‘steemr’ is an open source R package for playing with Steem data in R environment. It is used to download, post process, analyze, and visualize Steem data on the basis of the powerful statistic power of R.
What features did I add?
- I have submitted steemr to CRAN and now it is available. Users can install steemr directly from CRAN:
- Users can use
method = 'appbase_api'to download Steem data from AppBase API:
posts <- post_id('dapeng', method = 'appbase_api')
- A new powerful function
hourrose()was added to plot a diagram of an ID’s active hours in a day based on the post or comment time.
hourrose(my_df = posts, col_time = 'created')
This 24-hour clock shows the active hours of an ID. Users can even choose whether to display another parameter, such as vote number on these posts. Here is a screenshot of plotting such a image in RStudio IDE.
More feature of this function can be found in the help documentation:
- Although SteemData is gone, I still added the query method from steemdata.com. I wish SteemData could come back some day. I love it.
- The documentation has been improved.
- Some minor literal chagnes.
How did I implement them?
I added the AppBase API option to the
id_info() function and
post_id() function with the support from ‘ kharoof/steemR’ repo.
I added the queries for SteemData with the R mongolite package and added the options that users can choose the server.
I added a new function
hourrose() originated from a windrose plotting method but tailored for Steem data.
All these changes can be found in ‘R/steemr.R’.
Links to relevant lines in the code on GitHub can be found mainly in my latest commits: