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Based on our record, Pandas seems to be a lot more popular than iPython. While we know about 198 links to Pandas, we've tracked only 18 mentions of iPython. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Third, if possible use a command line interpreter to test things out. I recommend ipython for this purpose. You can use your browser's developer console this way if you are learning Javascript. Source: about 1 year ago
IJulia is an interactive notebook environment powered by the Julia programming language. Its backend is integrated with that of the Jupyter environment. The interface is web-based, similar to the iPython notebook. It is open-source and cross-platform. - Source: dev.to / about 1 year ago
Also, take a look at installing iPthon to give you a much richer shell environment. This underpins Jupyter Notebooks, so is well known, proven and trusted. Source: about 1 year ago
I know this isn't quite what you're asking for, but IPython (https://ipython.org/) is very capable as a Python + bash (or other) shell, as it allows you to easily integrate the system shell into the interactive environment. Although they now recommend Xonsh (https://xon.sh/) for such purposes. Source: about 1 year ago
Either an online python interpreter like replit.com or simply any python interpreter, like `ipython`, or the default, barebones one that ships with the python installation pacakge. Source: over 1 year ago
Python is a natural fit for serverless development. It boasts a vast array of libraries, including Powertools for AWS and robust libraries for data engineers. Its versatility and excellent developer experience make it a top choice for serverless projects, offering a seamless and enjoyable development experience. - Source: dev.to / 13 days ago
In data analysis, managing the structure and layout of data before analyzing them is crucial. Python offers versatile tools to manipulate data, including the often-used Pandas reset_index() method. - Source: dev.to / 6 days ago
Dash is a Python framework that enables you to build interactive frontend applications without writing a single line of Javascript. Internally and in projects we like to use it in order to build a quick proof of concept for data driven applications because of the nice integration with Plotly and pandas. For this post, I'm going to assume that you're already familiar with Dash and won't explain that part in detail.... - Source: dev.to / 2 months ago
Last year I worked through the challenges using VisiData, Datasette, and Pandas. I walked through my thought process and solutions in a series of posts. - Source: dev.to / 5 months ago
Data analysis involves scrutinizing datasets for class imbalances or protected features and understanding their correlations and representations. A classical tool like pandas would be my obvious choice for most of the analysis, and I would use OpenCV or Scikit-Image for image-related tasks. - Source: dev.to / 5 months ago
Jupyter - Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. Ready to get started? Try it in your browser Install the Notebook.
NumPy - NumPy is the fundamental package for scientific computing with Python
PyCharm - Python & Django IDE with intelligent code completion, on-the-fly error checking, quick-fixes, and much more...
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
IDLE - Default IDE which come installed with the Python programming language.
OpenCV - OpenCV is the world's biggest computer vision library