After Electron project developed, the number of IDEs, text editors started to spam the whole earth. Some are just another fork, some are unusable. We have tested excluding the junks from zillions of ides. Here is a List of Good IDEs for Data Analysis, Data Science. It is sane to think about using Microsoft Visual Studio Code or Atom Editor as main software unless except Data Analysis, Data Science you need doing nothing. It is worthy to mention that we have guides for Jupyter Notebook which must be a part of any Python worker’s toolbox.
List of Good IDEs for Data Analysis, Data Science
Free PyCharm :
1 | https://www.jetbrains.com/pycharm-edu/download/#section=mac |
PyCharm is an IDE from a team responsible for one of the most famous Java IDE. PyCharm is great for those who have experience using another JetBrain’s IDE, those who like things like IPython. PyCharm allows to work with array viewers and interactive plots. PyCharm also supports JavaScript, HTML, CSS, Angular JS, Node.js, and so it a good option for web development too.
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Spyder :
1 | https://github.com/spyder-ide/spyder |
If you have Anaconda distribution installed on your computer, you possibly already know about Spyder. Spyder is a powerful IDE for the Python language with advanced editing, interactive testing, debugging features.
JupyterLab :
1 | https://github.com/jupyterlab/jupyterlab |
JupyterLab is really great IDE but still it has many things which needs to be developed to make something mass acceptable like Atom Editor or VS Code. By the phrase “mass acceptable” I want to mean – all who are related to data sciences.
nteract :
1 | https://github.com/nteract/nteract |
The matter of nteract is closer to JupyterLab, it is also really a good IDE but still it has many things which needs to be developed, may be enough now for most of the first time users.
Atom Editor with Hydrogen :
1 | https://atom.io/packages/hydrogen |
It is enough good to test drive without making the computer a junkyard of others trial of developments.
Juno :
1 | https://github.com/uetchy/juno |
As because Juno can be installed via Homebrew and minimal like Mac users want, it is great.
Rodeo :
1 | https://github.com/yhat/rodeo |
Rodeo is really powerful and more towards Spyder, PyCharm category.
Our way with Octave, Homebrew, Gnuplot :
If you already have Homebrew, Atom installed simply install :
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | brew tap homebrew/science brew install octave brew install gnuplot --with-aquaterm gnuplot gnuplot> set terminal aqua nano ~/.zshrc ## add export FONTCONFIG_PATH=/opt/X11/lib/X11/fontconfig ## save source ~/.zshrc nano /usr/local/Cellar/octave/<version>/share/octave/site/m/startup ## add setenv('GNUTERM','aqua') ## save apm init --package ~/.atom/packages/language-matlab --convert https://github.com/textmate/matlab.tmbundle ## install terminal-plus on Atom |
I got the above idea from places like https://stackoverflow.com/questions/35249881/octave-fontconfig-error.
I guess this list is enough.
