Brian Keegan brianckeegan

Note

Going to move development to this repo to make PRs easier to manage: https://github.com/brianckeegan/Post_2024_News

Post-2024 news

Mainstream media failed to hold Trump to account over the course of the 2024 presidential campaign through "view from nowhere" centrism and false equivalencies between both campaigns.

Here is a list of news organizations, newsletters, and writers that are audience-funded and/or non-profits committed to independent and investigative journalism.

Rules

No centrist contrarians or right-wing authors

	# Serrano, Boguna, Vespigani backbone extractor
	# from http://www.pnas.org/content/106/16/6483.abstract
	# Thanks to Michael Conover and Qian Zhang at Indiana with help on earlier versions
	# Thanks to Clay Davis for pointing out an error

	import networkx as nx
	import numpy as np

	def extract_backbone(g, weight='weight', alpha=.05):
	backbone_graph = nx.Graph()

	import pandas as pd
	import numpy as np
	import datetime

	dft = pd.DataFrame({'A' : ['spam', 'eggs', 'spam', 'eggs'] * 6,
	'B' : ['alpha', 'beta', 'gamma'] * 8,
	'C' : [np.random.choice(pd.date_range(datetime.datetime(2013,1,1),datetime.datetime(2013,1,3))) for i in range(24)],
	'D' : np.random.randn(24),
	'E' : np.random.random_integers(0,4,24)})

	# adapted from http://matplotlib.org/examples/api/barchart_demo.html
	def autolabel(rects):
	max_height = max([rect.get_height() for rect in rects if hasattr(rect,'get_height') and not np.isnan(rect.get_height())])
	for rect in rects:
	if hasattr(rect,'get_height'):
	height = rect.get_height()
	if not np.isnan(height):
	ax.text(rect.get_x()+rect.get_width()/2., height-.1*max_height, '%d'%int(height),
	ha='center', va='bottom',color='w')

	import numpy as np
	import pandas as pd
	from bs4 import BeautifulSoup, element
	import urllib2, re

	# Read the HTML from the webpage on Wikipedia stats and convert to soup
	soup = BeautifulSoup(urllib2.urlopen('http://stats.wikimedia.org/EN/TablesWikipediaEN.htm').read())

	# Look for all the paragraphs with 2014
	_p = soup.findAll('b',text=re.compile('2014'))

	from bs4 import BeautifulSoup
	import requests

	# Get the data
	raw = requests.get('http://www.baseball-reference.com/leagues/MLB/2016-standings.shtml').text

	# Parse it
	soup = BeautifulSoup(raw,'html.parser')

	# Find the table

	\begin{figure*}[!tb]
	\centering
	\footnotesize
	\begin{tabular}{cccc}

	% First row of triad census
	\begin{tikzpicture}
	[user/.style={circle,draw=black,fill=black!60,thick,text=white,inner sep=0pt,minimum size=.5cm},
	->,-stealth,line width = 2, black,
	font=\boldmath]