rjweiss

---
title: "USE Survey Analysis"
author: "Rebecca Weiss"
date: "Tuesday, September 01, 2015"
output: html_document
---


```{r, echo=FALSE, warning=FALSE, results='hide', message=FALSE}
require("plyr")

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library(ggplot2)
library(stringr)
library(scales)
library(plyr)
library(car)

predictions = read.csv('job831_predictions.tsv', sep="\t") # the job file from etcml as is
metadata = read.csv('etcml_iarchive_0106_full.tsv', header=F, stringsAsFactors=F) # my metadata from the archive

# this is rather sloppy but i'm lazy

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{
 "metadata": {
  "name": "textanalysis.ipynb"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {

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{
 "metadata": {
  "name": "tfidf.ipynb"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {

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{
 "metadata": {
  "name": "regex_lecture.ipynb"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {

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{
 "metadata": {
  "name": "cleaningtext.ipynb"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {

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{
 "metadata": {
  "name": "fileformats_solutions.ipynb"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {

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{
 "metadata": {
  "name": "encoding_lecture.ipynb"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {

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{
 "metadata": {
  "name": "Python_sentiment.ipynb"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {

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{
 "metadata": {
  "name": "Python_classification.ipynb"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {