Month: May 2015

Solution to [Viral] Math Puzzle for Vietnamese Eight-Year-Olds (Using R)

Anirudh Technical , ,

There was this math problem that went viral recently –  it was a Singapore Math Olympiad problem meant for 14-year olds which surprisingly many adults couldn’t solve. A friend sent me a link to that problem and I solved it with pen and paper in about 10 minutes, leaving me feeling hardly challenged. I guess really-tough questions aren’t the ones that actually go viral. If anything, a math problem going viral means it caters to an average IQ, something like a 100 – which then left me wondering whatever my IQ was! I had taken many online IQ tests when I was pursuing my engineering degree and my scores ranged between 135 and 145. But they weren’t tests one could really feel great about, mainly because everyone I knew who took them, scored 110+. I never took a Mensa test in the past, so I’m not sure whether I’d have made the cut. Anyway, I decided to check Quora to see if the nerds had found anything remotely mimicking a Mensa type IQ test. So I checked out this one and got a 130. It seems to be the least I’ve ever got on an IQ test, so without giving you any rationale to why I feel this might be closer to accurately measuring your IQ, I say it’s probably worth a shot.

iq_test_score

 

A week back, there was yet another math puzzle that had gone viral, meant for Vietnamese eight-year-olds, a problem that had stumped parents and teachers. You need to fill in the empty boxes below with the digits from 1 to 9 so that the equation makes sense, following the order of operations – multiply first, then division, addition and subtraction last. Apparently, this problem was for third graders in the town of Bao Loc in the Vietnamese Highlands.

I didn’t solve this one with pen and paper, and instead wrote an R program. It’s clearly a problem with a fixed number of variables (nine) associated with standard math operators, meaning there would be 9! (362880) permutations – which makes you think there’s got to be more than one solution. It became obvious I had to write some code.

I wrote a function appropriately named baoloc() to list out the solutions to this problem. The code is self explanatory. I got 128 unique solutions, which means if the students had to solve this problem with pencil on paper, they could get one of 128 possible answers, which makes the job of the examiner arduous and boring!

## The problem could be written as u + 13v/w + x + 12y - z - 11 + pq/r -10 = 66
## which reduces to u + 13v/w + x + 12y - z + pq/r = 87
## This problem was solved on [1] "Wed May 27 17:46:52 2015"
baoloc <- function()
{
packages <- rownames(installed.packages())
if("combinat" %in% packages) library("combinat") else install.packages("combinat")
numbers <- 1:9
permutations <- permn(numbers) ## list of all permutations of vector input
solutions <- numeric(9)
for(i in 1:length(permutations))
{
solution <- permutations[[i]]
if(solution[1] + 13*(solution[2]/solution[3]) + solution[4] + 12*solution[5] - solution[6] + (solution[7]*solution[8] / solution[9]) == 87)
{
solutions <- rbind(solutions, solution)
}
}
print("The number of solutions are:")
print(nrow(solutions)-1)
return(solutions[2:nrow(solutions),])
}
view raw baoloc.R hosted with ❤ by GitHub

