readr VS parquetize

Compare readr vs parquetize and see what are their differences.

readr

Read flat files (csv, tsv, fwf) into R (by tidyverse)

parquetize

R package that allows to convert databases of different formats to parquet format (by ddotta)
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readr parquetize
1 4
992 56
0.4% -
6.0 6.8
21 days ago about 2 months 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.

readr

Posts with mentions or reviews of readr. We have used some of these posts to build our list of alternatives and similar projects.
  • Is it safe to use the error handling features of C++ with Rcpp?
    1 project | /r/rstats | 28 Jan 2023
    If you use these error handling features, it does leave things in memory. I believe it’s only for objects you have allocated from c++, so may not be a big deal. For example, here’s where I noticed it in readr, which is presumably fixed now that they use rcpp11 https://github.com/tidyverse/readr/issues/757

What are some alternatives?

When comparing readr and parquetize you can also consider the following projects:

evaluate - A version of eval for R that returns more information about what happened

stata-alluvial - A Stata package for alluvial plots

ggplot2 - An implementation of the Grammar of Graphics in R

ftools - Fast Stata commands for large datasets

r4ds - R for data science: a book

targets - Function-oriented Make-like declarative workflows for R

tidyethnicnews - R package for turning Ethnic NewsWatch search results into tidyverse-ready dataframes

janitor - simple tools for data cleaning in R

awesome-R - A curated list of awesome R packages, frameworks and software.

sf - Simple Features for R

drake - An R-focused pipeline toolkit for reproducibility and high-performance computing

rmarkdown - Dynamic Documents for R