Features Spyder contains features like a text editor with syntax highlighting, code completion and variable exploring, which you can edit its values using a Graphical User Interface (GUI). “If you are switching from Matlab or Rstudio to Python; Spyder is the way to go, It very intuitive for scientific computing.”
RStudio belongs to "Languages" category of the tech stack, while Spyder can be primarily classified under "Integrated Development Environment". RStudio and Spyder are both open source tools.
With RStudio products you can combine R and Python seamlessly without extra overhead. You can use the RStudio IDE for R, but also for bilingual tasks. With RStudio Workbench, launch Jupyter Notebooks, JupyterLab, or VS Code for Python.
PyCharm can be classified as a tool in the "Integrated Development Environment" category, while RStudio is grouped under "Languages". Some of the features offered by PyCharm are: Syntax highlighting. Auto-Indentation and code formatting.
IPython Notebooks are awesome. Here's another, newer browser-based tool I've recently discovered: Rodeo. My impression is that it seems to better support an RStudio-like workflow.
spyder or install python(x,y). it is great.
If you are new to Python, you can install the free Anaconda distribution (http://continuum.io/downloads.html), which will install Spyder for you, as well as Python 2.7 and IPython. Spyder is very similar to RStudio.
Jupyter Notebook (previously known as IPython notebook) is a really cool project for interactive data manipulation in Python (and other languages, including R). It basically allows you to interactively code and document what you're doing in one interface and later on save it as a:
You can even share your notebooks online with others using the nbviewer service, where people publish whole books. Furthermore, GitHub renders your .ipynb files. You can publish your Jupyter Notebooks as reproducible research articles on Authorea. For collaborative editing by multiple users, check out Google Colab built on top of Jupyter.
The default Jupyter Notebook version starts a web application locally (or you deploy it to a server) and you use it from your browser. As Ryan also mentioned in his answer, Rodeo is an interface more similar to RStudio built on top of the Jupyter kernel.
JupyterLab is a newer take on the UI allowing for more flexibility in how you edit your notebooks, control interactive widgets and even run commands in terminal emulators.
There's also a Qt console for IPython, a similar project with inline plots, which is a desktop application.
Jupyter is a normal Python package and can be installed using pip install jupyter
. To get all the scientific libraries running on your computer, however, it might be easier to try the official Jupyter Docker containers. For example, assuming your notebooks are in ~/code/jupyter, you can run the container as:
docker run -it --rm -p 8888:8888 -v ~/code/jupyter:/home/jovyan/work jupyter/datascience-notebook
Check out Rodeo from Yhat if you're looking for something like RStudio for Python.
Rodeo has:
You might want to look into JupyterLab (the next generation of Jupyter Notbooks): https://github.com/jupyter/jupyterlab.
JupyterLab aims to create a more desktop-like experience on the Web.
Update: As of March 2018 JupyterLab is in beta. "The beta releases are suitable for general usage. For JupyterLab extension developers, the extension APIs will continue to evolve until the 1.0 release. Eventually, JupyterLab will replace the classic Jupyter Notebook after JupyterLab reaches 1.0."
To run Jupyter Lab as a Desktop Application, see christopherroach.com/articles/jupyterlab-desktop-app (Thanks to PatrickT).
Here's a quick preview:
You can arrange a notebook next to a graphical console atop a terminal that is monitoring the system, while keeping the file manager on the left:
For more details see: https://blog.jupyter.org/2016/07/14/jupyter-lab-alpha/ and here: http://www.techatbloomberg.com/blog/inside-the-collaboration-that-built-the-open-source-jupyterlab-project/.
Pycharm is a really decent IDE. From what I have seen so far it is the most similar to Rstudio. Another nice piece is that it allows you to install new Python libraries in a fashion similar to Rstudio (which otherwise can be a nightmare). There is now a free 'community' edition.
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