rstudio::conf 2020 Videos

February 17, 2020
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rstudio::conf 2020 Videos

rstudio::conf 2020 is already receding in the rear view mirror, but the wealth of resources generated by the conference will be valuable for quite some time. All of the materials from the workshops, and now all one hundred and four videos of conference talks are available. This unique video collection offers valuable insight into how developers, data scientists, statisticians,...

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Getting started in R markdown

February 17, 2020
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Getting started in R markdown

R Markdown: what, why and how? Before you start Components of a .Rmd file YAML header Code chunks Text Code inside text Images Tables Additional notes and useful resources Photo by Jon Tyson If you have spent some time writing code in R, you probably have heard of generating dynamic reports incorporating R code, R outputs (results) and text or comments. In this article, I will explain how R Markdown...

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RStudio 1.3 Preview: Configuration and Settings

February 17, 2020
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RStudio 1.3 Preview: Configuration and Settings

This blog post is part of a series on new features in RStudio 1.3, currently available as a preview release. Today, we’re going to talk about a number of improvements we’ve made to RStudio 1.3 around configuration and settings. To set the stage, here’s how you configure RStudio today: This point-and-click dialog makes it easy for users to select the settings...

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Efficient Data Management in R

February 17, 2020
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Efficient Data Management in R

The software environment R is widely used for data analysis and data visualization in the social sciences and beyond. Additionally, it is becoming increasingly popular as a tool for data and file management. Focusing on these latter aspects, this Methods Bites Tutorial by Marcel Neunhoeffer, Oliver Rittmann and our team members Denis Cohen and Cosima Meyer illustrates the workflow...

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Clustered randomized trials and the design effect

February 17, 2020
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Clustered randomized trials and the design effect

I am always saying that simulation can help illuminate interesting statistical concepts or ideas. The design effect that underlies much of clustered analysis is could benefit from a little exploration through simulation. I’ve written about clustered-related methods so much on this blog that I won’t provide links - just peruse the list of entries on the home page and...

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Quantile Regression (home made, part 2)

February 17, 2020
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Quantile Regression (home made, part 2)

A few months ago, I posted a note with some home made codes for quantile regression… there was something odd on the output, but it was because there was a (small) mathematical problem in my equation. So since I should teach those tomorrow, let me fix them. Median Consider a sample . To compute the median, solvewhich can be...

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Part 6: How not to validate your model with optimism corrected bootstrapping

February 17, 2020
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Part 6: How not to validate your model with optimism corrected bootstrapping

When evaluating a machine learning model if the same data is used to train and test the model this results in overfitting. So the model performs much better in predictive ability  than it would if it was applied on completely new data, this is because the model uses random noise within the data to learn

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Creating MS Word reports using the officer package

February 17, 2020
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Creating MS Word reports using the officer package

Commonly, the final product that a data scientist or a statistician generates is a report, usually in MS Word format. The officer package enables generating such a report from within R. It also enables generating PowerPoint presentations, but this is… Continue reading →

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What `R` you? (R dataframe vs python dataframe)

February 16, 2020
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Recap Previously in this series, we discovered the equivalent python data structures for the following R data structures: vectors lists arrays/matrixes In this post, we will look at translating R data frames into python. We will also compare and contrast data frames in R and python. R data frame is a python… Pretty straight forward, a R data frame is a python data frame. We will use...

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How to compute the z-score with R

February 16, 2020
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Are you interested in guest posting? Publish at DataScience+ via your RStudio editor. Category Basic Statistics Tags Data Management R Programming Tips & Tricks Sometimes it is necessary to standardize the data due to its distribution or simply because we need to have a fair comparison of a value (e.g, body weight) with a reference population (e.g., school, city, state, country). The calculation of z-score...

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Building a base dplyr with primitives

February 15, 2020
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Introduction In one of my latest posts, I discussed the idea of turning base R’s get and set operators ([, [[, [

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Apple Health Export Part I

February 15, 2020
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Apple Health Export Part I

This post is Part I of a dive into the contents of the Apple Health Export. It will work through the mechanics of moving data from the Apple Health app out of your iPhone and into R where you can analyze it. It also will describe in detail the problem of adjusting the time stamps for daylight savings time and travel across...

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new release of offensive programming packages

February 14, 2020
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new release of offensive programming packages

Offensive programming ecosystem has been upgraded. You may now use new versions of packages according to following table package name (available on CRAN) recommanded version wyz.code.offensiveProgramming ...

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The Premier Machine Learning Conference (15% discount code)

February 14, 2020
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The Premier Machine Learning Conference (15% discount code)

Attend any or all of the five jointly scheduled events! Get an additional 15% discount on your booking with the code RBLOGGERSMLW . Join us in Las Vegas for the largest Predictive Analytics World event to date! Learn more 5 days, 8 tracks, 160 speaker and over 150 exciting sessions Join the Machine Learning Week 2020, May … Continue reading The...

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Dude: Where are my Cats?  RStudio::Conf 2020

February 14, 2020
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Dude: Where are my Cats?  RStudio::Conf 2020 It may not have been the start to the conference that we planned... The post Dude: Where are my Cats?  RStudio::Conf 2020 appeared first on Mango Solutions.

