Common birthdays


This visualisation shows the popularity of birthdays in the US between 1973 – 1999. The darkness of the colour shows the rank of how popular that birthday is. Dark colours are more popular (i.e. better ranked) birthdays.

  • Most people are born in August & September (and therefore were conceived around November & December, during the holidays, perhaps?)
  • However, very few people are actually born during holidays – New year, Independence day, Halloween, Thanksgiving and Christmas. (People don’t like to spoil their holidays?)
  • Few people are born on the 1st of April. (You don’t want your kid born on Fool’s Day)
  • Few people are born on the 13th of any month. (Unlucky?)
  • Plenty are born on Valentine’s Day and St Patrick’s day

We tried to see what this looked like in India.

Based on school registration data for ~700,000 students born between 1992 – 1995, here’s what it looks like. (Click for a larger version.)


This shows a number of bizarre patterns:

  • Almost everyone’s born between May and June – just before the school opens.
  • Almost no one is born in August – after school opens.
  • An unusual number of people have round-numbered days as birthdays – 5th, 10th, 15th, 20th, 25, and 30th. (This round-numbered pattern was also seen when we analysed utility fraud).
  • January 1st is fairly popular. Other than that, none of the holidays seem to have an effect.

In fact, these results are so striking that we are tempted to believe that the popularly accepted proof for a person’s age – their Class 10 certificate – generally bears a convenient fiction created for the purposes of school admission several years ago.

The Social Network of Coders

Every problem faces the problem of finding smart, motivated people. Joel Spolsky offers this advice for finding great developers:

Think about where the people you want to hire are hanging out… Go to their conferences where you’ll find early adopters who are curious about new things and always interested in improving.

These days, the smart folks hang out at Github. (Github is like Facebook for coders. Coders can follow each other, and instead of uploading photos, they upload code.)

Last year, Matt Biddulph published a piece on Algorithmic recruitment with Github, and plotted the social network of coders on Github in specific cities: San Francisco and London in particular. People have extended this effort to other cities, but none in India.

At Gramener, we took a look at the Github follower network in various cities in India. The images below show the social network of Github users at Bangalore and Chennai – the Indian cities with the most users on Github.


Firstly, Bangalore, with 1460 users, clearly has more coders than Chennai (658). But what’s also interesting is the relatively large networked cluster in Bangalore. This is something that’s lacking in most other cities, as you can see below.


These cities tend to have smaller, disparate clusters. Whereas, in Bangalore, if you know some of the top Github users, you can easily hop from person to person and cover most of the popular users on Github. You can also guess that Hyderabad, Mumbai and Delhi (especially) are a bit less “sociable” and tend to form islands, when compared to Chennai or Pune.

In a way, this is reflected in the city’s social interaction as well. It’s a whole lot easier to meet a group of developers in Bangalore than it is in almost any other city in India.

To make your life easier, we’ve created a tool that lets you explore this social network.


Each coder is shown as a circle. The size of the circle increases with the number of followers. The colour of the circle changes based on their primary programming language. The labels indicate their Github user ID, the number of followers and their main programming language. Lines indicate that a user is following another. You can move each circle around to get a better view, and click on the circle to open their Github page.

This graph is called a force-directed layout. They are an excellent way of exploring and visualising small-scale networks interactively, since it lets you compare the structure of different networks, and also drill deep into every node in a network.

Visit to see the tool in action.

Musical sunbursts

We often wonder what songs would look like. Here’s our take on what Bobby McFerrin’s Don’t Worry Be Happy looks like.


This picture is a spectrogram of the song. It starts at the 12 o’clock position, and moves clockwise, ending at about 4:00 minutes. The intensity of colour indicates the volume at different frequencies – blue for high volume, red for medium, yellow for low and white for zero. The outer radius represents the lower frequencies and the inner radius the higher frequencies.

This sort of picture almost gives you a “fingerprint” of the song, and a feel for the kinds of ups-and-downs. For example, if you look at Bryan Adam’s Everything I Do, you can clearly see the light beginning, the somewhat stronger middle; then a pause before the 3:00 mark, strong again, and then fading out.

Bryan Adams.Everything I Do (I Do It For You).mp3

For your amusement, here are what a few more songs would look like – a mix of Bollywood, old and new.