@drsimonj here with five simple tricks I find myself sharing all the time with fellow R users to improve their code! This post was originally published on DataCamp’s community as one of their top 10 articles in 2017 1. More fun to sequence from 1 Next time you use the colon operator to create a sequence from 1 like 1:n, try seq(). #...
- As we come close to the end of 2017, its time to look back. This has been a great year for me in many ways. This blog started as a way to write short pieces about using R...
2017 is nearly at an end. We humans seem to need these cycles to help us on our path forward and have, throughout history, used these annual demarcation points as a time of reflection of what was, what is an what shall come next. To that end, I decided it was about time to help... Continue reading →
Blogging and social media for introverts - How to spot an introvert You may have seen David Robinson’s recent post encouraging R users to start blogging. Some folk will willingly act on this advice, and others won’t. For those that won...
Blogging and social media for introverts - How to spot an introvert You may have seen David Robinson’s recent post encouraging R users to start blogging. Some folk will willingly act on this advice, and others won’t. For those that won...
Blogging and social media for introverts - How to spot an introvert You may have seen David Robinson’s recent post encouraging R users to start blogging. Some folk will willingly act on this advice, and others won’t. For those that won...
You’ve probably seen people posting their #Best9of2017, primarily on Instagram I’d say. I’m not an Instagram user, although I do have an account to spy on my younger sister and cousins, so I don’t even have 9 Instagram posts in total but I do l...
Your first step to becoming a top-performing data scientist is .... The post The first step to becoming a top performing data scientist appeared first on SHARP SIGHT LABS.
Not everyone has the luxury of taking some downtime at the end the year, but if you do have some free time, you may enjoy something on my short list of downtime reading. The books and articles here are not exactly “light reading”, nor are they literature for cuddling by the fire. Nevertheless, you may find something that catches...
Using tabulizer we’re able to extract information from PDFs so it comes in really handy when people publish data as a PDF! This post takes you through using tabulizer and tidyverse packages to scrape and clean up some budget data from PASS, an association for the Microsoft Data Platform community. The goal is to mainly show some of the...
Sometimes you just want to add bananas from the commandline. Previously I created a small script that takes an image and adds a dancing banana to the bottom left of the image. I wanted to make an API too, but that will have to wait till next year....
![cyclic riddle [not in NYC!]](https://xianblog.files.wordpress.com/2017/12/riddler1222.jpg?w=328&h=328)
In the riddle of this week on fivethirtyeight, the question is to find the average number of rounds when playing the following game: P=6 players sitting in a circle each have B=3 coins and with probability 3⁻¹ they give one coin to their right or left side neighbour, or dump the coin to the centre.
We are excited to announce the rquery R package. rquery is Win-Vector LLC‘s currently in development big data query tool for R. rquery supplies set of operators inspired by Edgar F. Codd‘s relational algebra (updated to reflect lessons learned from working with R, SQL, and dplyr at big data scale in production). As an example: … Continue reading Announcing...
dplyr is one of the most popular r-packages and also part of tidyverse that’s been developed by Hadley Wickham. The mere fact that dplyr package is very famous means, it’s one of the most frequently used. Being a data scientist is not always about creating sophisticated models but Data Analysis (Manipulation) and Data Visualization play Related Post How to apply...
It has undoubtedly been a busy year in the R -and, much broader, the data science- community. As the year is drawing to a close, I'd would like to take the time to look back at the moments that were most important, fun, relevant, ... to the R community. In today's blog post, I will do this by chronologically listing...
It has undoubtedly been a busy year in the R -and, much broader, the data science- community. As the year is drawing to a close, I'd would like to take the time to look back at the moments that were most important, fun, relevant, ... to the R community. In today's blog post, I will do this by chronologically listing...
RcppProgress is a tool to help you monitor the execution time of your C++ code, by providing a way to interrupt the execution inside the C++ code, and also to display a progress bar indicative of the state of your computation. Additionally, it is com...
Introducing adavis My second ever post on this blog was on introducing adamap, a Shiny app that maps Americans for Democratic Action voting scores (the so-called Liberal Quotient) between 1947-2015. It was built with highcharter, and hence it was nicely interactive but quite slow. I wanted to switch to another package since, and when I eventually ran into statebins, I...
Data science for business (DS4B) is the future of business analytics yet it is really difficult to figure out where to start. The last thing you want to do is waste time with the wrong tool. Making effective use of your time involves two pieces: (1) selecting the right tool for the job, and (2) efficiently learning how to...
This Stackoverflow question made me think about how to build formulae. For example, you might want to programmatically build linear model formulae and then map these models on data. For example, suppose the following (output suppressed): data(mtcars) lm(mpg ~ hp, data = mtcars) lm(mpg ~I(hp^2), data = mtcars) lm(mpg ~I(hp^3), data = mtcars) lm(mpg ~I(hp^4), data = mtcars) lm(mpg ~I(hp^5), data = mtcars) lm(mpg ~I(hp^6), data...
Just too often on X validated, one sees questions displaying a complete ignorance of the basics that makes one purposelessly wonder what is the point of trying to implement advanced methods when missing the necessary background. And just as often, I reacted to the question by wondering out loud about this… In the current case,
In this third and last post about the Sub-Gaussian property for the Beta distribution (post 1 and post 2), I would like to show the interplay with the Bernoulli distribution as well as some connexions with optimal transport (OT is a hot topic in general, and also on this blog with Pierre’s posts on Wasserstein
Everybody is freaking out about the rise of the Bitcoin and the potential of the Blockchain technologies. The advent of cryptocurrencies, game changing use cases, disruption of established business models by disintermediation, etc.. By...
Hello everyone, Why we always want to take the red pill when we can take the blue one? That’s the question! In this post I will explain how to launch a shiny application from a shortcut. Just like that: It’s fast and useful if you work with colleagues that don’t have a clue about R and just want to...
Overview of simple outlier detection methods with their combination using dplyr and ruler packages. Prologue During the process of data analysis one of the most crucial steps is to identify and account for outliers, observations that have essentially different nature than most other observations. Their presence can lead to untrustworthy conclusions....
The Revolutions team is celebrating Christmas today, and we're taking a break with family and enjoying good food. And given the number of Eggnogs that are being prepared — thanks to Hadley Wickham's eggnogr Shiny app — it might be a good idea to take the rest of the week off as well. (You can find the R source...
This example is drawn from “A Painless Q-Learning Tutorial” at http://mnemstudio.org/path-finding-q-learning-tutorial.htm which explains how to manually calculate iterations using the updating equation for Q-Learning, based on the Bellman Equation (image from https://www.is.uni-freiburg.de/ressourcen/business-analytics/13_reinforcementlearning.pdf): The
Overview: Reinforcement learning uses “reward” signals to determine how to navigate through a system in the most valuable way. (I’m particularly interested in the variant of reinforcement learning called “Q-Learning” because the
I am excited to share a new deep learning model performance trajectory graph. Here is an example produced based on Keras in R using ggplot2: The ideas include: We plot model performance as a function of training epoch, data set (training and validation), and metric. For legibility we facet on metric, and facets are adjusted … Continue reading Plotting...
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