mkowoods

http://rgraphgallery.blogspot.com/

#Base graphic reference Guide
http://www.inside-r.org/r-doc/graphics/par


http://projecttemplate.net/index.html

http://alignedleft.com/tutorials/d3

mkowoods

import urllib
import json

"""
https://developers.google.com/maps/documentation/geocoding/
https://developers.google.com/maps/documentation/distancematrix/
"""
class GoogleMapsAPI(object):

    def __init__(self):

mkowoods

from Tkinter import *
import tkFileDialog

root = Tk()
root.withdraw()
inputfile = tkFileDialog.askopenfilename(initialdir = 'C:\\', title = "Select Quote File", filetypes = [('csv files', '.csv')])
print inputfile

import csv

mkowoods

#-------------------------------------------------------------------------------
# Name:        module1
# Purpose:
#
# Author:      mwoods
#
# Created:     05/11/2014
# Copyright:   (c) mwoods 2014
# Licence:     <your licence>
#-------------------------------------------------------------------------------

mkowoods

import os

SET_PATH = "E:\\"

os.chdir(SET_PATH)

results =  os.walk(SET_PATH)

mkowoods

https://github.com/blog/273-github-ribbons


<a href="https://github.com/you"><img style="position: absolute; top: 0; right: 0; border: 0;" src="https://camo.githubusercontent.com/652c5b9acfaddf3a9c326fa6bde407b87f7be0f4/68747470733a2f2f73332e616d617a6f6e6177732e636f6d2f6769746875622f726962626f6e732f666f726b6d655f72696768745f6f72616e67655f6666373630302e706e67" alt="Fork me on GitHub" data-canonical-src="https://s3.amazonaws.com/github/ribbons/forkme_right_orange_ff7600.png"></a>

mkowoods

def letter_frequency(text):
    wdct = {}
    for n in text:
        m = n.lower()
        if m.isalpha():
            wdct[m] = wdct.get(m, 0) + 1
    return sorted([(k,v) for k,v in wdct.iteritems()], key = lambda x : (-x[1], x[0]))


result = letter_frequency('IWT LDGAS XH HIXAA P LTXGS EAPRT, STHEXIT BN TUUDGIH ID BPZT RATPG PCS ETGUTRI HTCHT DU XI.')

mkowoods

# -*- coding: utf-8 -*-
"""
Created on Thu Nov 20 18:48:28 2014

@author: mwoods
code is based on textbelt by Ian Webster
https://github.com/typpo/textbelt/tree/master/lib
"""

mkowoods

n_col = 100
n_rows = 1000

set.seed(500)

rand.matrix <- matrix(data = rep(NA, n_rows*n_col), nrow = n_rows, ncol = n_col)
rand.class <-  rbinom(n = n_rows, size = 1, prob = 0.7)

#Assign some variables to be randomly relevant
for(i in 1:n_col){

mkowoods

#!/usr/bin/env python
# -*- coding: utf-8 -*-

import subprocess
import time

VERBOSE = False


def wait(seconds):