In general, when submitting a notebook, all Python 3.6 code is supported on UNCode. However, Ipython notebooks and python code differ in some functionalities, then UNCode might support them or not. Also, there are some things you should bear in mind when creating your notebook.

• Python modules:
  You are able to use the next python modules in addition to the pre installed python modules:
  import pandas, numpy, matplotlib, scipy, scikit-learn, seaborn, datascience, plotly, cufflinks, bokeh, tabulate, nltk, tensorflow, Keras
  
  Installing modules:
  All the modules and data you require are already installed and supported by UNCode.
  Then, when you have lines installing a module, for instance: !pip install pandas or using conda, these lines are automatically removed from your notebook to avoid runtime execution errors.
  
  In case you want to use one module and it is not in the previous list, do not hesitate on reaching out for support.
• Print expressions:
  Usually while executing your notebook on your runtime you might add some print expressions, though, these expressions are deleted and these outputs are not shown in the submission feedback.
• Internet access in grading environment:
  The internet access when your code is being graded is dependant on the task. Some tasks might allow it or not.
  In case you are allowed to access internet, this mainly will work to download files or data, for instance datasets. As stated above, you cannot install modules.
  In case there is not access, be careful when using code that requires internet access as it will fail while grading.
• Magic functionality execution:
  Magic functions are not allowed when your notebook is graded. For example the next line:
  %matplotlib inline
  In case your notebook contains some lines like this, they will be automatically removed to avoid runtime execution errors.
• Commands execution:
  Python Notebooks provide a functionality to execute commands like these:
  !ls
!pwd
  However, this kind of lines are transformed as follows:
  !ls is turned into the following code:
  import subprocess
call = subprocess.run(["ls"], stdout=subprocess.PIPE)
print(call.stdout.decode('utf-8')
  That code will do the same for you as in the notebook. However, you are not allowed to assign the result of command execution to variables, for instance the next line will return an error:
  result = !ls.
• Google Colab modules
  When you use Google Colaboratory (Colab) and you want to load and read data from Google Drive, you are required to use some python modules unique in Colab. These modules are not supported by UNCode. Then, make sure when you submit your notebook, you do not include it.