| # -*- coding: utf-8 -*- | |
| import re | |
| from scrapy.item import Item, Field | |
| from scrapy.contrib.spiders import CrawlSpider, Rule | |
| from scrapy.contrib.linkextractors.sgml import SgmlLinkExtractor | |
| from scrapy.selector import HtmlXPathSelector | |
| from lxml.cssselect import css_to_xpath |
This line chart is constructed from a TSV file storing the daily average temperatures of New York, San Francisco and Austin over the last year. The chart employs conventional margins and a number of D3 features:
| GENERATED_FILES = \ | |
| unemployment.tsv | |
| .PHONY: all clean | |
| all: $(GENERATED_FILES) | |
| clean: | |
| rm -rf -- $(GENERATED_FILES) |
| from Queue import Queue | |
| from threading import Thread, active_count | |
| import pytumblr | |
| import sys | |
| import time | |
| import logging | |
| client = pytumblr.TumblrRestClient( | |
| 'FILLINYOUROWNDAMNVALUES', | |
| 'FILLINYOUROWNDAMNVALUES', |
| $ pagoda . | |
| /Library/Ruby/Site/1.8/rubygems/core_ext/kernel_require.rb:45:in `gem_original_require': /Library/Ruby/Gems/1.8/gems/pagoda-jekyll-0.0.9/bin/../lib/pagoda/app.rb:39: syntax error, unexpected tIDENTIFIER, expecting tAMPER (SyntaxError) | |
| ...source, *%w[_posts], post_file) | |
| ^ | |
| /Library/Ruby/Gems/1.8/gems/pagoda-jekyll-0.0.9/bin/../lib/pagoda/app.rb:146: syntax error, unexpected tIDENTIFIER, expecting tAMPER | |
| repo.add File.join(jekyll_site.source, *%w[_posts], filename) | |
| ^ | |
| from /Library/Ruby/Site/1.8/rubygems/core_ext/kernel_require.rb:45:in `require' | |
| from /Library/Ruby/Gems/1.8/gems/pagoda-jekyll-0.0.9/bin/pagoda:20 | |
| from /usr/bin/pagoda:23:in `load' |
| import matplotlib.pyplot as plt | |
| from datetime import datetime, timedelta | |
| import numpy as np | |
| from math import log | |
| import tweepy | |
| import collections | |
| import bisect | |
| DATE_FORMAT = "%Y-%m-%d %H:%M:%S" | |
| INTERVAL = timedelta(hours = 1) |
| import requests | |
| import operator | |
| companies = ["hubspot"] | |
| api_url = "https://api.github.com/orgs/{}/repos" | |
| data = {} | |
| for company in companies: | |
| data[company] = {'forks': 0, 'stars': 0, 'repos': 0, 'languages': {}} | |
| r = requests.get(api_url.format(company)) |
| SetID,Number,Variant,Theme,SubTheme,Year,SetName,Minifigs,Pieces,UKPrice,USPrice,CAPrice,Image,ImageFilename,InstructionsAvailable,EAN,UPC | |
| 22696,"00","5","Samsonite","Model Maker","1969","Life Cereal Puppet Set",,88,,1,,"False","","False","","" | |
| 7326,"102A","1","LEGOLAND","Construction","1970","Front-End Loader",,57,,,,"True","102A-1","False","","" | |
| 7455,"442A","1","Classic","Accessories","1971","International Flags",,6,,,,"False","","False","","" | |
| 1232,"670F","1","Racers","Radio-Control","2004","Wheels Pack",,10,,,,"True","670F-1","False","","" | |
| 1,"671F","1","Racers","Radio-Control","2004","Antenna Pack",,13,,,,"True","671F-1","False","","" | |
| 4690,"673F","1","Racers","Radio-Control","2004","Gearbox Pack",,6,,,,"True","673F-1","False","","" | |
| 9434,"973PB507C01","1","Promotional","Minifigure","2009","LEGO World Denmark 2009 Minifigure",,4,,,,"False","","False","","" | |
| 9780,"ALPHARETTA","1","Promotional","LEGO Store Grand Opening Set","2012","Alpharetta Exclusive Minifigure Pack",3,15,,0,,"True","ALPHARETTA-1","False","" |
| <!DOCTYPE html> | |
| <head> | |
| <link rel="stylesheet" href="http://cdn.leafletjs.com/leaflet-0.7/leaflet.css" /> | |
| <link rel="stylesheet" href="http://leaflet.github.io/Leaflet.markercluster/dist/MarkerCluster.Default.css" /> | |
| <script src="http://cdn.leafletjs.com/leaflet-0.7/leaflet.js"></script> | |
| <script src="http://leaflet.github.io/Leaflet.markercluster/dist/leaflet.markercluster-src.js" type='text/javascript'></script> | |
| <script src="http://briangonzalez.github.io/jquery.adaptive-backgrounds.js/js/jquery.js"></script> | |
| <style> |
| import matplotlib | |
| import matplotlib.pyplot as plt | |
| import numpy as np | |
| import pandas as pd | |
| import vincent | |
| # source: http://www.pro-football-reference.com/boxscores/game_scores.cgi | |
| SOURCE_FILE = "./nflscores.csv" | |
| data = pd.read_csv(SOURCE_FILE, header=0) |
