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Sean J. Taylor seanjtaylor

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seanjtaylor / gist:2865517
Created June 4, 2012 00:05
Most Frequent Integer 1-Grams from Google N-Grams
(py27)sean@leibniz:/media/datasets/n-grams/data/1gms$ zgrep "^[0-9]\+\s" vocab.gz | sort -n -r -k 2 | head -n 100
1 2563166795
2 1846241630
0 1834474671
3 1304070731
2005 1091295264
4 1045739277
5 915581712
10 698337921
6 692314831
@seanjtaylor
seanjtaylor / gist:5498002
Created May 1, 2013 20:14
WTH
taylorphd-pc:julia sjt$ rm -rf ~/.julia
staylorphd-pc:julia sjt$ bin/julia
_
_ _ _(_)_ | A fresh approach to technical computing
(_) | (_) (_) | Documentation: http://docs.julialang.org
_ _ _| |_ __ _ | Type "help()" to list help topics
| | | | | | |/ _` | |
| | |_| | | | (_| | | Version 0.1.2+111718311.r1187
_/ |\__'_|_|_|\__'_| | Commit 1187040d02 (2013-03-08 10:00:57)
|__/ |
@seanjtaylor
seanjtaylor / _.md
Created July 29, 2013 21:01
creds
@seanjtaylor
seanjtaylor / index.html
Last active December 23, 2015 07:59
Creds Viz take 2
<html>
<head>
<style>
rect.background {
fill: #EEE;
}
line.rule {
stroke: #FFF;
}
text.labels {
@seanjtaylor
seanjtaylor / weather_data.R
Created January 24, 2015 17:16
library(mgcv)
library(ggplot2)
library(dplyr)
library(XML)
library(weatherData)
us.airports.url <- 'http://www.world-airport-codes.com/us-top-40-airports.html'
us.airports <- readHTMLTable(us.airports.url)[[1]] %>%
filter(!is.na(IATA)) %>%
@seanjtaylor
seanjtaylor / gist:568141f04a16d518be24
Created February 11, 2015 01:46
Reshaping a Pandas dataframe into a sparse matrix
import pandas as pd
import scipy.sparse as sps
df = pd.DataFrame({'tag1': ['sean', 'udi', 'bogdan'], 'tag2': ['sean', 'udi', 'udi'], 'freq': [1,2,3]})
# tag1 -> rows, tag2 -> columns
df.set_index(['tag1', 'tag2'], inplace=True)
mat = sps.coo_matrix((df.freq, (df.index.labels[0], df.index.labels[1])))
print(mat.todense())
@seanjtaylor
seanjtaylor / btl_example.R
Last active August 29, 2015 14:25
How to estimate a BTL model in R.
df <- data.frame(higher = c('US', 'CA', 'MX'),
lower = c('CA', 'MX', 'MX'))
levels <- c('US', 'CA', 'MX')
X.l <- model.matrix(~ 0 + factor(higher, levels = levels), data = df)
X.r <- model.matrix(~ 0 + factor(lower, levels = levels), data = df)
X <- X.l - X.r
colnames(X) <- levels # makes it easier to interpret regression output
@seanjtaylor
seanjtaylor / nfl_officials_analysis.R
Created June 15, 2016 16:04
Quick analysis of NFL Officials
library(rvest)
library(stringr)
library(readr)
library(ggplot2)
library(dplyr)
library(tidyr)
library(broom)
library(lubridate)
base.url <- 'http://www.pro-football-reference.com/'
@seanjtaylor
seanjtaylor / gamling_odds_implied_wins.R
Created September 8, 2016 15:26
Analysis of Season Win O/Us
library(rvest)
library(stringr)
library(dplyr)
library(ggplot2)
library(tidyr)
min.fun <- function(p, thresh.prob = NULL, thresh = NULL) {
(thresh.prob - pbinom(thresh, 16, p))^2
}
@seanjtaylor
seanjtaylor / air_yards_plot.R
Created October 1, 2016 21:03
Plotting Air Yards Auto-correlation
library(dplyr)
library(ggplot2)
library(rvest)
library(tidyr)
html.doc <- read_html('http://www.footballoutsiders.com/stat-analysis/2016/quarterbacks-and-progression-air-yards')
# Extract table
raw.table <- html.doc %>%
html_table() %>%