rsivapr

[
  {
    "date":"1-May-12",
    "close":58.13
  },
  {
    "date":"30-Apr-12",
    "close":53.98
  },
  {

rsivapr

#!/usr/bin/env python

import sys
import csv

def MeanAveragePrecision(valid_filename, attempt_filename, at=10):
    at = int(at)
    valid = dict()
    for line in csv.DictReader(open(valid_filename,'r')):
        valid.setdefault(line['source_node'],set()).update(line['destination_nodes'].split(" "))

rsivapr

import csv

r = csv.reader(open('train.csv','r'))
r.next()

edges = set()
#commutative_graph = dict()
for edge in r:
    edges.add((edge[0], edge[1]))
#    commutative_graph.setdefault(edge[0], set()).add(edge[1])

rsivapr

gameGrid = function(gridSize) {
    var i;
    window.a = [];
    this.size = gridSize;
    this.map = [];
    for (i = 0; i < this.size; i++) {
        this.map[i] = [];
    }
};

rsivapr

import pandas as pd
import statsmodels.api as sm
import pylab as pl
import numpy as np
import sklearn.metrics

print "Reading DATA.CSV ... \n"
df = pd.read_csv('data.csv')
df.columns = ["numb", "age","frailty","sex","val"]
for i in range(df.shape[0]):

rsivapr

import numpy as np
from datetime import date
claimsdata = np.genfromtxt('claims.csv', dtype = (int, object, object, int, object), delimiter=',', names = True)
poldata = np.genfromtxt('policies.csv', dtype = (int, object, object, object, object), delimiter=',', names = True)
f = open('categories')
f.readline()
dict1 = {}
for i in f.readlines():
    colorVal = i.split(',')
    colorVal[1]=colorVal[1][:-1]

rsivapr

What

Roll your own iPython Notebook server with Amazon Web Services (EC2) using their Free Tier.

What are we using? What do you need?

• An active AWS account. First time sign-ups are eligible for the free tier for a year
• One Micro Tier EC2 Instance
• With AWS we will use the stock Ubuntu Server AMI and customize it.
• Anaconda for Python.
• Coffee/Beer/Time

rsivapr

300,100006
300,100011
300,100012
300,100033
300,100044
300,100053
300,100059
300,100072
300,100104
300,100111

rsivapr

from selenium import webdriver
import getpass

driver = webdriver.Firefox()
driver.get('https://myaccount.lib.ncsu.edu/')

user = driver.find_element_by_name('user_idp')

for option in user.find_elements_by_tag_name('option'):
     if option.text == 'NC State Unity Users':

rsivapr

awk 'BEGIN { srand(systime()); } {if (rand() < 0.25) { print $0; } }' Train.csv > sampled_train.csv