johnjosephhorton

# accept time would be seconds from the unix epoch
results$rank <- mapply(
                       function(time,worker_id){
                         which(time==sort(subset(results, WorkerId==worker_id)$accept_time))
                       }, results$accept_time, results$WorkerId)

johnjosephhorton

# keys and values map 1:1
# e.g., 
keys <- c(1,2,3)
values <- c('a','b','c')
list_of_keys <- c(1,2,3,1,1,2)
letters <- sapply(list_of_keys, function(x){values[which(x==keys)]})

johnjosephhorton

unix2POSIXct  <-  function (time)   structure(time, class = c("POSIXt", "POSIXct"))

johnjosephhorton

import urllib2
import csv

FIRST_LINE = 11
LAST_LINE = 38

def get_level(l):
    for i, char in enumerate(l):
        if char != " ":
            break

johnjosephhorton

def f(x):
    return x**2

johnjosephhorton

library(lme4)
library(ggplot2)
library(XML)

# grab the NFL data & compute the score difference (Home - Away) 
nfl.raw <- read.csv("http://www.repole.com/sun4cast/stats/nfl2011stats.csv")
nfl.raw$delta <- with(nfl.raw, (ScoreOff - ScoreDef))

# fit the model 
m <- lmer(delta ~ (1 | TeamName) + (1|Opponent), data = nfl.raw)

johnjosephhorton

df$s.star <- with(df, log(-c/log(1-q))/log(1-q))
df$s.star[df$s.star < 0] <- 0
g.optimal <- ggplot(df, aes(x = q, y = s.star, colour=factor(c))) + geom_line(aes(group=factor(c))) +
  xlab("Probability that an application is successful") +
  ylab("Optimal number of applications to send")

png("optimal_apps.png")
 print(g.optimal)
dev.off()

johnjosephhorton

import networkx as nx 
import matplotlib.pyplot as plt

relationships = {
'cats':['cute', 'clean', 'curious', 'lazy'],
'children':['cruel', 'happy', 'mean', 'stupid'], 
'cows':['fat', 'sacred to hindus', 'stupid', 'sacred'],
'dogs':['loyal', 'cute', 'loving', 'happy'],
'frogs':['happy', 'slimy', 'important', 'sensitive to pollution'], 
'goldfish':['dirty', 'good', 'addicting', 'hard to keep alive'], 

johnjosephhorton

(add-to-list 'load-path "~/.emacs.d/")

(add-to-list 'load-path (expand-file-name "~/elisp/org-mode/lisp"))
(add-to-list 'auto-mode-alist '("\\.\\(org\\  |org_archive\\|txt\\)$" . org-mode))
(setq org-agenda-files '("/tmp/test.org"))
(require 'org-install)
(require 'org-habit)

(global-set-key "\C-cl" 'org-store-link)
(global-set-key "\C-ca" 'org-agenda)

johnjosephhorton

library(ggplot2)
library(sqldf)
# using the dataset 'raw' wich is a list of contractors by lat, long
df <- sqldf("SELECT COUNT(*) AS num, LocLat, LocLong 
             FROM raw GROUP BY LocLat, LocLong")
g <- qplot(LocLong,LocLat, colour=num, size=log(num), data = df)
png("india.png")
print(g)
dev.off()