The above code produces the following solutions:
[1] "The number of solutions are:"
[1] 128
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9]
solution 9 1 2 5 6 7 3 4 8
solution 7 9 6 1 5 2 3 4 8
solution 1 9 6 7 5 2 3 4 8
solution 1 5 2 3 4 8 7 9 6
solution 1 5 2 3 4 8 9 7 6
solution 5 1 2 9 6 7 3 4 8
solution 5 1 2 9 6 7 4 3 8
solution 1 5 2 8 4 7 3 9 6
solution 1 5 2 8 4 7 9 3 6
solution 1 9 6 7 5 2 4 3 8
solution 7 9 6 1 5 2 4 3 8
solution 9 1 2 5 6 7 4 3 8
solution 1 2 6 4 7 8 5 3 9
solution 1 2 6 4 7 8 3 5 9
solution 1 4 8 2 7 9 3 5 6
solution 1 4 8 2 7 9 5 3 6
solution 7 1 4 9 6 5 2 3 8
solution 9 1 4 7 6 5 2 3 8
solution 5 4 1 9 2 7 8 3 6
solution 5 4 1 9 2 7 3 8 6
solution 9 4 1 5 2 7 8 3 6
solution 9 4 1 5 2 7 3 8 6
solution 4 9 6 1 5 8 3 7 2
solution 4 9 6 1 5 8 7 3 2
solution 8 6 4 7 5 9 1 3 2
solution 7 6 4 8 5 9 1 3 2
solution 9 4 8 5 6 7 1 3 2
solution 5 4 8 9 6 7 1 3 2
solution 1 9 6 4 5 8 7 3 2
solution 1 9 6 4 5 8 3 7 2
solution 9 1 4 7 6 5 3 2 8
solution 7 1 4 9 6 5 3 2 8
solution 1 3 9 4 7 8 2 5 6
solution 1 3 4 7 6 5 2 9 8
solution 1 3 4 7 6 5 9 2 8
solution 1 3 9 4 7 8 5 2 6
solution 1 5 3 9 4 2 7 8 6
solution 1 5 3 9 4 2 8 7 6
solution 1 3 2 9 5 6 7 4 8
solution 1 3 2 9 5 6 4 7 8
solution 1 3 6 2 7 9 5 4 8
solution 1 3 6 2 7 9 4 5 8
solution 1 3 2 4 5 8 7 9 6
solution 1 3 2 4 5 8 9 7 6
solution 6 3 1 9 2 5 8 7 4
solution 6 3 1 9 2 5 7 8 4
solution 9 3 1 6 2 5 8 7 4
solution 9 3 1 6 2 5 7 8 4
solution 7 3 1 5 2 6 8 9 4
solution 7 3 1 5 2 6 9 8 4
solution 5 3 1 7 2 6 9 8 4
solution 5 3 1 7 2 6 8 9 4
solution 9 5 3 1 4 2 7 8 6
solution 9 5 3 1 4 2 8 7 6
solution 3 1 4 2 7 9 6 5 8
solution 3 1 4 2 7 9 5 6 8
solution 7 3 4 1 6 5 9 2 8
solution 7 3 4 1 6 5 2 9 8
solution 3 6 4 9 5 8 1 7 2
solution 3 6 4 9 5 8 7 1 2
solution 5 4 8 9 6 7 3 1 2
solution 9 4 8 5 6 7 3 1 2
solution 7 6 4 8 5 9 3 1 2
solution 8 6 4 7 5 9 3 1 2
solution 9 6 4 3 5 8 1 7 2
solution 9 6 4 3 5 8 7 1 2
solution 4 3 9 1 7 8 5 2 6
solution 4 3 9 1 7 8 2 5 6
solution 4 3 2 1 5 8 9 7 6
solution 4 3 2 1 5 8 7 9 6
solution 3 2 4 8 5 1 7 9 6
solution 3 2 4 8 5 1 9 7 6
solution 5 9 3 6 2 1 8 7 4
solution 5 9 3 6 2 1 7 8 4
solution 3 5 2 1 4 8 9 7 6
solution 3 5 2 1 4 8 7 9 6
solution 6 9 3 5 2 1 7 8 4
solution 6 9 3 5 2 1 8 7 4
solution 3 9 6 2 5 1 7 4 8
solution 3 9 6 2 5 1 4 7 8
solution 3 2 8 6 5 1 7 9 4
solution 3 2 8 6 5 1 9 7 4
solution 7 3 2 8 5 9 6 1 4
solution 8 3 2 7 5 9 6 1 4
solution 8 3 2 7 5 9 1 6 4
solution 7 3 2 8 5 9 1 6 4
solution 3 2 1 5 4 7 8 9 6
solution 3 2 1 5 4 7 9 8 6
solution 3 9 2 8 1 5 7 6 4
solution 9 3 2 1 5 6 7 4 8
solution 3 9 2 8 1 5 6 7 4
solution 9 3 2 1 5 6 4 7 8
solution 2 3 6 1 7 9 4 5 8
solution 2 3 6 1 7 9 5 4 8
solution 8 9 2 3 1 5 6 7 4
solution 8 9 2 3 1 5 7 6 4
solution 2 9 6 3 5 1 4 7 8
solution 2 9 6 3 5 1 7 4 8
solution 6 2 8 3 5 1 9 7 4
solution 6 2 8 3 5 1 7 9 4
solution 7 2 8 9 6 5 3 1 4
solution 9 2 8 7 6 5 3 1 4
solution 8 7 2 5 3 9 6 1 4
solution 8 7 2 5 3 9 1 6 4
solution 5 7 2 8 3 9 1 6 4
solution 5 7 2 8 3 9 6 1 4
solution 8 2 4 3 5 1 9 7 6
solution 8 2 4 3 5 1 7 9 6
solution 8 5 2 7 4 9 3 1 6
solution 7 5 2 8 4 9 3 1 6
solution 4 2 6 1 7 8 3 5 9
solution 4 2 6 1 7 8 5 3 9
solution 7 5 2 8 4 9 1 3 6
solution 8 5 2 7 4 9 1 3 6
solution 2 4 8 1 7 9 5 3 6
solution 2 8 6 9 4 1 5 7 3
solution 2 8 6 9 4 1 7 5 3
solution 9 8 6 2 4 1 7 5 3
solution 9 8 6 2 4 1 5 7 3
solution 2 4 8 1 7 9 3 5 6
solution 2 1 4 3 7 9 5 6 8
solution 2 1 4 3 7 9 6 5 8
solution 8 5 2 1 4 7 9 3 6
solution 8 5 2 1 4 7 3 9 6
solution 5 2 1 3 4 7 9 8 6
solution 5 2 1 3 4 7 8 9 6
solution 9 2 8 7 6 5 1 3 4
solution 7 2 8 9 6 5 1 3 4
view raw solution_baoloc.R hosted with ❤ by GitHub

