andrewflowers Goto Github PK

2014-03-17-nyu-r

R room for the NYU bootcamp

538model

538 Election Forecasting Model

andrewflowers.github.io

My personal website/blog

bokeh

Interactive Web Plotting for Python

bumped-flights

Which U.S. airlines are the worst at bumping passengers from flights?

chartbuilder

A front-end charting application that facilitates easy creation of simple beautiful charts

d3-book

Sample code files to accompany the book “Interactive Data Visualization for the Web”

data-analysis

Andrew's personal data analysis repo

dataanalysis

The lecture slides for Coursera's Data Analysis class

datagotham2013

doing_data_science

This is the example code repository for Doing Data Science by Cathy O'Neil and Rachel Schutt (O'Reilly Media)

draft-mistakes-in-r

Draft of book *How to make mistakes in R*

edtc-code

Code for Economic Dynamics, Theory and Computation

forecast

forecast package for R

futureofwalpole_rtm_map

A map of Walpole precincts and the RTMs representing them

ggplot

ggplot for python

gtd_2015

Global Terrorism Database 2015 update

healthineq

Health inequality data visualization project

how-to-make-mistakes-in-r

How To Make Mistakes in R

html2text

Convert HTML to Markdown-formatted text.

ideology

Mapping U.S. voters' shifting political ideologies

ipython

Official repository for IPython itself. Other repos in the IPython organization contain things like the website, documentation builds, etc.

legislator-scorecard

🗳️ Explore MA state representatives' voting records

lesswrong-bundle

PDF version of the LessWrong.com sequences

mass-stats

Know Your Town -- Updated Local Statistics and Information

mining-the-social-web-2nd-edition

The official online compendium for Mining the Social Web, 2nd Edition (O'Reilly, 2013)

mlb_pbp_data

MLB play-by-play data

new-york-msa-pop-matrix

An age by race by gender population matrix of the New York MSA

old-python-scripts

Old Python scripts

probabilistic-programming-and-bayesian-methods-for-hackers

aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)