janitor
parquetize
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| janitor | parquetize | |
|---|---|---|
| 2 | 4 | |
| 1,341 | 56 | |
| - | - | |
| 6.2 | 6.8 | |
| about 2 months ago | about 2 months ago | |
| R | R | |
| GNU General Public License v3.0 or later | - |
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janitor
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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.
parquetize
- You want to convert your R data to parquet files ? Use parquetize package !
- 🚨New {parquetize} release 🚨Easily convert your data to Parquet format ! Now from any query you want on any DBI compatible RDBMS. https://github.com/ddotta/parquetize/releases/tag/v0.5.6 #rstats #parquet #arrow #DBI More details in release note.
- 🚨🚨New release for {parquetize} R package 🚨🚨 => convert easily your data to Parquet format !
- You're an #rstats user and you need to convert your files to parquet format? Check out the new parquetize package now available on CRAN !
What are some alternatives?
tidyverse - Easily install and load packages from the tidyverse
stata-alluvial - A Stata package for alluvial plots
IntRo - Introduction to R for health data
readr - Read flat files (csv, tsv, fwf) into R
Practical-Applications-in-R-for-Psychologists - Lesson files for Practical Applications in R for Psychologists.
ftools - Fast Stata commands for large datasets
tidylog - Tidylog provides feedback about dplyr and tidyr operations. It provides wrapper functions for the most common functions, such as filter, mutate, select, and group_by, and provides detailed output for joins.
targets - Function-oriented Make-like declarative workflows for R
datapasta - On top of spaghetti, all covered in cheese....
sf - Simple Features for R
desctable - An R package to produce descriptive and comparative tables
drake - An R-focused pipeline toolkit for reproducibility and high-performance computing