How to become a programmer, or the art of Googling well

Anirudh Non Technical , , ,

This should serve as encouragement to all and sundry. Stop wasting time getting intimidated and learn to code like a pro.

Featured Image: http://xkcd.com/979/

okepi

*Note: Please read all italicized technical words as if they were in a foreign language.

The fall semester of my senior year, I was having some serious self-confidence issues. I had slowly come to realize that I did not, in fact, want to become a researcher. Statistics pained me, and the seemingly endless and fruitless nature of research bored me. I was someone who was driven by results – tangible products with deadlines that, upon completion, had a binary state: success, or failure. Going into my senior year, this revelation was followed by another. All of my skills thus far had been cultivated for research. If I wasn’t going into research, I had… nothing.

At a liberal arts college, being a computer science major does not mean you are a “hacker”. It can mean something as simple as, you were shopping around different departments, saw a command line for the…

View original post 1,398 more words

Excel using R

Anirudh Technical ,

Very often we find ourselves caught up with really mundane tasks involving voluminous excel data — in business and yes, even in research! The story keeps repeating everywhere. I’ll talk about how to automate some mechanical and brain-dead spreadsheet operations using R. This post will cover the basics of reading and writing operations on Excel data. There are 2 packages worth installing, that I’ve taken a liking to for this purpose. xlsx and XLConnect.

install.packages("xlsx","XLConnect")

Let’s say you have huge volumes of spreadsheet data, of a survey conducted in a city several times during the year (like every month or so). What if you were interested in only some of the details from that survey, and you wanted to extract those details for each time the survey was conducted that year, and summarize the whole thing in yet another spreadsheet. You don’t want to be repeatedly copying and pasting and wasting several man-hours doing so, especially if you had hundreds of surveys to scavenge from. Instead, a simple R script could complete the same task in minutes.

I’ll talk about an example scenario and walk you through the R code. I had data coming from a survey conducted every month of the year for the district of Agra, India — home to the Taj Mahal. Since they were the same survey conducted every month, the excel files were identical in format. Each file contained different data, but of same parameters being tested each month – so data in specific cells, say, E11:V11 were instances of the same metric common to each file. I wanted to stack data from these particular cells from each file onto a fresh excel workbook. I could have copy-pasted the whole thing and done the job manually, but I wasn’t just looking at data from one district, viz., Agra, but hundreds of other districts. This was obviously a task that badly needed automating.

So, for Agra, I had 12 spreadsheets corresponding to surveys for each month of the year. The R file (Agra) that you can see along with the excel files, is the script for creating the final spreadsheet that accomplished the earlier-mentioned objective.

Agra Directory

I wanted data taken from the cells E11:V11 from each of the above spreadsheets. For example, here’s how it looks for the April and May spreadsheets (highlighted portion)

A-Agra_April

B-Agra_May

I had to write R code to get the data from each of the spreadsheets to be neatly stacked in a fresh workbook named Outliers-Agra, and give appropriate row names, column names, and worksheet name, as in the screenshot below.

Agra-Outliers.xls

How was this done using R?

