Mission 09 / CAPSTONE / CROSS-DISCIPLINE

Integrated Engineering Missions

Turn invented UAS telemetry into a small, reproducible Pandas report and save the result to a learner portfolio.

Starter lesson30 min

Briefing

Summarize a synthetic telemetry mission

An engineering mission combines data ingestion, transformation, validation, and communication. This starter processes a fixed synthetic flight sample entirely in the browser.

State the source and scope

The CSV below is invented and contains three observations from two zones. A useful report preserves its source, field meanings, and the exact selection rule applied. Never use classified, CUI, or sensitive operational data in this public learning environment.

Transform reproducibly

Pandas reads the CSV and groups samples by zone. Reproducible code makes the transformation reviewable. For a larger mission, a later capstone can load cleaned records into PostgreSQL and compare query results with the Python report.

Save an artifact

Passing this exercise saves your submitted code and result to your private MissionStack portfolio. The portfolio record is scoped to the signed-in learner; public sharing and report export are not implemented yet.

Practical exercise

Run the mission

Use Pandas to count the synthetic samples by zone and print `north:2,south:1`.

Progressive hint

Read the `zone` column from `csv_data`, group by zone, and count rows. Keep the output concise and reproducible.

Need another hint?

The synthetic sample contains two north rows and one south row; return groups in alphabetical order.

Sample data · synthetic CSV

sample,zone,altitude_m,mode
1,north,14,hold
2,north,18,hold
3,south,12,land

import pandas as pd
from io import StringIO

telemetry = pd.read_csv(StringIO(csv_data))
counts = telemetry.groupby("zone").size().sort_index()
print(",".join(f"{zone}:{count}" for zone, count in counts.items()))

import pandas as pd
from io import StringIO

telemetry = pd.read_csv(StringIO(csv_data))
counts = telemetry.groupby("zone").size().sort_index()
print(",".join(f"{zone}:{count}" for zone, count in counts.items()))

Output

Run the starter to see observable output. Code is saved in this browser.

Pyodide · Python in WebAssembly · isolated short-lived browser worker

Passing work is graded by the academy and saved to your private portfolio when you submit it.

Knowledge check

What kind of data belongs in this public training mission?

Pass both checks to save progress and earn 175 XP.