Happy Halloween 2013

 

Happy Halloween to all you guys! Stay Safe and Party Hard!

Infographics on Why Others Can't Keep Their Old Insurance Plans

Check out the Infographics done by NYTimes, which explains why some people can't keep their insurance plans. It is very detailed and easy to comprehend. President Barrack Obama promised that people can keep their old insurance plan under the Obamacare, however the truth is most need to buy a new plan.

High resolution graphics with R

For most purposes PDF or other vector graphic formats such as windows metafile and SVG work just fine. However, if I plot lots of points, say 100k, then those files can get quite large and bitmap formats like PNG can be the better option. I just have to be mindful of the resolution.

As an example I create the following plot:

x <- rnorm(100000)
plot(x, main="100,000 points", col=adjustcolor("black", alpha=0.2))

Saving the plot as a PDF creates a 5.2 MB big file on my computer, while the PNG output is only 62 KB instead. Of course, the PNG doesn't look as crisp as the PDF file.

png("100kPoints72dpi.png", units = "px", width=400, height=400)
plot(x, main="100,000 points", col=adjustcolor("black", alpha=0.2))
dev.off()

Hence, I increase the resolution to 150 dots per pixel.

png("100kHighRes150dpi.png", units="px", width=400, height=400, res=150)
plot(x, main="100,000 points", col=adjustcolor("black", alpha=0.2))
dev.off()

This looks a bit odd. The file size is only 29 KB but the annotations look too big. Well, the file has only 400 x 400 pixels and the size of a pixel is fixed. Thus, I have to provide more pixels, or in other words increase the plot size. Doubling the width and height as I double the resolution makes sense.

png("100kHighRes150dpi2.png", units="px", width=800, height=800, res=150)
plot(x, main="100,000 points", col=adjustcolor("black", alpha=0.2))
dev.off()

Next I increase the resolution further to 300 dpi and the graphic size to 1600 x 1600 pixels. The file is still very crisp. Of course the file size increased. Now it is 654 KB in size, yet sill only about 1/8 of the PDF and I can embed it in LaTeX as well.

png("100kHighRes300dpi.png", units="px", width=1600, height=1600, res=300)
plot(x, main="100,000 points", col=adjustcolor("black", alpha=0.2))
dev.off()

Note, you can click on the charts to access the original files of this post.

High resolution graphics with R

For most purposes PDF or other vector graphic formats such as windows metafile and SVG work just fine. However, if I plot lots of points, say 100k, then those files can get quite large and bitmap formats like PNG can be the better option. I just have to be mindful of the resolution.

As an example I create the following plot:

x <- rnorm(100000)
plot(x, main="100,000 points", col=adjustcolor("black", alpha=0.2))

Saving the plot as a PDF creates a 5.2 MB big file on my computer, while the PNG output is only 62 KB instead. Of course, the PNG doesn't look as crisp as the PDF file.

png("100kPoints72dpi.png", units = "px", width=400, height=400)
plot(x, main="100,000 points", col=adjustcolor("black", alpha=0.2))
dev.off()

Hence, I increase the resolution to 150 dots per pixel.

png("100kHighRes150dpi.png", units="px", width=400, height=400, res=150)
plot(x, main="100,000 points", col=adjustcolor("black", alpha=0.2))
dev.off()

This looks a bit odd. The file size is only 29 KB but the annotations look too big. Well, the file has only 400 x 400 pixels and the size of a pixel is fixed. Thus, I have to provide more pixels, or in other words increase the plot size. Doubling the width and height as I double the resolution makes sense.

png("100kHighRes150dpi2.png", units="px", width=800, height=800, res=150)
plot(x, main="100,000 points", col=adjustcolor("black", alpha=0.2))
dev.off()

Next I increase the resolution further to 300 dpi and the graphic size to 1600 x 1600 pixels. The file is still very crisp. Of course the file size increased. Now it is 654 KB in size, yet sill only about 1/8 of the PDF and I can embed it in LaTeX as well.

png("100kHighRes300dpi.png", units="px", width=1600, height=1600, res=300)
plot(x, main="100,000 points", col=adjustcolor("black", alpha=0.2))
dev.off()

Note, you can click on the charts to access the original files of this post.

Obamacare website Utter Failure

Obamacare website has been a total disappointment from start. When healthcare.gov was opened to public on October 1, 2013 it crashed and the government blamed the overwhelming visitors of the site. It's now fixed, but there are new unresolved problems particularly in name registration, eligibility questions and in the most important step of buying insurance. It led users to cryptic error messages or enduring long waits when trying to sign up.

The number of Obamacare website problems since the website opened has been deeply embarrassing for the White House. The drawbacks have called into question whether the Obama administration is capable of implementing the complex policy they seems to be unaware of the scope of the problems when the exchange sites opened.

Even Obama acknowledges problems:

�Nobody is madder than me about the fact that the website is not working as well as it should, which means it�s gonna get fixed,� Obama said.

He even turn to an ex-adviser Jeffrey Zients, he is the former acting director of the White House budget office.

A person close to the project said that "No way it was properly tested before it went live" since the website is full of bugs and junk computer codes.

Review: K�lner R Meeting 18 October 2013

The Cologne R user group met last Friday for two talks on split apply combine in R and XLConnect by Bernd Wei� and G�nter Faes respectively, before the usual Schnitzel and K�lsch at the Lux.

Split apply combine in R

The apply family of functions in R is incredible powerful, yet for newcomers often somewhat mysterious. Thus, Bernd gave an overview of the different apply functions and their cousins. The various functions differ in their object inputs, e.g. vectors, arrays, data frames or lists, and their outputs. Other related functions are by, aggregate and ave. While functions like aggregate reduce the output size, others like ave will return as many rows as the input object and repeat the results where necessary.

Alternatively to the base R function Bernd touched also on the **ply functions of the plyr package. The function names are certainly easier to remember, but their syntax can be a little awkward (.()). Bernd's slides, in German, are already available from our Meetup site.

XLConnect

When dealing with data stored in spreadsheets most member of the group rely on read.csv and write.csv in R. However, if you have a spreadsheet with multiple tabs and formatted numbers, read.csv becomes clumsy, as you would have to save each tab without any formatting in separate files.

G�nter presented the XLConnect as an alternative to read.csv or indeed RODBC for reading spreadsheet data. It uses the Apache POI API as the underlying interface. XLConnect requires a Java runtime environment on your computer, but no installation of Excel. That makes it a true platform independent solution to exchange data with spreadsheets and R. Not only can you read defined rows and columns from Excel into R, or indeed named ranges, but in the same way data can be stored in Excel files again and to top it all - also graphic output from R.

Next K�lner R meeting

The next meeting is scheduled for 13 December 2013. A discussion of the data.table package is already on the agenda.

Please get in touch if you would like to present and share your experience, or indeed if you have a request for a topic you would like to hear more about. For more details see also our Meetup page.

Thanks again to Bernd Wei� for hosting the event and Revolution Analytics for their sponsorship.

Review: K�lner R Meeting 18 October 2013

The Cologne R user group met last Friday for two talks on split apply combine in R and XLConnect by Bernd Wei� and G�nter Faes respectively, before the usual Schnitzel and K�lsch at the Lux.

Split apply combine in R

The apply family of functions in R is incredible powerful, yet for newcomers often somewhat mysterious. Thus, Bernd gave an overview of the different apply functions and their cousins. The various functions differ in their object inputs, e.g. vectors, arrays, data frames or lists, and their outputs. Other related functions are by, aggregate and ave. While functions like aggregate reduce the output size, others like ave will return as many rows as the input object and repeat the results where necessary.

Alternatively to the base R function Bernd touched also on the **ply functions of the plyr package. The function names are certainly easier to remember, but their syntax can be a little awkward (.()). Bernd's slides, in German, are already available from our Meetup site.

XLConnect

When dealing with data stored in spreadsheets most member of the group rely on read.csv and write.csv in R. However, if you have a spreadsheet with multiple tabs and formatted numbers, read.csv becomes clumsy, as you would have to save each tab without any formatting in separate files.

