soodoku

1 AL
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8 CO
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11 DC
12 FL

fredbenenson

layout	title	description	tags
default	SQL Style Guide	A guide to writing clean, clear, and consistent SQL.	data process

Purpose

carlislerainey

# load packages
library(magrittr)
library(googlesheets)
library(lubridate)
library(dplyr)
library(stringr)
library(tidyr)
library(ggplot2)
library(maps)

soodoku

bearloga

#' Manual classification of observations
#' 
#' \code{classify} launches a Shiny app to manually classify a subset of observations.
#'
#' @param x A character vector.
#' @param btn_labels A character vector of length 2 corresponding to 0 and 1.
#' @return A vector of 0/1 for each element in \code{x}.
#' @export
#' @examples \dontrun{
#'  foo <- sprintf('%s (%.2f miles per gallon)', rownames(mtcars), mtcars$mpg)

tslumley

redpeak=function(s,w){
x=c(0,0,1,NA, 1,2,2,NA,0.5,1,1.5)
y=c(0,1,1,NA,1,1,0,NA,0,0.5,0)
polygon(x*w+s[1],y*w+s[2],col=c("black","navyblue","#98332f"))
}

soodoku

apt-get upgrade
apt-get update
sudo aptitude install emacs24
sudo aptitude install r-base
sudo aptitude install libcurl4-openssl-dev
sudo aptitude install libxml2-dev

apt-get install openjdk-7-*
R CMD javareconf -e

soodoku

"
Weighting by Propensity Scores
Last Edited: 5/31/2015

Task Outline:
1. Two datasets:
	dataset 1: large pop. representative sample	
	dataset 2: convenient sample
2. Create weights for dataset 2 so that its marginals are close to dataset 1 on some vars.  

soodoku

"
Basic Text Classifier 		 
	- Takes a csv with a text column, and column of labels
	- Splits into train and test
	- Preprocesses text using tm/bag-of-words, 1/2-order Markov
	- Uses SVM and Lasso

@author: Gaurav Sood								 
 	
"

soodoku

'''
What does it do?
Goes through a corrupted csv sequentially and outputs rows that are clean. 
Also outputs, total n, total corrupted n
    
@author: Gaurav Sood
Run: python salvage_csv.py input_csv output_csv

'''