First, the necessary libraries had to be loaded into R, the ones talked about at the start of this post.

library("xlsx") 
library("XLConnect")

Next, I had to change the working directory to where the survey data was kept, in this case, a folder aptly named Agra. The files in the directory were stored in a vector named files. Since the main R-file where I was writing the script Agra.R, was part of that directory, it also was part of the vector files. The vector files was created to later read the spreadsheets iteratively using a for-loop, so Agra.R had to be deleted from it. This was done using the which() function to locate the position of the R-file, craftily using subsetting rules to remove it from the vector.

setwd("C:/Anirudh/Coding/R/Agra") ## CHANGE WORKING DIRECTORY as required
files <- list.files() ## vector containing the file names in that directory
files <- files[-which(files == "Agra.R")] ## Removes R-file (in this case, Agra.R) from the vector of files

An empty matrix, temp, was created to be exactly the size of the data to be read from all the excel files in the directory. The data from each file was then iteratively stored to fill temp. The read.xlsx() function is a function from the xlsx library. The arguments are mostly self-explanatory. files[i] subsets the ith instance in files. header is set FALSE to indicate that the top row of the excel file did not consist of variables.

temp <- matrix(nrow = length(files), ncol = 18) ## matrix, 18 columns as in 5:22, rows = no.of xls files
for(i in seq_along(files[1:length(files)]))
{
  dat <- read.xlsx(files[i], sheetIndex = 1, rowIndex = 11, colIndex = 5:22, header = FALSE)
  mat <- as.matrix(dat) ## reading data from 11th row of xlsx file into a matrix of row size 1
  temp[i,] <- mat ## storing data from above matrix into matrix temp
}

The contents of temp (a matrix object) were then stored in a data frame object before being written to a fresh excel file (this is necessary). For writing operations in excel, I used functions from the XLConnect library. The workbook had to be loaded using loadWorkbook() with the create argument set to TRUE to indicate that a fresh excel file was being created. If I had to write to an already existing file, the argument would have been set FALSE . I created a worksheet and named it ANC3 (that had got something to do with the data). startRow and startCol are set to the location where we want the data to begin from.

df <- as.data.frame(temp) ## storing contents of temp matrix as data frame
wb <- loadWorkbook("C:/Anirudh/Coding/R/Agra/Outliers-Agra.xlsx", create = TRUE) # new workbook
createSheet(wb, name = "ANC3") ## create worksheet / tab with name "ANC3"
writeWorksheet(wb, df, sheet = "ANC3", startRow = 2, startCol = 2, header = FALSE)

Next, the data in the new excel file, Outliers-Agra.xlsx was given appropriate column names (colnames) and row names (months).

colnames <- read.xlsx(files[i],sheetIndex = 1, rowIndex = 6, colIndex = 5:22, header = FALSE)
colnames <- as.data.frame(as.matrix(colnames))
months <- as.data.frame(matrix(c("April", "May", "June", "July", "August", "September","October", "November","December", "January", "February", "March")))
writeWorksheet(wb, colnames, sheet = "ANC3", startRow = 1, startCol = 2, header = FALSE)
writeWorksheet(wb, months, sheet = "ANC3", startRow = 2, startCol = 1, header = FALSE)

Lastly, the workbook needed to be saved.

saveWorkbook(wb)

After executing the R script, the new workbook Outliers-Agra is added to the parent directory.

Agra Directory with Agra.R and Outliers-Agra

So this is how some basic Excel work can be managed using R. Since these were only 12 files, writing all this code to perform simple copy and paste functions might seem like an awful lot to go through. But the data in this example was for one Indian district  (Agra) — and if you had to do the same thing thousands of times covering hundreds of districts (directories), you’d thank this gem of free software known as R, for what it can accomplish.

Featured Image: https://xkcd.com/1445/

Code for my First Text-Based Game

Anirudh Technical ,

I started learning Python from Learn Python the Hard Way, 10 days ago. The last scripting language I learnt was C++, but it was ages ago – and never took to it with as much interest as I am taking on Python. I learnt C++ to pass an undergraduate course in 2008, and that’s all I really wanted from it back then.

