2782 search results for "ggplot"

Twitter sentiment analysis with R

Twitter sentiment analysis with R

Recently I designed a relatively simple code in R to analyze the content of Twitter posts by using the categories identified as positive, negative and neutral. The idea of processing tweets is based on a presentation http://www.slideshare.net/ajayohri/twitter-analysis-by-kaify-rais. The algorithm evaluates tweets based on the number of positive and negative words in the tweet. The words in the tweet correspond with the words... Read More »

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Project Tycho, Correlation between states

April 27, 2014
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Project Tycho, Correlation between states

In this fourth post on Measles data I want to have a look at correlation between states. As described before, the data is from Project Tycho, which contains data from all weekly notifiable disease reports for the United States dating back to 1888...

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What If You Dig A Hole Through The Earth?

April 26, 2014
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What If You Dig A Hole Through The Earth?

It suddenly struck me that that tiny pea, pretty and blue, was the Earth. I put up my thumb and shut one eye, and my thumb blotted out the planet Earth. I didn’t feel like a giant. I felt very, very small (Neil Armstrong) Where would you come out if you dig a hole straight

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Bandit Formulations for A/B Tests: Some Intuition

April 24, 2014
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Bandit Formulations for A/B Tests: Some Intuition

Controlled experiments embody the best scientific design for establishing a causal relationship between changes and their influence on user-observable behavior. – Kohavi, Henne, Sommerfeld, “Practical Guide to Controlled Experiments on the Web” (2007) A/B tests are one of the simplest ways of running controlled experiments to evaluate the efficacy of a proposed improvement (a new Related posts:

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R Helps With Employee Churn

April 24, 2014
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R Helps With Employee Churn

by Joseph Rickert Pasha Roberts, Chief Scientist at Talent Analytics, is writing a series of articles on Employee Churn for the Predictive Analytics Times that comprise a really instructive and valuable example of using R to do some basic predictive modeling. So far, Pasha has published Employee Churn 201 in which he makes a case for the importance of...

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Preventing escaping in HTML

April 24, 2014
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Preventing escaping in HTML Preventing escaping in HTML library(xtable) ## ## Attaching package: 'xtable'## ## The following objects are masked from 'package:Hmisc':## ## label, label<- library(stringr)library(whisker) Problem statementBeing a novice in R language, the problem I faced maight be a novice one,...

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R activity around the world

April 22, 2014
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R activity around the world

This project was inspired by "Where is the R Activity?" and our follow-up post on the number of useR! 2013 attendees. But instead of static maps, now we gathered bunch of R-related data from a variety of different sources to create some interactive car...

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Overlaying species occurrence data with climate data

April 22, 2014
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Overlaying species occurrence data with climate data

One of the goals of the rOpenSci is to facilitate interoperability between different data sources around web with our tools. We can achieve this by providing functionality within our packages that converts data coming down via web api's in one format (often a provider specific schema) into a standard format. The new version of rWBclimate that...

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High incidence in Measles Data in Project Tycho

April 21, 2014
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High incidence in Measles Data in Project Tycho

In this third post on Measles data I want to have a look at some high incidence occasions. As described before, the data is from Project Tycho, which contains data from all weekly notifiable disease reports for the United States dating back to 1888. These data are freely available to anybody...

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Old tails: a crude power law fit on ebook sales

April 18, 2014
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Old tails: a crude power law fit on ebook sales

We use R to take a very brief look at the distribution of e-book sales on Amazon.com. Recently Hugh Howey shared some eBook sales data spidered from Amazon.com: The 50k Report. The data is largely a single scrape of statistics about various anonymized books. Howey’s analysis tries to break sales down by declared category and Related posts:

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