3148 search results for "ggplot"

Spending Seized Assets – A State-by-State Per-capita Comparison in R

October 13, 2014
By
Spending Seized Assets – A State-by-State Per-capita Comparison in R

The Washingon Post did another great story+vis, this time on states Spending seized assets. According to their sub-head: Since 2008, about 5,400 police agencies have spent $2.5 billion in proceeds from cash and property seized under federal civil forfeiture laws. Police suspected the assets were linked to crime, although in 81 percent of cases no

Read more »

Analyze Instagram with R

October 13, 2014
By
Analyze Instagram with R

This tutorial will show you how you create an Instagram app, create an authentication process with R and get data via the Instagram API. There is no R package for this yet so we... The post Analyze Instagram with R appeared first on ThinkToStart.

Read more »

SIR Model of Epidemics

October 12, 2014
By
SIR Model of Epidemics

The SIR model divides the population to three compartments: Susceptible, Infected and Recovered. If the disease dynamic fits the SIR model, then the flow of individuals is one direction from the susceptible group to infected group and then to the recovered group. All individuals are assumed to be identical in terms of their susceptibility to infection, infectiousness if infected...

Read more »

When to Use Stacked Barcharts?

October 11, 2014
By
When to Use Stacked Barcharts?

Yesterday a few of us on Facebook’s Data Science Team released a blogpost showing how candidates are campaigning on Facebook in the 2014 U.S. midterm elections. It was picked up in the Washington Post, in which Reid Wilson calls us “data … Continue reading →

Read more »

DataFrame manipulation in R from basics to dplyr

October 11, 2014
By
DataFrame manipulation in R from basics to dplyr

  In my surroundings at work I see quite a few people managing their data in spreadsheet software like Excel or Calc, these software will do the work but I usually tend to do as little data manipulation in them as possible and to turn as soon as possible my spreadsheets into csv files and

Read more »

A Note on Tweedie

October 9, 2014
By
A Note on Tweedie

by Joseph Rickert In a recent post I talked about the information that can be developed by fitting a Tweedie GLM to a 143 million record version of the airlines data set. Since I started working with them about a year or so ago, I now see Tweedie models everywhere. Basically, any time I come across a histogram that...

Read more »

In case you missed it: September 2014 Roundup

October 8, 2014
By

In case you missed them, here are some articles from September of particular interest to R users. Norm Matloff argues that T-tests shouldn't be part of the Statistics curriculum and questions the "star system" for p-values in R. A nice video introduction to the dplyr package and the %>% operator, presented by Kevin Markham. An animation of police militarization...

Read more »

Plot Me Like a Hurricane (a.k.a. animating historical North Atlantic basin tropical storm tracks)

October 7, 2014
By

Markus Gessman (@MarkusGesmann) did a beautiful job Visualising the seasonality of Atlantic windstorms using small multiples, which was inspired by both a post by Arthur Charpentier (@freakonometrics) on using Markov spatial processes to “generate” hurricanes—which was tweaked a bit by Robert Grant (@robertstats)—and Gaston Sanchez‘s Visualizing Hurricane Trajectories RPub. I have some history with hurricane

Read more »

Visualising the seasonality of Atlantic windstorms

October 7, 2014
By
Visualising the seasonality of  Atlantic windstorms

Last week Arthur Charpentier sketched out a Markov spatial process to generate hurricane trajectories. Here, I would like to take another look at the data Arthur used, but focus on its time component. According to the Insurance Information Institute, a normal season, based on averages from 1980 to 2010, has 12 named storms, six hurricanes and...

Read more »

The World We Live In #1: Obesity And Cells

October 6, 2014
By
The World We Live In #1: Obesity And Cells

Lesson learned, and the wheels keep turning (The Killers – The world we live in) I discovered this site with a huge amount of data waiting to be analyzed. The first thing I’ve done is this simple graph, where you can see relationship between cellular subscribers and obese people. Bubbles are countries and its size

Read more »

Sponsors

Mango solutions



RStudio homepage



Zero Inflated Models and Generalized Linear Mixed Models with R

Dommino data lab

Quantide: statistical consulting and training



http://www.eoda.de







ODSC

ODSC

CRC R books series





Six Sigma Online Training





Contact us if you wish to help support R-bloggers, and place your banner here.

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)