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Air pollution USA

Wednesday, December 10, 2014

##We will be looking at the pollution of the air in the USA

Data are extracted from http://www.epa.go.

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EDA analysis

Marc Ferradou
Wednesday, November 26, 2014

##Data Sets

The data set consist of 6 csv files:

• episode_country.csv => association between country id and country name
• episode_region.csv => association between region id and region name (Europe...)

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%Marc Ferradou
%v0.0.1
%Licence: WTFPL 
%Date: 3/16/14
%This code is an answer to the BNP codehunter challenge. It tooks me about 2 hours and I picked Matlab for its simplicity to do the job.
%As easy as this code looks, I was actually one of the 20 winners. As we say, KIS.
%Read more here: https://graduates.bnpparibas.com/codehunter/crack-the-challenge/
%Result: this is a 29x29 transformation of a london (I believe) landscape
%with 3 Easter eggs.
%Note: I choosed matlab because it was in my opinion the quickest (in term

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##Introduction The question is: Tell us something interesting about the ping backs we receive from videos. Input:

• Question asked before
• tsv data file
• pdf file with data format Output:
• This document

I picked R in order to do this analysis as it did appears to me that this is mainly an exploratory data analysis and R markdown + ggplot2 are very conveniant for that in my opinion.

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There are multiple questions:

1. The operating regions are indicated by region_id. Generate a report of the average hourly_charge in each operating region as well as the overall average.

2. Assuming that a booking is completed if it is not cancelled by the customer and has no reschedule events, generate a report based on the calendar week (running Sun-Sat) of the number of bookings done, number of bookings done using coupons, total hours booked, and number of bookings which were cancelled by the customer.

3. Recurring bookings are bookings which happen on a regularly scheduled basis and are indicated by recurring_id and a frequency (freq) indicating how many weeks pass between each booking in the series. Determine the distribution of bookings based on the frequency of the recurring booking to which they belong across the days of the week on which they were completed.

4. Say we have a problem with customers canceling and rescheduling bookings. Assuming all the bookings are from different users, pull metric

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Playing with facebook

Tuesday, December 09, 2014

library(knitr)
opts_knit$set(upload.fun = imgur_upload, base.url = NULL) # upload all images to imgur.com

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d3 = function() {
  var d3 = {
    version: "3.2.7"
  };
  if (!Date.now) Date.now = function() {
    return +new Date();
  };
  var d3_document = document, d3_documentElement = d3_document.documentElement, d3_window = window;
  try {
    d3_document.createElement("div").style.setProperty("opacity", 0, "");

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d3 = function() {
  var d3 = {
    version: "3.2.7"
  };
  if (!Date.now) Date.now = function() {
    return +new Date();
  };
  var d3_document = document, d3_documentElement = d3_document.documentElement, d3_window = window;
  try {
    d3_document.createElement("div").style.setProperty("opacity", 0, "");