243 search results for "web scraping"

What to Expect?

January 22, 2010
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What to Expect?

In 2007, I was introduced to Twitter via the written qualifying exam towards my Ph.D.. At first, I did not know what to do with it. After a good year or so (maybe even sooner) passed, I began to follow some very interesting people that share the same interests as me. It has transformed my academic experience. It is...

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The Hype Bubble Map for Dog Breeds

April 18, 2016
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The Hype Bubble Map for Dog Breeds

In the whole history of the world there is but one thing that money can not buy… to wit the wag of a dog’s tail (Josh Billings) In this post I combine several things: Simple webscraping to read the list of companion dogs from Wikipedia. I love rvest package to do these things. Google Trends … Continue reading...

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On the growth of CRAN packages

April 15, 2016
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On the growth of CRAN packages

by Andrie de Vries Every once in a while somebody asks me how many packages are on CRAN. (More than 8,000 in April, 2016). A year ago, in April 2015, there were ~6,200 packages on CRAN. This poses a second question: what is the historical growth of CRAN packages? One source of information is Bob Muenchen's blog R Now...

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Performing SQL selects on R data frames

March 13, 2016
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Performing SQL selects on R data frames

For anyone who has SQL background and who wants to learn R, I guess the sqldf package is very useful because it enables us to use SQL commands in R. One who has basic SQL skills can manipulate data frames in R using their SQL skills. You can read more about sqldf package from cran. Related Post

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Who Has the Best Fantasy Football Projections? 2016 Update

March 12, 2016
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Who Has the Best Fantasy Football Projections? 2016 Update

In prior posts, we demonstrated how to download projections from numerous sources, calculate custom projections for your league, and compare the accuracy of different sources of projections (2013, 2014, 2015).  In The post Who Has the Best Fantasy Football Projections? 2016 Update appeared first on Fantasy Football Analytics.

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Developing a R Tutorial shiny dashboard app

March 9, 2016
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Developing a R Tutorial shiny dashboard app

Through this post, I would like to describe a R Tutorial Shiny app that I recently developed. You can access the app here. (Please open the app on Chrome as some of the features may not work on IE. The app also includes a “ReadMe” introduction which provides a quick overview on how to use Related Post

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The Gender of Big Data

February 17, 2016
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The Gender of Big Data

When I grow up I want to be a dancer (Carmen, my beautiful daughter) The presence of women in positions of responsibility inside Big Data companies is quite far of parity: while approximately 5o% of world population are women, only 7% of CEOs of Top 100 Big Data Companies are. Like it or not, technology … Continue reading...

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Target Store Locations with rvest and ggmap

Target Store Locations with rvest and ggmap

I just finished developing a presentation for Target Analytics Network showcasing geospatial and mapping tools in R . I decided to use Target store locations as part of a case study in the presentation. The problem: I didn’t have any store location data, so I needed to get it from somewhere off the web. Since... Continue reading →

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Craft httr calls cleverly with curlconverter

February 10, 2016
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Craft httr calls cleverly with curlconverter

When you visit a site like the LA Times’ NH Primary Live Results site and wish you had the data that they used to make the tables & visualizations on the site: Sometimes it’s as simple as opening up your browsers “Developer Tools” console and looking for XHR (XML HTTP Requests) calls: You can actually

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New Version of “Wrangling F1 Data With R” Just Released…

February 5, 2016
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New Version of “Wrangling F1 Data With R” Just Released…

So I finally got round to pushing a revised (and typo corrected!) version of Wrangling F1 Data With R: A Data Junkie’s Guide, that also includes a handful of new section and chapters, including descriptions of how to detect undercuts, the new style race history chart that shows the on-track position of each driver for

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