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Python words in plain language

Assignment and type
frames = 96 binds a name to an integer. "96" is text, not the same numeric value. Values and names.
List and index
A list keeps items in order. Positions start at zero; the final nonnegative index is length minus one. List lookups.
Loop and indentation
A for loop processes each item. Indentation groups its repeated statements; a statement outside the block runs separately. Loops.
Parameter, argument and Return
A parameter names an input in a definition; an argument supplies its value in a call. Return gives a result to the caller; print displays it. A function that only prints returns None. Functions.
Dictionary and schema
A dictionary labels values with keys. A schema states the required fields and types; a missing fact is not automatically zero. Dictionaries · Validation.
File, CSV and JSONL
A file stores bytes/text. CSV needs a quoting-aware parser; JSONL contains one JSON value per line. Browser practice files are temporary, not computer files. CSV · JSONL.
Denominator and evidence
A rate divides a count by its declared eligible total. Keep exclusions visible. A quiz score, practical check and self-review are different evidence. Quality rates.

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SyntaxError / IndentationError
Python could not parse the code. Inspect the named line and the preceding line for a missing colon, unmatched quote/bracket or inconsistent indentation. Review blocks.
NameError
A name has no value here. Compare case and spelling, and check that assignment happens before use. Do not replace an unknown parameter with a fixed sample.
TypeError / ValueError
A wrong kind of value or an unacceptable value can fail an operation. Inspect the supplied input and declared policy; do not broadly suppress the error. Narrow error handling.
IndexError / KeyError
The requested position or key is missing. Inspect the collection and interface instead of guessing a fallback. Indices · Keys.
Run stays loading / runtime or checker unavailable
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Expected sample prints, but a check fails
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← Route Week 6 · Day 27 of 40

Filtering rows

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Lesson idea Tap to fold
Recall

What does a comparison such as score >= 4 produce?

Show the answer

A Boolean value—True or False—for each value being compared.

Today

A mask makes one decision for every row

A Series comparison returns a boolean Series with one decision per row. df[mask] selects its True rows; df.loc[mask] is another valid form. The result follows row order and index alignment, not an assumed zero-based position.

For two conditions, use & for elementwise AND and | for elementwise OR. Put parentheses around each comparison. Python and/or instead try to obtain one overall truth value from a Series and raise an ambiguous-truth error.

These examples assume numeric duration/score and boolean artifact facts, with missing numeric values excluded by the comparison. Exactly four qualifies for score >= 4; exactly eight qualifies for duration <= 8. The task is a classroom shortlist rule, not an authoritative delivery judgment.

# A mask makes one decision for every row.
import pandas as pd

df = pd.DataFrame([
    {"item_id": "Museum", "score": 4, "artifact": False},
    {"item_id": "Canal", "score": 5, "artifact": True},
])
mask = (df["score"] >= 4) & (df["artifact"] == False)
selected = df.loc[mask]
print(selected["item_id"].tolist())

Only ['Museum'] remains. Canal’s high score cannot overcome its artifact flag because both conditions are required.

Test the exact boundary and a row that meets only one condition. A familiar sample list is not proof that the mask works.

Official pandas 2.2 reference for this lesson

Predict, explain, then test

These three brief checks are self-reviewed, not scored. Answer before opening the comparison. Coding checks use unfamiliar tables under the stated task assumptions.

Trace the boundary

Does score exactly 4 satisfy score >= 4?

Compare your answer · self-reviewed

Yes. A strict > comparison would implement a different rule.

Choose an operator

Why is Python and wrong between two Series comparisons?

Compare your answer · self-reviewed

It asks for one truth value for the Series. Use elementwise & with parentheses.

Check order

Does filtering automatically sort the matching item IDs?

Compare your answer · self-reviewed

No. Filtering retains their current row order; sorting is a separate operation.

Now

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day-27.py Python + pandas · runs in this browser
Output

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