalogue-line"></div>
<p>
This post is about drawing hiragana and katakana tables using R, data.table, and ggplot2. The objective was to better illustrate the rules that underlie these two Japanese writing systems.
</p>
</div>
</a>
<a href="/post/2019-06-08-lightweight-dendrograms/" class="catalogue-item">
<div>
<time datetime="2019-06-08 00:00:00 +0000 UTC" class="catalogue-time">June 8, 2019</time>
<h1 class="catalogue-title">Dendrograms in R, a lightweight approach</h1>
<div class="catalogue-line"></div>
<p>
I wanted a “lightweight” and flexible ggplot2-based solution to draw dendrograms, in particular with the possibility to highlight clusters using different branch colors. I finally ended up writing a small set of functions, using ggdendro and ggplot2 only.
</p>
</div>
</a>
<a href="/post/2019-05-18-images-to-ridges/" class="catalogue-item">
<div>
<time datetime="2019-05-18 00:00:00 +0000 UTC" class="catalogue-time">May 18, 2019</time>
<h1 class="catalogue-title">Turning images into ridgeline plots</h1>
<div class="catalogue-line"></div>
<p>
I was wondering what images turned into ridgeline plots would look like. This post illustrates some experiments performed with ggplot2 and ggridges.
</p>
</div>
</a>
<a href="/post/2019-03-03-datatable-dplyr/" class="catalogue-item">
<div>
<time datetime="2019-03-03 00:00:00 +0000 UTC" class="catalogue-time">March 3, 2019</time>
<h1 class="catalogue-title">A data.table and dplyr tour</h1>
<div class="catalogue-line"></div>
<p>
data.table and dplyr are two R packages that both aim at an easier and more efficient manipulation of data frames. This article shows how they can be used to execute common data munging tasks. The commands are presented side-by-side to facilitate the comparison.
</p>
</div>
</a>
<a href="/post/2019-01-15-2018-learning/" class="catalogue-item">
<div>
<time datetime="2019-01-15 00:00:00 +0000 UTC" class="catalogue-time">January 15, 2019</time>
<h1 class="catalogue-title">Self-studying Python and Machine Learning: 2018 in review</h1>
<div class="catalogue-line"></div>
<p>
Both for personal interest and professional development, I started to learn Python and machine learning concepts. This article summarizes my 2018 learning path.
</p>
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© 2020. Made with <a href='https://gohugo.io'>Hugo</a> using the <a href='https://github.com/EmielH/tale-hugo/'>Tale</a> theme.
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