vnlog
nvim-ipy
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vnlog
- Vnlog: Process labelled tabular ASCII data using normal Unix tools
- Process tabular data with Unix tools
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Qsv: Efficient CSV CLI Toolkit
For simple analyses (i.e. what most people do most of the time) doing this on the commandline gets you there faster. I use vnlog (https://github.com/dkogan/vnlog/). By the time you fired up your editor to write your Python code, I already have analyses and plots ready.
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Joining CSV Data Without SQL: An IP Geolocation Use Case
Alternative very appropriate for some uses cases: `vnl-join` from the vnlog toolkit (https://github.com/dkogan/vnlog). Uses the `join` tool from coreutils (works well, has been around forever), and `vnlog` for nice column labelling
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Miller: Like Awk, sed, cut, join, and sort for CSV, TSV, and tabular JSON
There's also https://github.com/dkogan/vnlog/ which is a wrapper around the existing coreutils, so all the options work, and there's nothing to learn
- vnlog: making awk and sort and join (and friends) smarter
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Awk equivalents to SQL query data manipulation
And to improve the ergonomics, the vnlog wrappers are available to operate on field names, while retaining the internals of the core tools:
https://github.com/dkogan/vnlog/
- Vnlog: Making Awk, grep, sort and join smarter
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Learn to Process Text in Linux Using Grep, Sed, and Awk
I sorta, kinda agree. Tools written in AWK (and friends) are indeed somewhat unmaintainable, but they're really close to being just right for a LOT of applications. The vnlog toolkit (https://github.com/dkogan/vnlog) adds just a little bit of syntactic sugar to the usual commandline tools to make processing scripts robust and easy to read and write. This was not my intent initially, but I now do most of my data processing with the shell and vnl-wrapped awk (and sort and join, ...) It's really nice. If you write stuff in awk, you should check it out. (Disclaimer: I'm the author)
- Extending Awk with Field Labels
nvim-ipy
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jupyter and vim
In my setup the figures appear as new windows on my other monitor, which works really well. If you want to display the figures inline, you can for example use QtConsole. You would then need another plugin to connect vim and IPython, for example vim-ipython (no support for cells as far as I know) or nvim-ipy (for neovim). Here's an article that describes a setup with the latter: https://www.blog.gambitaccepted.com/2020/04/26/neovim-qtconsole-setup/
- Using Neovim in place of Jupyter notebooks
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Help with Python IDLE
There's also nvim-ipy (but I don't use neovim, so I can't recommend it).
What are some alternatives?
ttyplot - a realtime plotting utility for terminal/console with data input from stdin
vim-ipython-cell - Seamlessly run Python code in IPython from Vim
matplotplusplus - Matplot++: A C++ Graphics Library for Data Visualization 📊🗾
jupyter-vim-binding - Jupyter meets Vim. Vimmer will fall in love.
RecordStream - commandline tools for slicing and dicing JSON records.
jupyterlab-vim - :neckbeard: Vim notebook cell bindings for JupyterLab
jupytext.vim - Vim plugin for editing Jupyter ipynb files via jupytext
vim-ipython - A two-way integration between Vim and IPython 0.11+
matplotlib - C++ wrappers around python's matplotlib
vim-slime - A vim plugin to give you some slime. (Emacs)
feedgnuplot - Tool to plot realtime and stored data from the commandline, using gnuplot.
oni - Oni: Modern Modal Editing - powered by Neovim