# 2839 search results for "ggplot2"

## Twitter sentiment analysis based on affective lexicons with R

Continue to dig tweets. After we reviewed how to count positive, negative and neutral tweets in previous post, I discovered another great idea. Suppose positive or negative is not enough and we want to understand the rate of positivity or negativity. For example, “good” in tweet has 4 points rating, but “perfect” has 6. Thus, we... Read More »

## European MEP Data, Part 2

May 11, 2014
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Following last week's short examination, I now wanted to drill down a bit more in the voting behaviour as given in data from votewatch.eu on voting of MEPs.Votewatch's Data describe how often MEPs voted what in the European Parliament. For each MEP the number of votes, percentages Yes, No, Abstain, number of elections and...

## Further points on crayon colors

May 9, 2014
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I saw this great post on crayola crayon colors at the Learning R blog, reproducing a nice graph of the Crayola crayon colors over time. (Also see this even nicer version.) The Learning R post shows how to grab the crayon colors from the wikipedia page, “List of Crayola crayon colors,” directly in R. Here’s

## Hazardous and Benign Space Objects: Solving Kepler’s Equation

May 8, 2014
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$Hazardous and Benign Space Objects: Solving Kepler’s Equation$

Following on from my previous post about Near Earth Objects, today we are going to solve Kepler’s Equation to find the eccentric anomaly, which is the next step towards plotting the positions of these NEOs relative to Earth. The Eccentric, True and Mean Anomalies The relationship between the eccentric and true anomalies are depicted in

## Relation of Word Order and Compression Ratio and Degree of Structure

May 7, 2014
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Having a habit of compulsively wondering approximately every 34.765th day about how zip compression (bzip2 in this case) might be used to measure information contained in data – this time the question popped up in my head of whether or … Continue reading →

## A comment on “We cannot afford to study effect size in the lab” from the DataColada blog

May 6, 2014
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In a recent post on the DataColada blog, Uri Simonsohn wrote about “We cannot afford to study effect size in the lab“. The central message is: If we want accurate effect size (ES) estimates, we need large sample sizes (he suggests four-digit n’s). As this is hardly possible in the lab we have to use

## 7 R Quirks That Will Drive You Nutty

May 5, 2014
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7 R Quirks That Will Drive You Nutty StumpedEvery language has its idiosyncrasies. Some “designer”“ type languages have less due to extreme thoughtfulness of language engineers. I suspect Julia for example has many less quirks. However, despite...

## Rforecastio Package Update (1.1.0)

May 4, 2014
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I’ve bumped up the version number of Rforecastio (github) to 1.1.0. The new features are: removing the SSL certificate bypass check (it doesn’t need it anymore) using plyr for easier conversion of JSON->data frame adding in a new daily forecast data frame roxygen2 inline documentation library(Rforecastio) library(ggplot2) library(plyr)   # NEVER put API keys in

## How much code have you written?

May 3, 2014
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This past week I attended the National Water Quality Monitoring Conference in Cincinnati. Aside from spending my time attending talks, workshops, and meeting like-minded individuals, I spent an unhealthy amount of time in the hotel bar working on this blog post. My past experiences mixing coding and beer have suggested the two don’t mix, but

## A clear picture of power and significance in A/B tests

May 3, 2014
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A/B tests are one of the simplest reliable experimental designs. Controlled experiments embody the best scientific design for establishing a causal relationship between changes and their influence on user-observable behavior. “Practical guide to controlled experiments on the web: listen to your customers not to the HIPPO” Ron Kohavi, Randal M Henne, and Dan Sommerfield, Proceedings Related posts: