library(XML)url="http://stats.espncricinfo.com/ci/engine/stats/index.html?class=1;team=6;template=results;type=batting"#Note I can also break the url string and use paste command to modify this url with parameters
tables$"Overall figures"#Now see this- since I only got 50 results in each page, I look at the url of next page
table2=tables$"Overall figures"#Now I need to join these two tables vertically
Note-I can also automate the web scraping .
Now the data is within R, we can use something like Deducer to visualize.
A highly optimized blog post or web content can get you a lot of attention just like Rebecca Black’s video (provided it passes through the new quality metrics \change*/ in the Search Engine)
But if the underlying content is weak, or based on a shoddy understanding of the content-it can drive lots of horrid comments as well as ensuring that bad word of mouth is spread about the content or you/despite your hard work.
An example of this is copy and paste journalism especially in technology circles, where even a bigger Page Ranked website /blog can get away with scraping or stealing content from a lower page ranked website (or many websites) after adding a cursory “expert comment”. This is also true when someone who is basically a corporate communication specialist (or PR -public relations) person is given a techinical text and encourage to write about it without completely understanding it.
A mild technical defect in the search engine algorithm is that it does not seem to pay attention to when the content was published, so the copying website or blog actually can get by as fresher content even if it is practically has 90% of the same words). The second flaw is over punishment or manual punishment of excessive linking – this can encourage search optimization minded people to hoard links or discourage trackbacks.
A free internet is one which promotes free sharing of content and does not encourage stealing or un-authorized scraping or content copying. Unfortunately current search engine optimization can encourage scraping and content copying without paying too much attention to origin of the words.
In addition the analytical rigor by which search algorithms search your inboxes (as in search all emails for a keyword) or media rich sites (like Youtube) are quite on a different level of quality altogether. The chances of garbage results are much more while searching for media content and/or emails.
# Colored Histogram with Different Number of Bins
hist(mtcars$mpg, breaks=12, col="red")
click to view
# Add a Normal Curve (Thanks to Peter Dalgaard)
x <- mtcars$mpg
h<-hist(x, breaks=10, col="red", xlab="Miles Per Gallon",
main="Histogram with Normal Curve")
yfit <- yfit*diff(h$mids[1:2])*length(x)
lines(xfit, yfit, col="blue", lwd=2)
click to view
Histograms can be a poor method for determining the shape of a distribution because it is so strongly affected by the number of bins used.
KERNEL DENSITY PLOTS
Kernal density plots are usually a much more effective way to view the distribution of a variable. Create the plot using plot(density(x)) where x is a numeric vector.
# Kernel Density Plot
d <- density(mtcars$mpg) # returns the density data
plot(d) # plots the results
click to view
# Filled Density Plot
d <- density(mtcars$mpg)
plot(d, main="Kernel Density of Miles Per Gallon")
polygon(d, col="red", border="blue")
click to view
COMPARING GROUPS VIA KERNAL DENSITY
The sm.density.compare( ) function in the smpackage allows you to superimpose the kernal density plots of two or more groups. The format is sm.density.compare(x, factor) where x is a numeric vector and factor is the grouping variable.
# Compare MPG distributions for cars with
# 4,6, or 8 cylinders
I have received numerous requests for a hardcopy version of this site, so over the past year I have been writing a book that takes the material here and significantly expands upon it. If you are interested, early access is available.
Click per milli (or CPM) gives you a very low low conversion compared to contacting ad sponsor directly.
But its a great data experiment-
as you can monitor which companies are likely to be advertised on your site (assume google knows more about their algols than you will)
which formats -banner or text or flash have what kind of conversion rates
what are the expected pay off rates from various keywords or companies (like business intelligence software, predictive analytics software and statistical computing software are similar but have different expected returns (if you remember your eco class)
NOW- Based on above data, you know whats your minimum baseline to expect from a private advertiser than a public, crowd sourced search engine one (like Google or Bing)
Lets say if you have 100000 views monthly. and assume one out of 1000 page views will lead to a click. Say the advertiser will pay you 1 $ for every 1 click (=1000 impressions)
Then your expected revenue is $100.But if your clicks are priced at 2.5$ for every click , and your click through rate is now 3 out of 1000 impressions- (both very moderate increases that can done by basic placement optimization of ad type, graphics etc)-your new revenue is 750$.
Be a good Samaritan- you decide to share some of this with your audience -like 4 Amazon books per month ( or I free Amazon book per week)- That gives you a cost of 200$, and leaves you with some 550$.
Wait! it doesnt end there- Adam Smith‘s invisible hand moves on .
You say hmm let me put 100 $ for an annual paper writing contest of $1000, donate $200 to one laptop per child ( or to Amazon rain forests or to Haiti etc etc etc), pay $100 to your upgraded server hosting, and put 350$ in online advertising. say $200 for search engines and $150 for Facebook.
Month 1 would should see more people visiting you for the first time. If you have a good return rate (returning visitors as a %, and low bounce rate (visits less than 5 secs)- your traffic should see atleast a 20% jump in new arrivals and 5-10 % in long term arrivals. Ignoring bounces- within three months you will have one of the following
1) An interesting case study on statistics on online and social media advertising, tangible motivations for increasing community response , and some good data for study
2) hopefully better cost management of your server expenses
3)very hopefully a positive cash flow
you could even set a percentage and share the monthly (or annually is better actions) to your readers and advertisers.
go ahead- change the world!
the key paradigms here are sharing your traffic and revenue openly to everyone
donating to a suitable cause
helping increase awareness of the suitable cause
basing fixed percentages rather than absolute numbers to ensure your site and cause are sustained for years.
Just go to Users-Personal Settings- and check the options shown. Thats it every time you write a post it suggests links and tags. Links are helpful for your readers (like Wikipedia links to understand dense technical jargon, or associated websites). Tags help to classify your contents so that all visitors to the web site including spiders ,search engines and your readers can search it better.
The bad thing is I need to go back to all 1025 posts on this site and auto generate tags for the archives ! Oh well. Great collaboration between zementa and Automattic for this new feature.