I finally got around to finishing up this tutorial on how to use pandas DataFrames and SciPy together to handle any and all of your statistical needs in Python. This is basically an amalgamation of my two previous blog posts on pandas and SciPy.
A piece from Grist points out that major TV networks spent just 50 minutes on climate change—combined—in 2016. We’ve asked a few of our journalist-authors what kind of responsibility the media has to report on climate change topics. Does this lack of coverage happen because there isn't a compelling news story or narrative? Check out what John Fleck, Dan Fagin, and Randy Olson have to say about it below.
The success of a marriage is a multifaceted monster that’s difficult to predict. Nearly a decade ago, the nation was shocked to find half of all total U.S. marriages ended in divorce, and finding the key to the perfect marriage came to the forefront of society. Data scientist Randy Olson was one of those curious individuals who set out to uncover and break down all of the marriage factors.
@ThisIsFrag When it comes down to it, human expert time is far more expensive than compute time. And recent advances (e.g. Google AutoML project you mentioned in your podcast) have shown that automated methods also do a better job.
Muck Rack makes it simple to find people, tweets, or articles that mention any name, keyword, company, hashtag etc. We've compiled this guide to help you make the most of your search.
Selecting a term
Start searching tweets, articles from media outlets, articles mentioned in tweets, journalists'
names, titles and bios with some suggested searches:
Companies or Topics (e.g. iPhone, Microsoft)
Phrases (e.g. "cloud computing") — use quotes to keep the terms together
Twitter handles (e.g. @username) — returns those who have mentioned or replied to
Names (e.g. "David Pogue")
Hashtags (e.g. #sxsw, #london2012)
Bio details (e.g. vegan, Olympics, father)
Muck Rack's Advanced Search allows for many boolean operators.
Find results that mention multiple specified terms, use AND or
+. For example, ensure each result contains both Elon Musk and Mark Zuckerberg by
searching Musk AND Zuckerberg or Musk + Zuckerberg.
Use the operators OR or , to broaden your search when you'd like either of
multiple terms to appear in results. (This is the default behavior of our search when no operators
are used). For example, results will contain either cake or cookie by searching cake OR cookie or cake,cookie
Use NOT or - to subtract results from your search. For
example, searching Disney will yield results about the Walt Disney Company as well as Walt Disney
World Resort. To exclude mentions of Disney World, search for Disney -World or Disney
When using one of these operators with a phrase, enclose it in quotation marks. For example, you can
find results about smartphones excluding Apple's iPhone 4S by searching smartphone -"iPhone
Exact case matching or punctuation
If you're searching for a brand name or keyword that relies on specific punctuation marks or capitalization, you can
find results that match your exact query by adding matchcase: before the keyword you're searching for, like matchcase:E*TRADE .
Use parentheses to separate multiple
boolean phrases. For example, to find journalists talking about having fun in Disney World or
Disneyland, search for ("disney world" OR disneyland) AND fun.
An asterisk can be used to search for any variation of a root word truncated by the asterisk. For example, searching for admin* will return results for administrator, administration, administer, administered, etc.
A near operator is an AND operator where you can control the distance between the words. You can vary the distance the near operation uses by adding a forward slash and number (between 0-99) such as strawberries NEAR/10 "whipped cream", which means the strawberries must exist within 10 words of "whipped cream".