There are 52 exercises in the book, and I have finished the 36th exercise today. It required me to write code for a simple text-based game, the likes of which were people played by computer nerds in the 80’s when the GUIs weren’t as advanced as they are today. Sometimes nerds from our generation might also want to get a kick out of these text-based games, as evidenced by the following:

Here’s the python code for this text-based game you might want to try out. You can simply copy the code below into a text file, naming it something like game.py and save it to your home directory or wherever you wish to and run game.py from. Then from Terminal (CMD for Windows), type in python game.py. Of course, you need to have Python installed. If you want to learn how to create a text based game of your own, the best way would be to play such a game, simultaneously glancing at its code, understanding how the game was programmed to function. I haven’t over-complicated this one so that newbs like me could work out the map easily – and maybe add their own branches and make the game lot more interesting.

from sys import exit

def lion():
    print "You had to choose some direction and you chose West. You have been walking for miles.... and you're thirsty, and dehydrated."
    print "... you have just begun to feel you're walking into eternity when you see a T-junction. But just then you hear a ROAR!!!"
    print "You turn back to see a giant lion, miles away, running after you at great speed. You just have time to react. What now?"
    
    do_what = raw_input("> ")
    
    if "left" in do_what or "south" in do_what:
        print "Unfortunately for you, the lion catches up and rips you to shreds. You feel intense pain, yet you can't die. This is hell." 
        dead()
    elif "right" in do_what or "north" in do_what:
        print "You find a portal to another dimension. Could this be a trap? Or should you take that chance? What do you do?"
        do_what = raw_input("> ")
        if "portal" in do_what:
            cthulhu()
        else:
            dead()
    else:
        dead()

def princess():
    print "You have been walking for miles... and this is geting frustrating. Will this road ever end?"
    print "A dagger falls from the skies abvoe. What do you do?"
    do_what = raw_input("> ")
    if "dagger" in do_what or "pick" in do_what:
        print "lo and behold! A beautiful princess stands before you."
        print "A diamond on the hilt of your dagger turns the color of her eyes. This is a clue."
        what_color = raw_input("Do you see the color or blood?\n> ")
        print "... are you sexually attracted to her?"
        sexually_attracted = raw_input("> ")
        print "You'll have to make a choice. You can either go kiss in a warm embrace or kill her with your dagger. Which will it be?"
        your_choice = raw_input("> ")
        if "yes" in what_color or "blood" in what_color:
            if "kill" in your_choice:
                win()
            else:
                dead()
        elif "yes" in sexually_attracted:
            if "kiss" in your_choice:
                print "You have been betrayed by your lecherous lust. This goddess of desire turns into a dragon and burns you to dust."
                dead()
            else:
                win()
                
        elif "no" in sexually_attracted:
                if "kill" in your_choice:
                    print "What a muderous and sinful thing you did."
                    dead()
                else:
                    win()
        else:
            dead()
    else:
        print "You should have picked up the dagger. You never know what might be coming..."
        print "...but what do we have here!? A beautiful maiden! She looks like royalty. In fact she is a princess!"
        print "... are you sexually attracted to her?"   
        sexually_attracted = raw_input("> ")
        if "yes" in sexually_attracted:
            print "You have been betrayed by your lecherous lust. This goddess of desire turns into a dragon and burns you to dust."
            dead()
        else:
            print "The princess gives you a magic potion that can grant you any boon."
            print "You ask for all the happiness and riches of the world"
            win()                        

    
        
def prince():
    print "You have been walking for miles... and this is geting frustrating. Will this road ever end?"
    print "A dagger falls from the skies abvoe. What do you do?"
    do_what = raw_input("> ")
    if "dagger" in do_what or "pick" in do_what:
        print "lo and behold! A handsome prince stands before you."
        print "A diamond on the hilt of your dagger turns the color of his hair. This is a clue."
        what_color = raw_input("Do you see the color or blood?\n> ")
        print "... are you sexually attracted to him?"
        sexually_attracted = raw_input("> ")
        print "You'll have to make a choice. You can either go kiss in a warm embrace or kill him with your dagger. Which will it be?"
        your_choice = raw_input("> ")
        if "yes" in what_color or "blood" in what_color:
            if "kill" in your_choice:
                win()
            else:
                dead()
        elif "yes" in sexually_attracted:
            if "kiss" in your_choice:
                print "You have been betrayed by your lecherous lust. This god of desire turns into a dragon and burns you to dust."
                dead()
            else:
                win()
                
        elif "no" in sexually_attracted:
                if "kill" in your_choice:
                    print "What a muderous and sinful thing you did."
                    dead()
                else:
                    win()
        else:
            dead()
    else:
        print "You should have picked up the dagger. You never know what might be coming..."
        print "...but what do we have here!? A handsome prince!"
        print "... are you sexually attracted to him?"   
        sexually_attracted = raw_input("> ")
        if "yes" in sexually_attracted:
            print "You have been betrayed by your lecherous lust. This god of desire turns into a dragon and burns you to dust."
            dead()
        else:
            print "The prince gives you a magic potion that can grant you any boon."
            print "You ask for all the happiness and riches of the world"
            win()                        


def cthulhu():
    print "You walk for miles into what seems like an endless abyss. And then he presents himself. The evil Cthulhu."
    print "He, it, or whatever - stares at you and you go insane."
    print "Do you flee for your life or eat your head?"
    
