10 Tips and Tricks for Data Scientists Vol.4
We have started a series of articles on tips and tricks for data scientists (mainly in Python and R). In ... Read more10 Tips and Tricks for Data Scientists Vol.4
April 2021
Ten Years vs The Spread II: Calculating publication lag times in R
This post is an update of a previous analysis on quantixed. We have covered publication lag times – the time it takes for a paper go from submitted (received) to accepted and published – a lot on here. It is possible to look at lag times, in R using data from PubMed. ...
How to clean the datasets in R?
How to clean the datasets in R?, Data cleansing is one of the important steps in data analysis. Multiple packages are available in r...
The post How to clean the datasets in R? appeared first on finnstats. [Read more...]
Long time, no see: Virtual Lunch Roulette
Abstract:
When distributing individuals into groups every week for a virtual social mixer, e.g. using Zoom breakout rooms, it’s boring to end up in a group with someone, who you already met last week. We compute the probility for this to happen and state a simple rejection sampling ... [Read more...]
rOpenSci’s R-universe Project
How to join this free online event with Jeroen Ooms and Karthik Ram.
The R-universe platform is a new umbrella project under which rOpenSci experiments with new ideas for improving publication and discovery of research software in R. The system provides an array of services to users and developers of ...
R compiler Application-Installation Guide
Introduction R compiler, write R codes on your device. You can easily execute basic statistical analysis in mobile itself. This is ideal for learning...
The post R compiler Application-Installation Guide appeared first on finnstats.
Splitting Linear Models
Last Thursday I watched Wolfgang Viechtbauer’s stream
on Twitch. Wolfgang spoke about linear regression.
(If you’re interested in the results: Wolfgang lists the R-code he wrote during
the stream at https://www.wvbauer.com/doku.php/live_str...
ATOMIC: an AutoML (and easy-to-use) solution for imbalanced learning
TLDR. If you already have some experience in imbalanced learning problems, you’re probably aware of the time-consuming part of testing lengthy lists of resampling strategies (one of the available methods to tackle imbalanced learning tasks) and resp...
The Easter Bunny is Cashing In
Has the price of Easter Eggs shot up since last year? Let’s use data from Trundler to investigate. I’ll do the analysis in R using the {trundler} package.
Data Preparation
I’ve already got a collection of product IDs stashed in PRODUCT_ID. We nee...
10 Tips and Tricks for Data Scientists Vol.3
I have started a series of articles on tips and tricks for data scientists (mainly in Python and R). In ... Read more10 Tips and Tricks for Data Scientists Vol.3
Methow Valley Air Quality
Mazama Science has released a new set of tutorials demonstrating the use of air quality R packages to investigate data from regulatory monitors and low-cost sensors. This post is just a short summary of what the tutorials cover. We invite anyone interested in wildfire smoke and air quality to run ...
The top 10 R errors, the 7th one will surprise you
You can read the original post in its original format on Rtask website by ThinkR here: The top 10 R errors, the 7th one will surprise you
In the same way you fall learning to walk, you make mistakes learning R. The goal of this article was to regroup the most ...
tidyverse in r – Complete Tutorial
tidyverse in R, one of the Important packages in R, there are a lot of new techniques available maybe users are not aware of....
The post tidyverse in r – Complete Tutorial appeared first on finnstats.
Visual Representation of Text Data Sets using the R tm and wordcloud packages: part one, Beginner’s Guide
Visual Representation of Text Data Sets Using the R tm and wordcloud Packages: Part One Douglas M. Wiig This paper is the next installment in series that examines the use of R scripts to present and analyze complex data sets using various types of visual representations. Previous papers have discussed ...
Interactive Individual Conditional Expectation (ICE) plots
This post is not about a new technique or package, but rather combining existing functionality in interpretable machine learning and data visualization in a way to facilitate analyses of model results. We’ll make use of two packages DALEX and PLOTLY ot... [Read more...]
Not so soft softmax
Our last post examined the correspondence between a logistic regression and a simple neural network using a sigmoid activation function. The downside with such models is that they only produce binary outcomes. While we argued (not very forcefully) that if investing is about assessing the probability of achieving an attractive ...
Microeconomic Theory and Linear Regression (Part 1)
Introduction
This is a summary of a very old collection of materials that I used as teaching assistant (before 2017).
Among those materials I found some class notes from Arne Henningsen, the author of micEcon R package.
I’ll use that package and some others to show some concepts from Microeconomic ...
GetDFPData2 available in CRAN!
After testing the package extensivelly, GetDFPData2 is finally available in CRAN. GetDFPData2 is the second and backwards incompatible version of GetDPFData, a R package for downloading annual financial reports from B3, the Brazilian financial exchange. Unlike its first iteration, GetDFPData2 imports data using a database of csv files from CVM, ... [Read more...]
New plot functionality for ClustImpute 0.2.0 and other improvements
Let’s create some dummy data…
### Random Dataset set.seed(739) n [Read more...]
Making the Most of Mobility
I became aware of the Community Mobility Reports data courtesy of this tweet from Mike Schussler:
Next time someone tells you that people are misbehaving you can tell the the data says no they are listening doing as they are told. Data from our mo...
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