Count number of questions/topics posted on en-net by time
count_topics_day(topics = get_themes_topics(), .sort = FALSE)
count_topics_week(topics = get_themes_topics(), .sort = FALSE)
count_topics_month(topics = get_themes_topics(), .sort = FALSE)
count_topics_year(topics = get_themes_topics(), .sort = FALSE)A tibble of topics by theme, by author, and by posting date
from en-net forum produced through a call to get_themes_topics()
Logical. Should output be sorted by count frequencies? Default is FALSE
A tibble of topic counts by specified time grouping
## Get counts of topics by day
count_topics_day(topics = ennet_topics)
#> # A tibble: 1,954 × 2
#> day n
#> <date> <int>
#> 1 2009-02-14 1
#> 2 2009-02-18 1
#> 3 2009-02-19 2
#> 4 2009-02-20 1
#> 5 2009-02-23 1
#> 6 2009-02-24 2
#> 7 2009-02-25 3
#> 8 2009-03-02 1
#> 9 2009-03-03 1
#> 10 2009-03-07 1
#> # … with 1,944 more rows
## Get counts of topics by week
count_topics_week(topics = ennet_topics)
#> # A tibble: 635 × 3
#> week week_name n
#> <date> <chr> <int>
#> 1 2009-02-08 Week 06 2009 1
#> 2 2009-02-15 Week 07 2009 4
#> 3 2009-02-22 Week 08 2009 6
#> 4 2009-03-01 Week 09 2009 3
#> 5 2009-03-08 Week 10 2009 4
#> 6 2009-03-15 Week 11 2009 4
#> 7 2009-03-22 Week 12 2009 2
#> 8 2009-04-12 Week 15 2009 3
#> 9 2009-04-19 Week 16 2009 1
#> 10 2009-04-26 Week 17 2009 4
#> # … with 625 more rows
## Get counts of topics by month
count_topics_month(topics = ennet_topics)
#> # A tibble: 155 × 3
#> month month_name n
#> <date> <chr> <int>
#> 1 2009-02-01 Feb 2009 11
#> 2 2009-03-01 Mar 2009 13
#> 3 2009-04-01 Apr 2009 8
#> 4 2009-05-01 May 2009 8
#> 5 2009-06-01 Jun 2009 8
#> 6 2009-07-01 Jul 2009 10
#> 7 2009-08-01 Aug 2009 10
#> 8 2009-09-01 Sep 2009 8
#> 9 2009-10-01 Oct 2009 2
#> 10 2009-11-01 Nov 2009 4
#> # … with 145 more rows
## Get counts of topics by year
count_topics_year(topics = ennet_topics)
#> # A tibble: 13 × 3
#> year year_name n
#> <date> <chr> <int>
#> 1 2009-01-01 2009 88
#> 2 2010-01-01 2010 103
#> 3 2011-01-01 2011 191
#> 4 2012-01-01 2012 246
#> 5 2013-01-01 2013 228
#> 6 2014-01-01 2014 303
#> 7 2015-01-01 2015 391
#> 8 2016-01-01 2016 362
#> 9 2017-01-01 2017 303
#> 10 2018-01-01 2018 263
#> 11 2019-01-01 2019 254
#> 12 2020-01-01 2020 301
#> 13 2021-01-01 2021 255