mblondel

import numpy as np

rng = np.random.RandomState(0)

print "Trace"
A = rng.rand(3, 3)
print np.trace(A)
print np.einsum("ii", A)
print

akras14

Git Cheat Sheet

Commands

Getting Started

git init

or

bsweger

Useful Pandas Snippets

A personal diary of DataFrame munging over the years.

Data Types and Conversion

Convert Series datatype to numeric (will error if column has non-numeric values)
(h/t @makmanalp)

sumardi

# New repository
mkdir <repo> && cd <repo>
git init
git remote add –f <name> <url>
git config core.sparsecheckout true
echo some/dir/ >> .git/info/sparse-checkout
echo another/sub/tree >> .git/info/sparse-checkout
git pull <remote> <branch>

# Existing repository

tobigue

import os
import random
import string
from subprocess import call

import numpy as np

from sklearn.base import BaseEstimator, ClassifierMixin
from sklearn.datasets import dump_svmlight_file

fabianp

"""
Implementation of pairwise ranking using scikit-learn LinearSVC

Reference: 

    "Large Margin Rank Boundaries for Ordinal Regression", R. Herbrich,
    T. Graepel, K. Obermayer 1999

    "Learning to rank from medical imaging data." Pedregosa, Fabian, et al., 
    Machine Learning in Medical Imaging 2012.

mblondel

# Copyright Mathieu Blondel December 2011
# License: BSD 3 clause

import numpy as np
import pylab as pl

from sklearn.base import BaseEstimator
from sklearn.utils import check_random_state
from sklearn.cluster import MiniBatchKMeans
from sklearn.cluster import KMeans as KMeansGood