from crunch import crunch_data crunched_data, week, year = crunch_data(weeks=4, on="week", name_threshold=500, dropNaNs=False) print crunched_data data = {} for index, row in crunched_data.iterrows(): data[index] = {#'color': plt.cm.get_cmap('spring')(row.values[0]), 'color': '#000000', 'percent': int(row.values[-2]*100), 'deviation': abs(50 - int(row.values[-2]*100))} from circlegraph import make_figure filename = make_figure(data, text="vecka {}".format(week), year=year, font="Latin Modern Mono") twitter_handles = {'dn.se': '@Dagensnyheter', 'expressen.se': '@Expressen', 'svd.se': '@SvD', 'etc.se': '@ETC_redaktionen', 'svt.se': '@SVT', 'aftonbladet.se': '@Aftonbladet', 'di.se': '@dagensindustri'} # Get best and worst best = sorted(data.iteritems(), key=lambda e: e[1]['deviation'])[0][0] best_percent = sorted(data.iteritems(), key=lambda e: e[1]['deviation'])[0][1]['percent'] worst = sorted(data.iteritems(), key=lambda e: e[1]['deviation'])[-1][0] worst_percent = sorted(data.iteritems(), key=lambda e: e[1]['deviation'])[-1][1]['percent'] tweet_to_worst = 'Vecka {week} hade {worst} {worst_percent} % kvinnor i sina texter och var därmed sämst denna vecka. Bäst var {best} med {best_percent} %.'.format(week=week, worst=twitter_handles[worst], worst_percent=worst_percent, best=twitter_handles[best], best_percent=best_percent) print tweet_to_worst assert len(tweet_to_worst) < 140
auth = tweepy.OAuthHandler(conf.consumer_key, conf.consumer_secret) auth.set_access_token(conf.access_token, conf.access_token_secret) api = tweepy.API(auth) from crunch import crunch_data crunched_data, week, year = crunch_data() data = {} for index, row in crunched_data.iterrows(): data[index] = {#'color': plt.cm.get_cmap('spring')(row.values[0]), 'color': '#000000', 'percent': int(row.values[0]*100), 'deviation': abs(50 - int(row.values[0]*100))} from circlegraph import make_figure filename = make_figure(data, week=week, year=year, font="Latin Modern Mono") twitter_handles = {'dn.se': '@Dagensnyheter', 'expressen.se': '@Expressen', 'svd.se': '@SvD', 'etc.se': '@ETC_redaktionen', 'svt.se': '@SVT', 'aftonbladet.se': '@Aftonbladet'} # Get best and worst best = sorted(data.iteritems(), key=lambda e: e[1]['deviation'])[0][0] best_percent = sorted(data.iteritems(), key=lambda e: e[1]['deviation'])[0][1]['percent'] worst = sorted(data.iteritems(), key=lambda e: e[1]['deviation'])[-1][0] worst_percent = sorted(data.iteritems(), key=lambda e: e[1]['deviation'])[-1][1]['percent'] tweet_to_worst = 'Vecka {week} hade {worst} {worst_percent} % kvinnor i sina texter och var därmed sämst denna vecka. Bäst var {best} med {best_percent} %.'.format(week=week, worst=twitter_handles[worst], worst_percent=worst_percent, best=twitter_handles[best], best_percent=best_percent) print tweet_to_worst assert len(tweet_to_worst) < 140
# -*- coding: utf-8 -*- import tweepy import config as conf import datetime """ Make graph of the last month """ from crunch import crunch_data crunched_data, week, year = crunch_data(weeks=10, on="month") crunched_data = crunched_data.dropna(axis=0) print crunched_data data = {} for index, row in crunched_data.iterrows(): data[index] = {'color': '#000000', 'percent': int(row.values[-2]*100), 'deviation': abs(50 - int(row.values[-2]*100))} monthnames = {1: 'Januari', 2: 'Februari', 3: 'Mars', 4: 'April', 5: 'Maj', 6:'Juni', 7: 'Juli', 8: 'Augusti', 9: 'September', 10: 'Oktober', 11: 'November', 12: 'December'} from circlegraph import make_figure filename = make_figure(data, text=monthnames[crunched_data.columns[-2]], year=year, font="Latin Modern Mono", filename="graphs/monthly.png") print "Genereated file: {}".format(filename)