Glue is a project I've been working on to interactively visualize multidimensional datasets in Python. The goal of Glue is to make trivially easy to identify features and trends in data, to inform followup analysis. This notebook shows an example of using Glue to explore crime statistics collected by the FBI (see this notebook for the scraping code). Because Glue is an interactive tool, I've inclu
Welcome to Plotly's Python API User Guide. The User Guide is entirely written inside IPython notebooks. Big thanks to Cam Davidson-Pilon and Lorena A. Barba for notebook styling ideas. The Github repository is divided into folders, one for each section or appendix. Each folder contains one or several IPython notebooks and the required data files to run them. The User Guide's homepage Section 0: Ge
USGS dataset listing every wind turbine in the United States: from collections import OrderedDict import bearcart import bokeh import bokeh.plotting as bp from bokeh.plotting import output_notebook import folium import ggplot as gg from ggplot import ggplot from IPython.html.widgets import interact import matplotlib.pyplot as plt import mpld3 import numpy as np import pandas as pd import vincent %
プログラマーのための確率プログラミングとベイズ推定¶PythonとPyMCの使い方¶ベイズ推定(Bayesian method)は,確率推論のためのもっとも適切なアプローチであるにもかかわらず,書籍を読むとページ数も数式も多いので,あまり積極的に読もうとする読者は少ないのが現状である.典型的なベイズ推定の教科書では,最初の3章を使って確率の理論を説明し,それからベイズ推論とは何かを説明する.残念ながら多くのベイズモデルは解析的に解くことが困難であるため,読者が目にするのは簡単で人工的な例題ばかりになってしまう.そのため,ベイス推論と聞いても「だから何?」と思ってしまうのである.実際,著者の私がそう思っていたのだから. 最近の機械学習のコンテストで良い成績を収めることができたので,私はこのトピックを復習しようと思い立った. 私は数学には強い方である.しかしそれでも,例題や説明を読んで頭の中で
# Boring preliminaries %pylab inline import re import math import string from collections import Counter from __future__ import division Statistical Natural Language Processing in Python. or How To Do Things With Words. And Counters. or Everything I Needed to Know About NLP I learned From Sesame Street. Except Kneser-Ney Smoothing. The Count Didn't Cover That. *One, two, three, ah, ah, ah!* — The
This is a simulation of an economic marketplace in which there is a population of actors, each of which has a level of wealth. On each time step two actors (chosen by an interaction function) engage in a transaction that exchanges wealth between them (according to a transaction function). The idea is to understand the evolution of the population's wealth over time. I heard about the problem when I
xkcd 1313: Regex Golf¶Peter Norvig January 2014 revised November 2015 I ♡ xkcd! It reliably provides top-rate insights, humor, or both. I was thrilled when I got to introduce Randall Monroe for a talk in 2007. But in xkcd #1313, I found that the hover text, "/bu|[rn]t|[coy]e|[mtg]a|j|iso|n[hl]|[ae]d|lev|sh|[lnd]i|[po]o|ls/ matches the last names of elected US presidents but not their opponents", c
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