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This is the second in a series of articles looking into whether when you were born affects your future. In the previous article I looked at Nobel laureates, which are, of course, from a range of fields. Now it is time to focus on just one discipline with poets. I have again used ScraperWiki to scrape wikipedia. This time using its list of poets and extracting each person's Date of Birth.

The dates of birth were collated and from this frequency charts were constructed for the months of birth and star signs of the poets. The findings are illustrated below.

Distribution of Months of Birth Among Poets There is not too much difference here between the months, although October and June do stand out as having more poets or less poets respectively. The difference between October and June is 2.99%. This is interesting as the result for poets born in June is the inverse of the result for Nobel laureates born in June, where they were most likely to become a Nobel laureate.

Distribution of Star Signs Among Poets As with Nobel laureates the difference in distribution of star signs among poets seems to be much greater then the distribution of the months in which they were born. We can see from the graph that Pisceans are more likely to be poets than Geminis and Taureans. However, if you look more closely at Pisces at the top and Gemini at the bottom, you will find that while the difference is 2.8%, this is actually less than the difference between highest and lowest for months of birth.

The problems with this study are similar to those for the article about Nobel laureates.

Unlike Nobel laureates the distribution of birth periods among poets seems to be about the same for star signs and months of birth. It seems that if your are a Piscean or born in October then you are more likely to be a poet and if you are a Gemini or born in June then you are less likely.

This series highlights the power of scraping the web to extract these sort of statistics and given the time, this could be extended to increase confidence in the data and draw more accurate conclusions. If you would like to commission, vLife Systems, to create a scraper which will extract data from websites or other data sources of interest to you, please get in touch via email: info@vlifesystems.com.

I have given examples of the code used to scrape Wikipedia in the previous article. For this article I will just reference the scrapers and provide code for one of the views instead.

The view is again written in Ruby and has html and JavaScript embedded within an erb template. The JavaScript is being used to create a graph with Google Charts.

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