janitor
tidyquery
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| janitor | tidyquery | |
|---|---|---|
| 2 | 2 | |
| 1,341 | 167 | |
| - | - | |
| 6.2 | 0.0 | |
| about 2 months ago | over 1 year ago | |
| R | R | |
| GNU General Public License v3.0 or later | Apache License 2.0 |
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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.
tidyquery
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Can "dplyr" code automatically be converted to SQL code?
tidyquery
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ClickHouse as an alternative to Elasticsearch for log storage and analysis
> 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?
tidyverse - Easily install and load packages from the tidyverse
duckdf - 🦆 SQL for R dataframes, with ducks
IntRo - Introduction to R for health data
clickhousedb_fdw - PostgreSQL's Foreign Data Wrapper For ClickHouse
Practical-Applications-in-R-for-Psychologists - Lesson files for Practical Applications in R for Psychologists.
meilisearch-js-plugins - The search client to use Meilisearch with InstantSearch.
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.
tidyquant - Bringing financial analysis to the tidyverse
datapasta - On top of spaghetti, all covered in cheese....
desctable - An R package to produce descriptive and comparative tables