JohnnyonFlame

import json
import pandas as pd
from pandas.io.json import json_normalize

with open('todojsontweet.json', 'r') as f:
    js = json.load(f)
    df = json_normalize(data=js, meta=[])

# Transform hashtag entities into a flat list
def jsfilter(fi):

gdsaxton

gdsaxton

#!/usr/bin/env python


"""
Social_Metrics_Tutorial_Script_User_Timeline_All_Pages.py - DOWNLOADS ALL AVAILABLE RECENT
TWEETS FROM 5 MLB ACCOUNTS INTO SQLITE DATABASE

BEFORE RUNNING THIS SCRIPT, YOU WILL NEED TO:
  1. HAVE ANACONDA PYTHON 2.7 INSTALLED
  2. HAVE CREATED CSV FILE (E.G., IN EXCEL) CONTAINING TWITTER HANDLES YOU 

macloo

#!/usr/bin/env python
# encoding: utf-8

"""
python 2.x
Scrape members from a Twitter list and then get their bios, locations, etc.
Based on 
https://github.com/lamthuyvo/social-media-data-scripts/blob/master/scripts/twitter_bio_info_compiler.py 
and 
https://github.com/kylemanna/social-utils/blob/master/twitter/list-follow.py 

dannguyen

Find out who Congress follows on Twitter using the command line

Part of a lesson for the Stanford Journalism Computational Methods in the Civic Sphere

This is a short tutorial on how to use command-line tools, including csvfix and t, the command-line Twitter interface, to access and parse data from the Sunlight Foundation and Twitter. The end goal of this exercise is to gather who everyone in Congress follows (friends, in the parlance of Twitter), and then count up the common friends to find out which Twitter accounts are most followed by members of Congress.

Here's a screenshot of the result, after it's been imported into [Google Spreadsheets](https://docs.google.com/spreadsheets/d/1cjRJyrPYj8KAhUrot8ubPOWgbAwm0OqIgPtsswJ2sjM/edit#gid=1358907576