Frequently Asked Questions
Q: What is the best way to get help in this course?
A: Your best avenues are to go to office hours held by the course staff, or to ask questions on Ed. Course staff will be monitoring Ed frequently and will try to answer your question quickly and thoroughly.
Q: Where will our grades for assignments be displayed for the course?
A: Grades will be displayed on Pensieve for the written and autograded portions for all assignments (homeworks, labs, projects, and exams). For homeworks and projects, your total grade is the sum of the autograded portion and the written portion.
Q: I passed all the tests when doing my homework/project, but still got points off on the autograded portion of the assignment. Why is this happening?
A: The homeworks and projects have hidden tests that are not visible to students while they do the assignment. In order to pass these hidden tests, you must test your code yourself and make sure your answer is correct. Our tests are not always comprehensive.
Q: I have a 80/100 on my grade report for a lab that I attended and got checked off. Why is this?
A: Your attendance may have been marked incorrectly. Please contact your lab TA.
Q: I worked with a partner on a project, and they have a grade on Pensieve for the project while I do not. Why is this happening?
A: You were likely not added to the Pensieve submission. Have your partner add you to both the written work and autograder submission immediately and contact your lab TA.
Q: I noticed a mistake in the grading of the written portion of my homework. How can I get this fixed?
A: To get this fixed, you must submit a regrade request via Pensieve before the regrade deadline. This is known as the regrade request window. We unfortunately will not accept any regrades after the window has closed. All regrade deadline dates are posted on the same Ed post that releases the assignment grades and solutions.
Q: I have some other grading questions. Who should I contact?
A: Please contact your lab GSI.
Q: I would like to apply for a (u)GSI position for this course. What should I do?
A: All applications for Academic Student Employee positions are managed centrally; you can find all the details here. Please do not email the instructors individually with your resume/etc, as they are not in a position to hire you.
Debugging
Cells and the Autograder
Why does running a particular cell cause my kernel to die?
If one particular cell seems to cause your kernel to die, your code is probably incorrect in a way that is causing the computer to use more memory than it has available. For instance: your code is trying to create a gigantic array. To prevent from crashing the entire server, the kernel will âdieâ. This is an indication that there is a mistake in your code that you need to fix.
My python code cell has turned into a text/markdown cell. How do I change it back?
Click on the cell and select Markdown > Code in the top toolbar. Alternatively, click on the cell and press y.
My markdown text cell has turned into a code cell. How do I change it back?
Click on the cell and select Code > Markdown in the top toolbar. Alternatively, click on the cell and press m.
How do I quickly run all the cells in a notebook?
Go to the Cell menu in the top toolbar, then âRun All.â You can also select a certain cell and run all cells before this point, or run all cells after this point. You should run all the cells in your notebook before submitting to confirm that you pass all the tests.
Why does grader.check_all() fail, if all previous tests passed?
This can happen if you âoverwriteâ a variable that is used in a question. For instance, if Question 1 asks you to store your answer in a variable named stat, and later on in the notebook you change the value of stat, youâll see the test after Question 1 pass, but the test at the end of the notebook fail. Make sure to avoid using the same variable name for more than one purpose.
Why does a notebook test fail now, when it passed before and I didnât change my code?
You probably ran your notebook out of order. Re-run all previous cells in order, which is how your code will be graded.
Why did a Pensieve test fail, when all the notebookâs tests passed?
This can happen if youâre running your notebookâs cells out-of-order. The autograder runs your notebook top-to-bottom. If youâre defining a variable at the bottom of your notebook and using it at the top, the Pensieve autograder will fail because it doesnât recognize the variable when it encounters it.
Additionally, this can fail if you have not saved before you run the autograder. Ensure you select File -> Save Notebook to avoid this.
This is why we recommend running Kernel -> Restart and Run All: it âforgetsâ all of the variables and runs the notebook from top-to-bottom, just like the Pensieve autograder will. This will highlight any issues. Find the first cell that raises an error. Make sure that all of the variables used in that cell have been defined above that cell, and not below.
Why do I get an error saying grader is not defined?
If it has been a while since youâve worked on an assignment, the kernel will shut itself down to preserve memory. When this happens, all of your variables are forgotten, including the grader. Thatâs OK: youâll just need to re-run all of the cells. The easiest way to do this is by using Kernel -> Restart and Run All.
This may also occur if you never ran the top cell of the notebook where the grader is defined.
Iâm positive I have the right answer, but the test fails. Is there a mistake in the test?
While you might see the correct answer displayed as the result of the cell, chances are it isnât being stored in the answer variable. Make sure you are assigning the result to the answer variable. Make sure there are no typos in the variable name.
I accidentally deleted something in a cell that was provided to me â how do I get it back?
There are two solutions:
1. In this public GitHub repository, youâll find the âoriginalâ versions of all assignments we released this semester. You can look here and manually add back any necessary code or text that you accidentally deleted.
2. Suppose youâre working on Lab 5. One solution is go directly to DataHub and rename your lab05 folder to something else, like lab05-old. Then, click the Lab 5 link on the course website again, and itâll bring you to a brand-new version of Lab 5. Then, you can copy your work from your old Lab 5 to this new one, which should have everything in it.
Specific Errors
A general rule of thumb when debugging is to look at the very last line of an error message. Thatâs usually the most informative part of the message, and will often tell you directly whatâs wrong.
... object is not callable
This often happens when you use a default keyword (like str or list) as a variable name, for instance list = [1, 2, 3]. These errors can be tricky because they donât error on their own, but cause problems when we try to use the name list (for example) later on in the notebook.
To fix the issue, identify any such lines of code, change your variable names to be something else, and restart your notebook.
Python keywords like str and list appear in green text, so be on the lookout if any of your variable names appear in green!
SyntaxError at the very beginning of a line of code
Python expected you to continue your last line of code. Typically this means you have mismatched parentheses on the line above the line that is erroring.
DataHub
Why canât I log in to DataHub?
Log out of all Google accounts or open an incognito window. When prompted, enter your full Berkeley email, username@berkeley.edu, as your credentials.
My notebook wonât load. Is DataHub down?
Sometimes DataHub does have availability issues. Usually it is back up and running again within an hour.
In other instances, there are some things you can do to get the notebook running again: Make sure your internet connection is working. If you can, restart your server by clicking the button at the top right labeled âControl Panelâ, then select âStop My Serverâ, followed by âStart My Serverâ.
If that doesnât work, try restarting your computer and using a different browser. Whenever you resume working on a notebook, run all cells youâve previously completed. If your problem persists after trying all these steps, please notify us on Ed.
What if I donât have access to DataHub and I still want to access Data 8 materials?
We welcome the general public to use our materials. If youâre not enrolled in the class, you can access all lectures and assignments in our public GitHub repository. In order to run Jupyter notebooks locally on your own computer, we recommend using Anaconda.
Courtesies to DSC 10: Principles of Data Science and their debugging guide, as it was of great inspiration!