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Just use a scatterplot. Also, Sydney sprawls.

July 17, 2018
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Just use a scatterplot. Also, Sydney sprawls.

Sydney’s congestion at ‘tipping point’ blares the headline and to illustrate, an interactive chart with bars for city population densities, points for commute times and of course, dual-axes. Yuck. OK, I guess it does show that Sydney is one of three cities that are low density, but have comparable average commute times to higher-density cities. … Continue reading Just...

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Monte Carlo Shiny: Part Three

July 17, 2018
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Monte Carlo Shiny: Part Three

In previous posts, we covered how to run a Monte Carlo simulation and how to visualize the results. Today, we will wrap that work into a Shiny app wherein a user can build a custom portfolio, and then choose a number of simulations to run and a number of months to simulate into the future. A link to that final...

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Video: R for AI, and the Not Hotdog workshop

July 17, 2018
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Video: R for AI, and the Not Hotdog workshop

Earlier this year at the QCon.ai conference, I gave a short presentation, "The Case for R, for AI developers". I also presented an interactive workshop, using R and the Microsoft Cognitive Services APIs, to automatically generate captions for images, and to create a tool to recognize images of hotdogs. Video from both the presentation, and the workshop (which starts...

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How to add Trend Lines to Visualizations in Displayr

July 17, 2018
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How to add Trend Lines to Visualizations in Displayr

In Displayr, Visualizations of chart type Column, Bar, Area, Line and Scatter all support trend lines.  Trend lines can be  linear or non-parametric (cubic spline,...

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Clean Your Data in Seconds with This R Function

July 17, 2018
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All data needs to be clean before you can explore and create models. Common sense, right. Cleaning data can be tedious but I created a function that will help. The function do the following: Clean Data from NA’s and Blanks Separate the clean data – Integer dataframe, Double dataframe, Factor dataframe, Numeric dataframe, and Factor Related PostHands-on Tutorial on...

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Deploying R models in SQL server

July 17, 2018
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Deploying R models in SQL server

As an R user who is building models and analysing data, one of the key challenges is how to make those results available to those who need it. After all, data science is about making better decisions, and your results need to get into the hands of the people who make those decisions. For reporting, there are many options from...

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pinp 0.0.6: Two new options

July 17, 2018
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pinp 0.0.6: Two new options

A small feature release of our pinp package for snazzier one or two column vignettes get onto CRAN a little earlier. It offers two new options. Saghir Bashir addressed a longer-standing help needed! issue and contributed code to select papersize opti...

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Using leaflet, just because

July 17, 2018
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Using leaflet, just because

I love it when researchers take the time to share their knowledge of the computational tools that they use. So first, let me point you at Environmental Computing, a site run by environmental scientists at the University of New South Wales, which has a good selection of R programming tutorials. One of these is Making … Continue reading Using...

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A quick #WorldEmojiDay exploration

July 16, 2018
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Let’s celebrate #WorldEmojiDay with a quick exploration of my own twitter account. The 📦 We’ll need: From Github {emo} remote::install_github("hadley/emo") From CRAN {dplyr} {tidyr} {rtweet} {tidytext} Note: This page has been created at: Sys.time() ## "2018-07-17 17:22:29 CEST" The 🔍 Let’s get my last 3200 tweets: library(emo) library(rtweet) library(dplyr) ## ## Attaching package: 'dplyr' ## The following objects...

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What’s inside? pkginspector provides helpful tools for inspecting package contents

What’s inside? pkginspector provides helpful tools for inspecting package contents

R packages are widely used in science, yet the code behind them often does not come under scrutiny. To address this lack, rOpenSci has been a pioneer in developing a peer review process for R packages. The goal of pkginspector is to help that process by providing a means to better understand the internal structure of R packages. It...

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