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You are here: Home » List of Good IDEs for Data Analysis, Data Science

By Abhishek Ghosh October 15, 2017 9:54 am Updated on October 15, 2017

List of Good IDEs for Data Analysis, Data Science

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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 :

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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 :

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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 :

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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 :

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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 :

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https://atom.io/packages/hydrogen

It is enough good to test drive without making the computer a junkyard of others trial of developments.

Juno :

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https://github.com/uetchy/juno

As because Juno can be installed via Homebrew and minimal like Mac users want, it is great.

Rodeo :

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https://github.com/yhat/rodeo

Rodeo is really powerful and more towards Spyder, PyCharm category.

Our way with Octave, Homebrew, Gnuplot :

List of Good IDEs for Data Analysis, Data Science

If you already have Homebrew, Atom installed simply install :

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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.

Tagged With data analysis ide , IDEs para data science , is pycharm good for data science , java data science ide , nteract versus jupyterlab

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Abhishek Ghosh

About Abhishek Ghosh

Abhishek Ghosh is a Businessman, Surgeon, Author and Blogger. You can keep touch with him on Twitter - @AbhishekCTRL.

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About This Article

Cite this article as: Abhishek Ghosh, "List of Good IDEs for Data Analysis, Data Science," in The Customize Windows, October 15, 2017, March 31, 2023, https://thecustomizewindows.com/2017/10/list-good-ides-data-analysis-data-science/.

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