tidyexplain VS tidyquery

Compare tidyexplain vs tidyquery and see what are their differences.

tidyexplain

๐Ÿคนโ€โ™€ Animations of tidyverse verbs using R, the tidyverse, and gganimate (by gadenbuie)

tidyquery

Query R data frames with SQL (by ianmcook)
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tidyexplain tidyquery
1 2
742 167
- -
1.8 0.0
over 2 years ago over 1 year ago
R R
Creative Commons Zero v1.0 Universal Apache License 2.0
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.

tidyexplain

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

tidyquery

Posts with mentions or reviews of tidyquery. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-03-02.
  • Can "dplyr" code automatically be converted to SQL code?
    1 project | /r/rstats | 15 Sep 2021
    tidyquery
  • ClickHouse as an alternative to Elasticsearch for log storage and analysis
    13 projects | news.ycombinator.com | 2 Mar 2021
    > SQL is a perfect language for analytics.

    Slightly off topic, but I strongly agree with this statement and wonder why the languages used for a lot of data science work (R, Python) don't have such a strong focus on SQL.

    It might just be my brain, but SQL makes so much logical sense as a query language and, with small variances, is used to directly query so many databases.

    In R, why learn the data.tables (OK, speed) or dplyr paradigms, when SQL can be easily applied directly to dataframes? There are libraries to support this like sqldf[1], tidyquery[2] and duckdf[3] (author). And I'm sure the situation is similar in Python.

    This is not a post against great libraries like data.table and dplyr, which I do use from time to time. It's more of a question about why SQL is not more popular as the query language de jour for data science.

    [1] https://cran.r-project.org/web/packages/sqldf/index.html

    [2] https://github.com/ianmcook/tidyquery

    [3] https://github.com/phillc73/duckdf

What are some alternatives?

When comparing tidyexplain and tidyquery you can also consider the following projects:

dtplyr - Data table backend for dplyr

duckdf - ๐Ÿฆ† SQL for R dataframes, with ducks

ggsignif - Easily add significance brackets to your ggplots

clickhousedb_fdw - PostgreSQL's Foreign Data Wrapper For ClickHouse

gpx-viz - Personal project to visualize gpx tracks

meilisearch-js-plugins - The search client to use Meilisearch with InstantSearch.

ganttrify - Create beautiful Gantt charts with ggplot2

tidyquant - Bringing financial analysis to the tidyverse

tidyverse - Easily install and load packages from the tidyverse

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.

MeiliSearch - A lightning-fast search API that fits effortlessly into your apps, websites, and workflow

cloki-go-legacy - Clickhouse Loki API in GO (WIP)