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RcppSimdJson 0.0.1 now on CRAN!

February 13, 2020
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A fun weekend-morning project, namely wrapping the outstanding simdjson library by Daniel Lemire (with contributions by Geoff Langdale, John Keiser and many others) into something callable from R via a new package RcppSimdJson lead to a first tweet o...

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Self-starting routines for nonlinear regression models

Self-starting routines for nonlinear regression models

In R, the drc package represents one of the main solutions for nonlinear regression and dose-response analyses (Ritz et al., 2015). It comes with a lot of nonlinear models, which are useful to describe several biological processes, from plant growth to bioassays, from herbicide degradation to seed germination. These models are provided with self-starting functions, which free the user...

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Dynamic discrete choice models, reinforcement learning and Harold, part 2

February 13, 2020
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Dynamic discrete choice models, reinforcement learning and Harold, part 2

In this blog post, I present a paper that has really interested me for a long time. This is part2, where I will briefly present the model of the paper, and try to play around with the data. If you haven’t, I suggest you read part 1 where I provide more context. Rust’s model Welcome to part 2 of this series, which might or...

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Benchmarking the portfolio

February 13, 2020
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Benchmarking the portfolio

In our last post, we looked at one measure of risk-adjusted returns, the Sharpe ratio, to help our hero decide whether he wanted to alter his portfolio allocations. Then, as opposed to finding the maximum return for our hero’s initial level of risk, we broadened the risk parameters and searched for portfolios that would at least offer the same...

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Git/Github for contributing to package development

February 13, 2020
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Git/Github for contributing to package development

Disclaimer: I have no affiliation with Microsoft’s GitHub, GitLab, CodeCademy or D2L team.

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Animated Plots using ggplot and gganimate

February 13, 2020
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Animated Plots using ggplot and gganimate

A short overview of the functionalities of the R package gganimate: Learn how to turn your static ggplots in beautiful animations showcasing your data. Der Beitrag Animated Plots using ggplot and gganimate erschien zuerst auf STATWORX.

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rstudio::conf retrospective

rstudio::conf retrospective

Two weeks ago, I was fortunate to attend my very first Rstudio conference. Spoiler: it was an amazing event - packed to the brim with new ideas, tools, impressions, and most important of all: smart and kind people. This was the first time that San F...

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Visualizing the Tallest Building in Each State

February 13, 2020
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Visualizing the Tallest Building in Each State

Via Digg:This data visualization, put together by takeasecond on Reddit, shows the tallest building in all 50 states in 2020. As the graph demonstrates, the current tallest building in America is New York's One World Trade Center at 1,776 feet tall. In...

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8 reasons why you should submit an abstract for EARL

February 13, 2020
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Abstract submissions for the Enterprise Applications of the R  Language Conference are now open! We are back at the Tower... The post 8 reasons why you should submit an abstract for EARL appeared first on Mango Solutions.

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shinyMatrix – Matrix Input for Shiny Apps

February 13, 2020
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shinyMatrix – Matrix Input for Shiny Apps

In this post we’d like to introduce you to our new R package shinyMatrix. It provides you with an editable matrix input field for shiny apps. ...

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The complete guide to clustering analysis: k-means and hierarchical clustering by hand and in R

February 12, 2020
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The complete guide to clustering analysis: k-means and hierarchical clustering by hand and in R

What is clustering analysis? Application 1: Computing distances Solution k-means clustering Application 2: k-means clustering Data kmeans() with 2 groups Quality of a k-means partition nstart for several initial centers kmeans() with 3 groups Manual application and verification in R Solution by hand Solution in R Hierarchical clustering Application 3: hierarchical clustering Data Solution by hand Single linkage Complete linkage Average linkage Solution in R Single linkage Complete linkage Average linkage k-means versus hierarchical clustering References Photo by Nikola Johnny Mirkovic What is clustering analysis? Clustering analysis...

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Photo Mosaics in R

February 12, 2020
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Photo Mosaics in R

Harrison Schramm, CAP, PStat, is a Senior Fellow at the Center for Strategic and Budgetary Assessments. In this short piece, I’m going to discuss a fun photography project I did over the winter using R. I’m also going to touch on some of the implications of the R license, which underlies our entire ecosystem, but we don’t usually think about...

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taxadb: A High-Performance Local Taxonomic Database Interface

Dealing with taxonomic inconsistencies within and across datasets is a fundamental challenge of ecology and evolutionary biology. Accounting for species synonyms, taxa splitting and unification is especially important as aggregation of data across time and different data sources becomes increasingly common. One potentially powerful approach for addressing these issues is to resolve scientific names to taxonomic identifiers that follow...

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digest 0.6.24: Some more refinements

February 12, 2020
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Another new version of digest arrived on CRAN (and also on Debian) earlier today. digest creates hash digests of arbitrary R objects (using the md5, sha-1, sha-256, sha-512, crc32, xxhash32, xxhash64, murmur32, and spookyhash algorithms) permitting e...

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