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Week 4 Checkpoint: Data Wrangling and the Capstone Pipeline — Python For Researchers

Day 29 · ~11 min●

Five days, five functions, one capstone pipeline. analysis_pipeline calls every function you've written in this track. How does that feel?

Like the entire track snapped into place. safe_compute_outcome fixes the messy rows. filter_eligible applies the pre-registration. rank_groups_by_outcome builds the table. The capstone just chains them.

That's the arc of every data pipeline: repair, filter, aggregate, rank, report. You've written each piece from scratch and you understand why it exists. How does the error handling feel now?

Natural. try/except (KeyError, ValueError) is the same instinct as checking for missing values before running Descriptives in SPSS — except it's explicit and version-controlled.

Explicit, version-controlled, and Reviewer-2-proof. Six questions — four from this week, two reviewing Weeks 1–3. Review questions marked [REVIEW].

Ready.

Repair, filter, aggregate, rank, report — you wrote all five from scratch. Week 4 locked in.

Quiz

0/6

6 questions80% to passretry anytime

1.What does [r for r in respondents if r.get('outcome') is not None] do differently from [r for r in respondents if r['outcome']]?

They are identical — both filter out respondents without an outcomeThe first includes respondents with outcome=0.0; the second excludes themThe first raises KeyError for missing keys; the second does notThe second uses .get() which is slower than bracket access

2.What does re.findall(r'"id":\s*"([^"]+)"', raw_text) return when raw_text = '{"id": "R_001"}'?

['{"id": "R_001"}']['R_001']['"id": "R_001"']None

3.In rank_groups_by_outcome, the sort key is lambda x: x[1]['mean_outcome']. What does x[1] refer to?

The second character of the group name stringThe second respondent in the group's listThe stats dict in a (group_name, stats_dict) tuple from .items()The second key in the summary dict

4.What does safe_compute_outcome({"id": "R_003", "outcome": ""}) return?

""0.0NoneValueError

5.[REVIEW] What does treatment_summary([]) return?

def treatment_summary(respondents):
    groups = group_by_treatment(respondents)
    summary = {}
    for group, members in groups.items():
        ...
    return summary

An empty dict {}NoneA ZeroDivisionErrorAn empty list []

6.[REVIEW] Which is the correct way to open and read a CSV as a dict in Python?

import csv, io
csv_text = "id,age\nR_001,29"

csv.DictReader(csv_text)csv.DictReader(open(csv_text))csv.DictReader(io.StringIO(csv_text))csv.reader(io.StringIO(csv_text), as_dict=True)