q
siuba
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| q | siuba | |
|---|---|---|
| 46 | 25 | |
| 10,109 | 1,101 | |
| - | - | |
| 3.6 | 7.5 | |
| 3 months ago | 7 months ago | |
| Python | Python | |
| GNU General Public License v3.0 only | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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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.
q
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I wrote this iCalendar (.ics) command-line utility to turn common calendar exports into more broadly compatible CSV files.
CSV utilities (still haven't pick a favorite one...): https://github.com/harelba/q https://github.com/BurntSushi/xsv https://github.com/wireservice/csvkit https://github.com/johnkerl/miller
- Segítség kérés Excel automatizáláshoz
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Show HN: ClickHouse-local – a small tool for serverless data analytics
I think they're talking about https://github.com/harelba/q, which is not very fast.
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sqly - execute SQL against CSV / JSON with shell
Apparently, there were many who thought the same thing; Tools to execute SQL against CSV were trdsql, q, csvq, TextQL. They were highly functional, hoewver, had many options and no input completion. I found it just a little difficult to use.
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Q – Run SQL Directly on CSV or TSV Files
Hi, author of q here.
Regarding the error you got, q currently does not autodetect headers, so you'd need to add -H as a flag in order to use the "country" column name. You're absolutely correct on failing-fast here - It's a bug which i'll fix.
In general regarding speed - q supports automatic caching of the CSV files (through the "-C readwrite" flag). Once it's activated, it will write the data into another file (with a .qsql extension), and will use it automatically in further queries in order to speed things considerably.
Effectively, the .qsql files are regular sqlite3 files (with some metadata), and q can be used to query them directly (or any regular sqlite3 file), including the ability to seamlessly join between multiple sqlite3 files.
http://harelba.github.io/q/#auto-caching-examples
- PostgreSQL alternative for Large amounts of data
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q VS trdsql - a user suggested alternative
2 projects | 25 Jun 2022
- One-liner for running queries against CSV files with SQLite
siuba
- The Design Philosophy of Great Tables (Software Package)
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Best alternative to Pandas 2023?
I don't know what's best for you, but I can recommend Siuba, a tidy interface for Python to send queries to pandas and SQL-db.
- Method Chaining in Pandas: Bad Form or a Recipe for Success?
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Happy Halloween, Pandas! 🎃🤓
You mean siuba?
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Explorer (Elixir and Polars)
For further inspiration, this is a pretty good-looking "dplyr for Python": https://github.com/machow/siuba
- Unpopular opinion: Matplotlib is a bad library
- A trick to have arbitrary infix operators in Python
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Going from R to Pandas: dplython vs dfply vs plydata
You should follow /u/the75th's advice. However, if you decide to buck that take, I'd look into siuba. I've never heard of those packages you've listed, and have doubts they'd be maintained.
- Tidyverse equivalent in Python?
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R / Tidyverse User -> Python | How to Make it Hurt Less
Check out siuba
What are some alternatives?
textql - Execute SQL against structured text like CSV or TSV
Pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
csvq - SQL-like query language for csv
dtale - Visualizer for pandas data structures
octosql - OctoSQL is a query tool that allows you to join, analyse and transform data from multiple databases and file formats using SQL.
Altair - Declarative statistical visualization library for Python
xsv - A fast CSV command line toolkit written in Rust.
vinum - Vinum is a SQL processor for Python, designed for data analysis workflows and in-memory analytics.
InquirerPy - :snake: Python port of Inquirer.js (A collection of common interactive command-line user interfaces)
DataFramesMeta.jl - Metaprogramming tools for DataFrames
ledger - Double-entry accounting system with a command-line reporting interface
data.table - R's data.table package extends data.frame: