janitor
simple tools for data cleaning in R (by sfirke)
IntRo
Introduction to R for health data (by andreamazzella)
| janitor | IntRo | |
|---|---|---|
| 2 | 1 | |
| 1,409 | 12 | |
| 0.6% | - | |
| 5.5 | 8.8 | |
| 4 months ago | 7 days ago | |
| R | R | |
| GNU General Public License v3.0 or later | - |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
janitor
Posts with mentions or reviews of janitor.
We have used some of these posts to build our list of alternatives
and similar projects.
-
Working with columns names that are numbers (in this case, years)
I would just clean the names and work with those. Then there is no need to use backticks. Read about the function clean_names in the janitor vignette: https://github.com/sfirke/janitor
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R Libraries Every Data Scientist Should Know - Pyoflife
I just stumbled across Janitor which can help you clean colum names easily.
IntRo
Posts with mentions or reviews of IntRo.
We have used some of these posts to build our list of alternatives
and similar projects.
-
Courses on R for Medical Research
I’ve prepared a 5-session introduction to R with the tidyverse, mainly focussing on the basics and data management (which is more important than stats when you start, IMO). Have a look https://github.com/andreamazzella/IntRo
What are some alternatives?
When comparing janitor and IntRo you can also consider the following projects:
parquetize - R package that allows to convert databases of different formats to parquet format
Data-science-best-resources - Carefully curated resource links for data science in one place
tidytext - Text mining using tidy tools :sparkles::page_facing_up::sparkles:
desctable - An R package to produce descriptive and comparative tables
tidyverse - Easily install and load packages from the tidyverse