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micaleel / install-mongodb.md
Last active August 29, 2015 14:25 — forked from adamgibbons/install-mongodb.md
Install MongoDB on Mac OS X 10.9

Install MongoDB with Homebrew

brew install mongodb
mkdir -p /data/db

Set permissions for the data directory

Ensure that user account running mongod has correct permissions for the directory:

from collections import namedtuple
def convert(dictionary):
return namedtuple('GenericDict', dictionary.keys())(**dictionary)
"""
>>> d = dictionary(a=1, b='b', c=[3])
>>> named = convert(d)
>>> named.a == d.a
True
>>> named.b == d.b
#!/usr/bin/env python
from pocket import Pocket
import webbrowser, sys
# Get consumer key from cmd line
consumer_key = sys.argv[1]
request_token = Pocket.get_request_token(
consumer_key=consumer_key,
# pylint: disable=W0612
import time
import pandas as pd
import numpy as np
import iopro
import gc
import pandas as pd
import numpy as np
from datetime import datetime
# generate some fake tick data with 1 million observations
n = 1000000
df = pd.DataFrame({
"timestamp": [datetime.now() for t in range(n)],
"value": np.random.uniform(-1, 1, n)
})
from dateutil.parser import parse
import pandas as pd
# monthly slaughter records since 1921
df = pd.read_csv("http://bit.ly/119792b")
# parse the data (we could also use pd.to_datetime)
df.date = df.date.apply(parse)
# sort the data frame by date
df = df.sort(['date'])
# create an index
// Word cloud layout by Jason Davies, http://www.jasondavies.com/word-cloud/
// Algorithm due to Jonathan Feinberg, http://static.mrfeinberg.com/bv_ch03.pdf
(function(exports) {
function cloud() {
var size = [256, 256],
text = cloudText,
font = cloudFont,
fontSize = cloudFontSize,
rotate = cloudRotate,
padding = cloudPadding,
@micaleel
micaleel / example1.py
Last active August 29, 2015 14:19 — forked from onyxfish/example1.py
import nltk
with open('sample.txt', 'r') as f:
sample = f.read()
sentences = nltk.sent_tokenize(sample)
tokenized_sentences = [nltk.word_tokenize(sentence) for sentence in sentences]
tagged_sentences = [nltk.pos_tag(sentence) for sentence in tokenized_sentences]
chunked_sentences = nltk.batch_ne_chunk(tagged_sentences, binary=True)
#!/usr/bin/env python
from pocket import Pocket
import webbrowser, sys
# Get consumer key from cmd line
consumer_key = sys.argv[1]
request_token = Pocket.get_request_token(
consumer_key=consumer_key,
"""
Usage: python remove_output.py notebook.ipynb [ > without_output.ipynb ]
Modified from remove_output by Minrk
"""
import sys
import io
import os
from IPython.nbformat.current import read, write