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General assignment information

Getting started

To edit/execute a Homework/lecture notebook:

  1. Open the page for the Homework/Lecture on this site.
  2. Click the launch button (🚀) at the top. {% if id == "nyu" -%}
    • {{coding_env_name}} may take a few minutes to start up. {%- endif %}
  3. You should now see the notebook in {{coding_env_name}}. {% if id == "columbia" -%}
  4. Make sure you're using your Columbia Google account. How to switch.
  5. Click Copy to Drive. {% endif -%}

That is now your own copy; make edits in there directly.

Tips

  • Read the instructions carefully. Like word problems from math class, they are very specific in what they are asking for.
  • Ask for help.
    • The assignments are meant to be challenging, not impossible.
    • Try and work through problems on your own to start. If you are stuck for more than a half hour, step away. If you still can't figure it out, ask for help.

Coding in general

  • Make variable names descriptive.
    • Do as I say, not as I do!
  • Only do one thing per line.
    • Makes troubleshooting easier
  • Spot check your results. If you are transforming data from a previous Step, compare the results, do a handful of the calculations manually, etc. to ensure that the results are correct.
  • Don't repeat yourself (DRY). If you find yourself copying and pasting code within your file(s), there's probably a better way to do it.
  • Avoid hard-coding values. Don't rely on things like row numbers or column order being stable, in case the dataset were to be updated.

Jupyter / {{coding_env_name}}

{% if id == "nyu" -%}

  • All lecture slides and homework templates can be found under python-public-policy/. The contents of this directory will be automatically updated from the GitHub repository, but should keep any changes you make.
  • Access {{coding_env_name}} via the links on this site rather than bookmarking {{coding_env_name}}, as that will pull down the latest changes. {% endif -%}
  • Keep each cell to only a few lines of code.
    • Allows/encourages you to output intermediate results, ensuring that everything is working as expected.
  • You are always welcome to add cells. You probably don't want more than a few lines of code in each. This makes the spot checking of intermediate results easier.
  • Make notebooks idempotent
    • Makes your work reproducible.
    • Use Restart and run all (⏩ button in toolbar).

Submission

  1. Ensure all the outputs are visible and the notebook is cleaned up.
    • This is a good time to run the notebook end-to-end with Restart and run all{% if id == "nyu" %} (⏩){% endif %}.
    • See general scoring criteria. {% if id == "columbia" -%}
  2. Confirm that the notebook is shared with the instructor and {{assistant_name}} with Commenter permissions. If it isn't, share the parent folder and re-confirm.
  3. Copy the URL of your notebook.
    • The URL should be of the format https://colab.research.google.com/drive/<long identifier>. If it's https://colab.research.google.com/github/..., click Copy to Drive.
  4. Paste your notebook URL in the {{lms_name}} Assignment.

Engaging with comments left in {{coding_env_name}} is more than welcome. {% else -%}

  1. Export the files.
    • .ipynb:
      1. File
      2. Download
    • .py:
      1. File
      2. Save and Export Notebook As
      3. Executable Script
  2. Submit.
    1. In {{lms_name}}, go to Content.
      • Note that this is not the Assignments tab of {{lms_name}}.
    2. If one of the Homeworks:
      1. Go to {{submission_tool_name}}.
      2. Upload the files to the Assignment.
    3. If the Final Project:
      1. Click Final Project. You should see the TurnItIn/PeerMark dashboard.
      2. Follow these instructions to upload the files. {%- endif %}

Notes

{% if id == "nyu" -%}

  • You can ignore {{submission_tool_name}} saying "Large file hidden". The {{assistant_name}} can download the notebook to view.
  • Resubmissions are done the same way. {%- endif %}
  • In-class exercises will not be submitted/graded.

Common issues

{% if id == "columbia" -%}

  • Mounting Google Drive is slow or fails: See the Google Colab help page.

  • Can't load a file from Drive with requests.get(): Use open().

  • Error: Command '['git', 'diff', '..origin/nyu', '--name-status']' returned non-zero exit status 128 when trying to launch {{coding_env_name}}: Something got corrupted in your copy of the files that come through nbgitpuller. Easiest thing is to move the existing ones and restart with a fresh copy.

    1. Launch {{coding_env_name}}.
    2. There should be a python-public-policy folder. Rename it, something like python-public-policy-old.
      • If you've edited any of the template notebooks, you can find them in that -old folder.
    3. Repeat the getting started steps. {% endif -%}

  • When using choropleth_map(), nothing appears on the map: Make sure:

    • Your locations corresponds to the DataFrame column name and featureidkey is set to properties.<property name> matching the GeoJSON
    • The column and the GeoJSON properties have values that match

  • SettingWithCopyWarning: How to fix

  • input() stuck: Jupyter can be a bit buggy when dealing with interactive input. If it seems to get stuck or you aren't seeing a prompt when you'd expect one, try clicking the {{coding_env_kernel_name.title()}} menu then Restart Kernel.

  • The values are out of order along the axis of a Plotly chart: Make sure that:

  • AttributeError: partially initialized module 'orjson' has no attribute 'OPT_NON_STR_KEYS': Add the following cell before your other Plotly code, then Restart and run all{% if id == "nyu" %} (⏩){% endif %}.

    import plotly.io

plotly.io.json.config.default_engine = 'json'

{% if id == "nyu" -%}

Disk full

If you get an error of Disk is full / No space left on device / Out of diskspace: You've used all the available disk space. If you do fill it up, your server may not be able to start again (spawn failed). You'll need to delete one or more large files that you don't need anymore:

  1. If you server is started already (you're seeing notebooks), click Control Panel -> Stop My Server.
  2. Go to start your server again.
  3. Select Troubleshooting Only - Clear Disk.
  4. Look at the File size Jupyter shows in the file browser.
  5. Delete one or more large files.
  6. If you're still using those datasets, make them smaller.

Error loading notebook

This error can happen if you tried to output a lot of data in tables/charts. Steps to resolve:

  1. Open the {{coding_env_name}}) file browser

  2. Click New, then Terminal

  3. Run the following, changing the path at the end to match whatever notebook needs to be repaired:

    jupyter nbconvert --to notebook --clear-output ~/python-public-policy/hw_<NUMBER>.ipynb

If you're confused by these instrucions, download the notebook file and email to the instructor. {%- endif %}

{{coding_env_kernel_name|title}} and memory issues

The {{coding_env_kernel_name}} is the place where Python is installed and the code is actually executing, in the cloud somewhere.

{% if id == "nyu" -%}

  • Make sure Python [conda env:python-public-policy] is selected as the {{coding_env_kernel_name}}.
    • Shows in the top right of the notebook interface
    • To change:
      1. Open the {{coding_env_kernel_name.title()}} menu.
      2. Click Change {{coding_env_kernel_name}}.
      3. Click Python [conda env:python-public-policy]. {%- endif %}
  • If your {{coding_env_kernel_name}} is repeatedly crashing, you're probably running out of memory.
    • Make sure you aren't loading data sets you don't need.
    • If loading a new dataset, make it smaller {% if id == "nyu" %}
    • Close {{coding_env_kernel_name}}s you aren't using from the Running page. {%- endif %}