RdplyrSelects VS dtplyr

Compare RdplyrSelects vs dtplyr and see what are their differences.

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RdplyrSelects dtplyr
1 24
0 671
- 0.1%
0.0 3.6
over 3 years ago 15 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.

RdplyrSelects

Posts with mentions or reviews of RdplyrSelects. We have used some of these posts to build our list of alternatives and similar projects.

dtplyr

Posts with mentions or reviews of dtplyr. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-04-09.

What are some alternatives?

When comparing RdplyrSelects and dtplyr you can also consider the following projects:

tidyquant - Bringing financial analysis to the tidyverse

tidytable - Tidy interface to 'data.table'

tidyexplain - 🤹‍♀ Animations of tidyverse verbs using R, the tidyverse, and gganimate

tidypolars - Tidy interface to polars

ggplot2 - An implementation of the Grammar of Graphics in R

vaex - Out-of-Core hybrid Apache Arrow/NumPy DataFrame for Python, ML, visualization and exploration of big tabular data at a billion rows per second 🚀

tidyquery - Query R data frames with SQL

dataiter - Simple, light-weight data frames for Python

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.

Datamancer - A dataframe library with a dplyr like API

explorer - Series (one-dimensional) and dataframes (two-dimensional) for fast and elegant data exploration in Elixir

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