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#List unique values in a DataFrame column
pd.unique(df.column_name.ravel())

#Convert Series datatype to numeric, getting rid of any non-numeric values
df['col'] = df['col'].astype(str).convert_objects(convert_numeric=True)

#Grab DataFrame rows where column has certain values
valuelist = ['value1', 'value2', 'value3']
df = df[df.column.isin(value_list)]

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# Note – this is not a bash script (some of the steps require reboot)
# I named it .sh just so Github does correct syntax highlighting.
#
# This is also available as an AMI in us-east-1 (virginia): ami-cf5028a5
#
# The CUDA part is mostly based on this excellent blog post:
# http://tleyden.github.io/blog/2014/10/25/cuda-6-dot-5-on-aws-gpu-instance-running-ubuntu-14-dot-04/

# Install various packages
sudo apt-get update

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/* Delete the tables if they already exist */
drop table if exists Highschooler;
drop table if exists Friend;
drop table if exists Likes;

/* Create the schema for our tables */
create table Highschooler(ID int, name text, grade int);
create table Friend(ID1 int, ID2 int);
create table Likes(ID1 int, ID2 int);

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/* Delete the tables if they already exist */
drop table if exists Movie;
drop table if exists Reviewer;
drop table if exists Rating;

/* Create the schema for our tables */
create table Movie(mID int, title text, year int, director text);
create table Reviewer(rID int, name text);
create table Rating(rID int, mID int, stars int, ratingDate date);

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// Use Gists to store code you would like to remember later on
console.log(window); // log the "window" object to the console

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# original example from Digg Data website (Takashi J. OZAKI, Ph. D.) 
# http://diggdata.in/post/58333540883/k-fold-cross-validation-in-r


library(plyr)
library(randomForest)

data <- iris

# in this cross validation example, we use the iris data set to