Calling for Help#
Aside from this troubleshooting guide, there are a number of other sources of documentation and troubleshooting information you can check before submitting an issue, as they might already offer an answer, or at least help you better understand the problem. Even if we aren’t able to help you, these places might.
Python resources#
Official Python help page#
The Python help page is a great resource that lists a number of places you can get assistance, support and learning resources for the language and its packages.
Python documentation#
The Python docs can help you understand a number of issues that can be caused by quirks in the language itself, or misunderstandings as to how it behaves.
Python subreddits#
r/python and r/learnpython are resources you can use to ask about and discuss issues with Python and its packages. The former is aimed more at general Python usage, and the latter more specifically at beginners.
Data science/SciPy resources:#
Anaconda help#
The Anaconda docs site offers free community help and documentation for the Anaconda applications, installing the Anaconda distribution, and using the Conda package and environment manager; along with paid support options.
SciPy.org website#
The Scipy website is the the central home of the SciPy stack, with information, documentation, help, and bug tracking for many of the core packages used with Spyder, including NumPy, SciPy, Matplotlib, Pandas, Sympy and IPython.
Project Jupyter#
Jupyter is the development hub for IPython, Spyder’s QtConsole, Jupyter notebooks used with the Spyder-Notebook plugin, and more.
Data Science Stack Exchange#
The Data Science site in Stack Exchange can be very useful for questions that relate more to data science than programming specifically.