330 search results for "boxplot"

Data Science, Data Analysis, R and Python

The October 2012 issue of Harvard Business Review prominently features the words “Getting Control of Big Data” on the cover, and the magazine includes these three related articles:“Big Data: The Management Revolution,” by Andrew McAfee and Erik Brynjolfsson, pages 61 – 68;“Data Scientist: The Sexiest Job of the 21st Century,” by Thomas H. Davenport and D.J. Patil, pages...

Read more »

We NEED more data

November 22, 2012
By
We NEED more data

Email One of the historic difficulties of doing research on urban energy systems has been the limited availability of data at sufficiently detailed spatial resolutions. Without this data, you might end up relying on aggregate information about the built environment, building occupants, and local geography that doesn't apply to the specifics of a particular neighbourhood

Read more »

Data types, part 3: Factors!

November 21, 2012
By
Data types, part 3: Factors!

In this third part of the data types series, I'll go an important class that I skipped over so far: factors.Factors are categorical variables that are super useful in summary statistics, plots, and regressions. They basically act like dummy variables t...

Read more »

The Hour of Hell of Every Morning – Commute Analysis, April to October 2012

November 19, 2012
By
The Hour of Hell of Every Morning – Commute Analysis, April to October 2012

IntroductionSo a little while ago I quit my job.Well, actually, that sounds really negative. I'm told that when you are discussing large changes in your life, like finding a new career, relationship, or brand of diet soda, it's important to frame things positively.So let me rephrase that - I've left job I previously held to pursue other directions. Why?...

Read more »

Textual Healing Part II

November 15, 2012
By
Textual Healing Part II

Yesterday’s post showed a number of quick coding options for changing text in a basic ggplot. Here’s another two tricks for fine-tuning faceted plots. Again, let’s load our made up data about tooth growth (a real dataset in R, ToothGr...

Read more »

In case you missed it: October 2012 Roundup

November 7, 2012
By

In case you missed them, here are some articles from October of particular interest to R users. Sponsorships for local R user groups from Revolution Analytics are now open to applicants worldwide. During the landfall of Hurricane Sandy in the US, several R-based apps used public weather and social media data to document its impact, like this timeline of...

Read more »

Another look at ideology of the US congress

November 5, 2012
By
Another look at ideology of the US congress

In response to last week's post on the rapidly increasing ideology of the US Republican Party, Mike Lawrence suggested another way of looking at the DW-NOMINATE ideology data. Rather than simply looking at boxplots of the congress scores by party over time, we could fit a smooth curve to get a better sense of the trends over time. Mike...

Read more »

Reordering factor levels in R plots

November 3, 2012
By
Reordering factor levels in R plots

A few days ago a post doctoral researcher asked me if I could help him reorder the factor levels on a bar chart. The problem is that R automatically alphabetizes factor levels. I thought this would be fairly straight-forward but...

Read more »

Volatility from daily or monthly: garch evidence

October 29, 2012
By
Volatility from daily or monthly: garch evidence

Should you use daily or monthly returns to estimate volatility? Does garch explain why volatility estimated with daily data tends to be bigger than if it is estimated with monthly data? Previously There are a number of previous posts — with the variance compression tag — that discuss the phenomenon of volatility estimated with daily … Continue reading...

Read more »

Carl Morris Symposium on Large-Scale Data Inference (2/3)

October 20, 2012
By
Carl Morris Symposium on Large-Scale Data Inference (2/3)

Continuing the summary of last week’s symposium on statistics and data visualization (see part 1 and part 3)… Here I describe Dianne Cook’s discussion of visual inference, and Rob Kass’ talk on statistics in cognitive neuroscience. [Edit: I've added a few … Continue reading →

Read more »