La librería parallel ha estado activa desde hace varios años y ha sido muy poco utilizada por personas como yo. Esta no es la única manera de realizar cálculos en paralelo en R pero es quizá la más tradicional y la manera en que se la utiliza es similar a otras librerías/paquetes. Simplemente se deben seguir 3 pasos (descritos líneas abajo). Esta vez, he utilizado solamente apply y parApply pero claro, puedes hacer un montón de aplicaciones en paralelo.
As of today, R is one of the most popular languages for Data Science. Being so popular, you can find 18872 packages published on CRAN as of today. Not to mention all packages that are being developed and can already be used. Having mentioned this, you would realise that you can find several packages doing similar things and some being better than others. To make your life easier and thanks to a nice conversation I had with friends/colleagues, here’s a list of the fundamental packages you would need for your day by day Data Science.
Shiny es una be—lle—za para hacer dashboards y apps con R. Con el tiempo necesario, puedes tener estilos, ya sea con archivos .css o con bslib, y tener apps que se ven muy “chéveres”. Pero mientras tanto, si quieres ver una app sencilla para aprender, aquí tienes una buena oportunidad! El funcionamiento de una app es bastante simple en realidad, tienes una “User Interface” (ui) y un “Server”. La ui puede ser creada de diferentes maneras, diferentes tamaños, puedes tener inputs que afectan a la app de diferentes maneras… todo esto con la ayuda de las funciones que tengas en el server.
Thanks to friends at the “Escuela Politécnica Nacional” in Ecuador, I got the chance to be in front of students after a loooong time off the classroom and talk about Data Science with R. Well in front meaning in front of my laptop during a zoom call, but still… It’s never boring talking about stuff I like, but I gotta admit, sometimes I doubt if my talking/explanations are fulfilling the students’ expectations.
After years of being a PC guy, I got a macbook. That means I had to install some stuff and trying to be a multitasker, I recorded and uploaded it to youtube. Starting with R and RStudio, also Python (it really took 1 minute), and git came already installed. So (spanish speaking alert!!!) here you can check the videos of the installing process and a longer video in which I set git and python in RStudio and test them.
En mi colegio (o secundaria), teníamos un cura como rector que decía: “el que controla su lengua, es varón perfecto”. Cambiemos a: “el que controla sus versiones, es buen coder mi brother”. También podríamos decir: “deja de hablar huevadas”… pero bueno, al tema. El control de versiones acolita, acolita un montón, sin importar el tipo de archivo con el que trabajes. Puedes olvidarte de: tesis_v1, tesis_v2,….tesis_final, tesis_final_final, tesis_la_vencida, …tesis_final_final_final_imprimir…
Hola a todos, hola mami, me hice youtuber. Tuve que descargar R y actualizar R Studio, y además, por preguntas de un amigo, me decidí por hacer un video sobre cómo puedes instalar R y R Studio (para windows, aunque da casi igual el OS que tengan, los pasos se parecen). Si eres nuevo en Data Science, estarás empezando a instalar programas y a mirar qué puedes hacer con ellos.
As a Data Scientist, have you ever been asked what data science is? Have you struggled to answer? I’ve found myself in this situation before, and just started talking and talking yet failing to give a clear answer. The short answer is: “everything that has to do with data”. To start, data has to be sourced somehow and from somewhere, this is usually done by data engineers or software engineers (data scientists’ best friends in the whole wide universe).
If you’re an R user, this might be (extremely) helpful. Styling your code might be a pain in the a$$. Even worse, receiving messy code from someone else… What if I told you that you can style your code with one single line of code? Well, a few weeks ago I was in front of a very messy code and started tidying it line by line… after a few minutes I had enough.