In the recent months, I have received many kind feedbacks and helpful suggestions from mindr users. I did not improve or enhance mindr until the latest week. Now the new version 1.1.5 brings more exciting features.
Many years ago, I collected some LaTeX templates when learning LaTeX. However, my interest in LaTeX was gone after submitting my PhD dissertation. I should have deleted these templates if they had not been so small. They would never be useful in the future, I thought.
In 2017, I started writing the book Learning R: R for Rookies . Unexpectedly, MS Word could not satisfy me with the typesetting. You know what I mean if you have experience (and pain) in writing a long book or dissertation with Word. Actually I suffered more, but I do not want to talk about it. I was sure that LaTeX could, but I would rather not use it.
Like a bolt out of the blue, I found bookdown.
sposts() displays a Shiny app, which is a user friendly interactive UI to show all the posts of a give Steemian's ID. Analysis diagrams are plotted as well, including the distribution of the post payout and votes, the active hour of the Steemian's posting, and the time series of the growth of the cumulative post number, payout, and votes.
I added diagrams into the Shiny app scner(). These diagrams include the word clouds of the Steemians of the CN community, as well as the histograms for the distributions according to the ESP, account value, online-days, etc..
A new functionscner() displays a Shiny app, which is a user friendly interactive UI for the statistics of a group of Steemians, hereby those who are active in the CN community. It has the potential to be used for other groups of Steemians with some simple modifications to this function.
A comment by the utopian.io moderator mentioned that the wordings of both 'followers but not following', 'following but not followers' are confusing. Although they are the official callings that I cannot change, a diagram could help. Therefore, I added a Venn diagram into the sfollow()shiny app.
gcomment() to retrieve the comment data of a given ID.gcomment().Copyright (c) 2019, OpenR Team; all rights reserved.
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