G�nter presented the XLConnect as an alternative to read.csv or indeed RODBC for reading spreadsheet data. It uses the Apache POI API as the underlying interface. XLConnect requires a Java runtime environment on your computer, but no installation of Excel. That makes it a true platform independent solution to exchange data with spreadsheets and R. Not only can you read defined rows and columns from Excel into R, or indeed named ranges, but in the same way data can be stored in Excel files again and to top it all - also graphic output from R.

Next K�lner R meeting

The next meeting is scheduled for 13 December 2013. A discussion of the data.table package is already on the agenda.

Please get in touch if you would like to present and share your experience, or indeed if you have a request for a topic you would like to hear more about. For more details see also our Meetup page.

Thanks again to Bernd Wei� for hosting the event and Revolution Analytics for their sponsorship.

Next K�lner R User Meeting: 18 Oktober 2013

Quick reminder: The next Cologne R user group meeting is scheduled for this Friday, 18 October 2013. We will discuss and hear about the apply family of functions and the XLConnect package. Further details and the agenda are available on our K�lnRUG Meetup site. Please sign up if you would like to come along. Notes from past meetings are available here.

Thanks to Revolution Analytics, who sponsors the Cologne R user group as part of their vector programme.

View Larger Map

Next K�lner R User Meeting: 18 Oktober 2013

Quick reminder: The next Cologne R user group meeting is scheduled for this Friday, 18 October 2013. We will discuss and hear about the apply family of functions and the XLConnect package. Further details and the agenda are available on our K�lnRUG Meetup site. Please sign up if you would like to come along. Notes from past meetings are available here.

Thanks to Revolution Analytics, who sponsors the Cologne R user group as part of their vector programme.

View Larger Map

Thousand of Users are Visiting Online insurance Exchanges

FRANKFORT, KY. - More than 160,000 users have visited the kynect.ky.gov to check and review information about health insurance coverage. The online visitors also have viewed more than 2.6 million web pages on kynect since Kentucky launched the health benefit exchange last Tuesday.

Gov. Steve Beshear's office said in a news release Monday that more than 6,080 individuals and/or families are now enrolled in new affordable health care coverage that will go into effect on Jan. 1.

As of 4pm Monday, 142,242 people had completed the pre-screening process to determine if they qualify for subsidies and discounts for insurance policies or to determine if they qualify for Medicaid.

About 19,372 applications for health care coverage have been started and 12,955 are now completed.

Health Insurance Marketplace or Exchanges now Open

Insurance Marketplace or Exchanges is now open. Affordable Care Act or the Obamacare gives you only two choices pay a penalty or buy health insurance. The insurance marketplaces are for those who are not insured and those who buy their own insurance (not provided by the employer).

If you already have insurance from work or through Medicare you don't need this exchanges. The Open Enrollment is from October 1, 2013 and closes on March 31, 2014.

Here are the points to remember:

� the Coverage purchased through the marketplace starts as soon as January 1, 2014. Because many of ObamaCare's benefits, rights and protections will take effect on 2014.

� There are three types of cost assistance available through marketplaces: Advanced premium tax credits which lower your monthly premium costs, cost sharing subsidies which lower your out-of-pocket costs for copays, coinsurance and deductibles, and Medicaid. Learn more about ObamaCare Cost Assistance.

� Cost assistance through the marketplace is available to Americans who make less than 400% of the Federal Poverty Level ($45,960 for an individual $94,200 for a family of four).

� The 2013 Federal Poverty Guidelines are used to determine cost assistance on the marketplace.

� Young adults can now stay on their parents health insurance plans until they are 26.

� Plans are presented in four categories � bronze, silver, gold, and platinum � to make comparing them easier.

The Insurance plans that are in the Marketplace are offered by private companies. They cover the same core set of benefits called essential health benefits. Insurance companies cannnot turn you away or charge you more for preexisting medical condition or illness. They must cover treatments for these conditions. Plans can't charge women more than men for the same plan. Many preventive services are covered at no cost to you. However, despite of these benefits many still decided to opt out.

The Opt Out Penalty is $95 fine per adult; $47.50 penalty per child; and a maximum of $235, per family. That, or 1% of your adjusted gross income; whichever is greater. It is also set to increase yearly. The penalty is still much cheaper than forking out  $300-$500 a month for insurance.