When /r/The_Donald disabled the downvoting button via CSS

Subreddit disabled comments on 2016-04-15, thread here

Data processing

BigQuery:

SELECT author, num_comments, score, ups, downs, gilded, created_utc FROM [fh-bigquery:reddit_posts.2016_04] 
WHERE subreddit = 'The_Donald'

https://storage.cloud.google.com/staeiou_reddit/reddit_posts_the_donald_201604



In [1]:

    
import pandas as pd
import seaborn as sns

%matplotlib inline



In [2]:

    
posts_df = pd.DataFrame.from_csv("reddit_posts_the_donald_201604.csv")



In [3]:

    
posts_df[0:5]









    Out[3]:






  
    
      
      num_comments
      score
      ups
      downs
      gilded
      created_utc
    
    
      author
      
      
      
      
      
      
    
  
  
    
      YaBoyyCuddle
      0
      13
      13
      0
      0
      1460422236
    
    
      blkrctngl
      2
      14
      14
      0
      0
      1461198429
    
    
      Monteg9210
      1
      23
      23
      0
      0
      1461198955
    
    
      wookee8
      10
      1
      1
      0
      0
      1460248572
    
    
      Voat_Donald_Trump
      10
      148
      148
      0
      0
      1459559899



In [4]:

    
posts_df['created'] = pd.to_datetime(posts_df.created_utc, unit='s')
posts_df['created_date'] = posts_df.created.dt.date



In [5]:

    
posts_df['downs'] = posts_df.score - posts_df.ups



In [6]:

    
posts_time_ups = posts_df.set_index('created_date').ups.sort_index()
posts_time_ups[0:5]









    Out[6]:





created_date
2016-04-01      0
2016-04-01      1
2016-04-01      5
2016-04-01    389
2016-04-01    304
Name: ups, dtype: int64



In [7]:

    
posts_date_df = posts_df.set_index('created').sort_index()

posts_date_df[0:5]









    Out[7]:






  
    
      
      num_comments
      score
      ups
      downs
      gilded
      created_utc
      created_date
    
    
      created
      
      
      
      
      
      
      
    
  
  
    
      2016-04-01 00:00:08
      45
      240
      240
      0
      0
      1459468808
      2016-04-01
    
    
      2016-04-01 00:00:47
      1
      1
      1
      0
      0
      1459468847
      2016-04-01
    
    
      2016-04-01 00:00:59
      0
      22
      22
      0
      0
      1459468859
      2016-04-01
    
    
      2016-04-01 00:02:16
      27
      299
      299
      0
      0
      1459468936
      2016-04-01
    
    
      2016-04-01 00:02:56
      9
      118
      118
      0
      0
      1459468976
      2016-04-01



In [8]:

    
posts_groupby = posts_date_df.groupby([pd.TimeGrouper('1D', closed='left')])

Visualizations

Daily average of number of comments per post



In [9]:

    
posts_groupby.mean().num_comments.plot(kind='barh', figsize=[8,8])









    Out[9]:





<matplotlib.axes._subplots.AxesSubplot at 0x7ff5ff1562e8>

Daily average of number of upvotes per post



In [10]:

    
posts_groupby.mean().ups.plot(kind='barh', figsize=[8,8])









    Out[10]:





<matplotlib.axes._subplots.AxesSubplot at 0x7ff5ff03f2e8>



In [ ]:

	num_comments	score	ups	downs	gilded	created_utc
author
YaBoyyCuddle	0	13	13	0	0	1460422236
blkrctngl	2	14	14	0	0	1461198429
Monteg9210	1	23	23	0	0	1461198955
wookee8	10	1	1	0	0	1460248572
Voat_Donald_Trump	10	148	148	0	0	1459559899

	num_comments	score	ups	downs	gilded	created_utc	created_date
created
2016-04-01 00:00:08	45	240	240	0	0	1459468808	2016-04-01
2016-04-01 00:00:47	1	1	1	0	0	1459468847	2016-04-01
2016-04-01 00:00:59	0	22	22	0	0	1459468859	2016-04-01
2016-04-01 00:02:16	27	299	299	0	0	1459468936	2016-04-01
2016-04-01 00:02:56	9	118	118	0	0	1459468976	2016-04-01