Debug wrong column names in the study table and plot

Do not start with a speculative fix for the study table and plot. Force the failure on purpose, save the before output, then change one cause at a time. Retries are allowed only for transient conditions—not for bad input that will fail forever on data-tables-and-plots.

import pandas as pd, io
try:
    df=pd.read_csv(io.StringIO('hourz,passed\n1,0\n'))
    assert {'hours','passed'}<=set(df.columns)
except AssertionError:
    print('caught bad column names')

Expected evidence: caught bad column names. If you cannot reproduce on demand, you do not yet control the failure mode for data-tables-and-plots.

After repair, rerun the exact reproduction command. Keep the failing fixture as a regression seed for the observability page. For the study-hours table plus hours-vs-pass plot, remember the claim you are restoring: CSV summaries and a saved plot file have explicit axes and a reproducible path.

Store a one-command reproduction for: wrong column names, or a plot that saves without axis labels. The command should use four-row study.csv with hours and passed columns or a minimal mutant of it. Paste the failing output into notes/failure-before.txt (or your shell scrollback as copied text). After the fix, paste notes/failure-after.txt and keep both.

Retries belong only on transient faults. If the failure is bad input, a bad allowlist, or a logic bug in the study table and plot, retrying will amplify cost without repairing trust around inspect typical hours, an extreme value, and the hours/pass relationship.

Classify the failure as prevent, detect, contain, or recover—using this lab’s language, not a generic poster. For data-tables-and-plots, the first fix should usually be detect+prevent at the boundary, because wrong column names, or a plot that saves without axis labels is cheaper to stop early than to explain in production prose.

At the debugging stage for data-tables-and-plots, the job is narrower than finishing a product demo. You are creating one progressive evidence piece about four-row study.csv with hours and passed columns that later pages inherit without redefining success. Keep that fixture small enough to inspect by hand, keep outputs copy-pasteable as text, and refuse to narrate this baseline as if it were a production SLA: hand-computed mean of the four-row fixture.

For this page specifically, success looks like before/after evidence for the characteristic failure while still centering the user decision to inspect typical hours, an extreme value, and the hours/pass relationship. If you cannot point to a file, command, or assertion that proves that for the study table and plot, stay on this page instead of advancing.

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