micaleel

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

micaleel

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)
    })

micaleel

# pylint: disable=W0612

import time

import pandas as pd
import numpy as np
import iopro

import gc

micaleel

#!/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,

micaleel

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

micaleel

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:

micaleel

Stacked and Grouped Bar Plot

Oddly enough ggplot2 has no support for a stacked and grouped (position="dodge") bar plot. The seaborn python package, although excellent, also does not provide an alternative. However, I knew it was surely possible to make such a plot in regular matplotlib. Matplotlib, although sometimes clunky, gives you enough flexibility to precisely place plotting elements which is needed for a stacked and grouped bar plot.

Below is a working example of making a stacked and grouped bar plot.

import seaborn as sns
import matplotlib.pyplot as plt
import numpy as np

micaleel

# Path to your oh-my-zsh configuration.
export ZSH=$HOME/.oh-my-zsh

# Set name of the theme to load.
# Look in ~/.oh-my-zsh/themes/
# Optionally, if you set this to "random", it'll load a random theme each
# time that oh-my-zsh is loaded.
#export ZSH_THEME="robbyrussell"
export ZSH_THEME="zanshin"

micaleel

#!/usr/bin/env python
"""strip outputs from an IPython Notebook

Opens a notebook, strips its output, and writes the outputless version to the original file.

Useful mainly as a git filter or pre-commit hook for users who don't want to track output in VCS.

This does mostly the same thing as the `Clear All Output` command in the notebook UI.

LICENSE: Public Domain

micaleel

import pandas as pd
# http://blog.yhathq.com/static/misc/data/WineKMC.xlsx
df_offers = pd.read_excel("./WineKMC.xlsx", sheetname=0)
df_offers.columns = ["offer_id", "campaign", "varietal", "min_qty", "discount", "origin", "past_peak"]
df_offers.head()

df_transactions = pd.read_excel("./WineKMC.xlsx", sheetname=1)
df_transactions.columns = ["customer_name", "offer_id"]
df_transactions['n'] = 1
df_transactions.head()