    next = raw_input("> ")
    
    if "flee" in next:
        start()
    elif "head" in next:
        cthulhu()
        
def win():
    print "You made an excellent choice. You win. You are magically transported to your time, your world."
    print "Exit? (y / n)"
    exit = raw_input("> ")
    if "y" in exit or "Y" in exit:
        exit(0)
    else:
        start()        


def dead():
    print "Wrong move friend. You shall be lost forever into the infinite abyss of the tree of the undead."
    exit(0)

def start():
    print "You are walking through an enchanted forest with gigantic trees as tall as mountains and as thick as large lakes."
    print "You got here magically teleported into a distant planet in a distant galaxy in the future."
    print "You see one such tree with a cave-like structure at its base. What do you do?"
    
    do_what = raw_input("> ")
    
    while True:
        if "cave" in do_what or "cave-like" in do_what or "enter" in do_what:
            print "You enter  the dark hollow of an ancient tree that has had earthlings like you in the past."
            print "This tree is called the tree of the undying, where death won't touch you."
            print "On the other hand, pain can - if you don't make the right moves. And then you have to live with the pain for eternity."
            print "You are suddenly sucked into a vortex, finding yourself at crossroads of sorts." 
            print "From here, you can go north, south, east or west."
        
            while True: 
                now_what = raw_input("> ")
                if "north" in now_what:
                    cthulhu()
                elif "south" in now_what:
                    prince()
                elif "east" in now_what:
                    princess()
                elif "west" in now_what:
                    lion()
                else:
                    print "I got no idea what you're saying. Is it that hard picking a cardinal direction?" 
        else:
            print "I got no idea what you're saying. You have no choice but to enter the cave. Now let's start over"
            start()
            

start()

featured image source: http://xkcd.com/91/

One-Month-Old Blog

Anirudh Technical , , , ,

UPDATE: While I’m already half way through the much recommended book by Zed A. Shaw – Learn Python The Hard Way, I’m still doing my research on other great resources to help me get started with Python. This page listing 10 Python blogs worth following, in particular emphasizes Mouse vs python to be the most useful. Starting the 10th of June, I’ll be engaged on a 9-week-long MOOC on Computer Science using Python, offered by MIT.

It’s been 2 months since I got started with R, and although my progress seems fast to me, it appears so mainly because R comes with insanely helpful packages that reduce large chunks of code into simple functions. Not only that, data visualization and graphics generated in R are beautiful and elegant. For example, the following code generates a Mandelbrot set created through the first 50 iterations of equation z = z2 + c plotted for different complex constants c

library(caTools)         # external package providing write.gif function
jet.colors <- colorRampPalette(c("#00007F", "blue", "#007FFF", "cyan", "#7FFF7F",
                                 "yellow", "#FF7F00", "red", "#7F0000"))
m <- 1000                # define size
C <- complex( real=rep(seq(-1.8,0.6, length.out=m), each=m ),
              imag=rep(seq(-1.2,1.2, length.out=m), m ) )
C <- matrix(C,m,m)       # reshape as square matrix of complex numbers
Z <- 0                   # initialize Z to zero
X <- array(0, c(m,m,50)) # initialize output 3D array
for (k in 1:50) {        # loop with 50 iterations
  Z <- Z^2+C             # the central difference equation
  X[,,k] <- exp(-abs(Z)) # capture results
}
write.gif(X, "Mandelbrot.gif", col=jet.colors, delay=800)

Mandelbrot

This is just an illustration of the power of a dozen or so lines of R code. Just as there are a ridiculous many packages in R, there are countless modules packed into many thousands of packages in Python to make life simpler, so I wasn’t surprised to find a module called antigravity, that can be imported in Python like this:

 import antigravity

and voila, you are redirected to this telling XKCD tale of Cueball performing gravity-defying stunts with Python.

source: http://www.xkcd.com/353/