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Practice: gradebook

Lists, dicts, functions, a file write, and an optional plot.

Attach scores.csv (banner → Add files). Each block is a complete cell. You will parse rows, compute a band, write a report, and optionally plot.

Goal

Produce gradebook.csv with name, score, and band. Print the class average.

1. Read the CSV

import os

print("uploads:", os.listdir("/uploads"))
print(open("scores.csv").read())

2. Parse into dicts

rows = []
with open("scores.csv") as f:
    header = f.readline()
    for line in f:
        line = line.strip()
        if not line:
            continue
        name, raw = line.split(",")
        rows.append({"name": name, "score": int(raw)})
print(rows)
print("average:", round(sum(r["score"] for r in rows) / len(rows), 1))

3. Band each student

def band(score):
    if score >= 90:
        return "A"
    if score >= 80:
        return "B"
    if score >= 70:
        return "C"
    return "D"

rows = []
with open("scores.csv") as f:
    next(f)
    for line in f:
        line = line.strip()
        if not line:
            continue
        name, raw = line.split(",")
        score = int(raw)
        rows.append({"name": name, "score": score, "band": band(score)})

for row in sorted(rows, key=lambda r: r["score"], reverse=True):
    print(f"{row['name']:8} {row['score']:3} {row['band']}")

4. Write the report

def band(score):
    if score >= 90:
        return "A"
    if score >= 80:
        return "B"
    if score >= 70:
        return "C"
    return "D"

rows = []
with open("scores.csv") as f:
    next(f)
    for line in f:
        line = line.strip()
        if not line:
            continue
        name, raw = line.split(",")
        score = int(raw)
        rows.append({"name": name, "score": score, "band": band(score)})

with open("gradebook.csv", "w") as f:
    f.write("name,score,band\n")
    for row in rows:
        f.write(f"{row['name']},{row['score']},{row['band']}\n")
print(open("gradebook.csv").read())

Download gradebook.csv from the chip.

5. Optional plot

import matplotlib.pyplot as plt

def band(score):
    if score >= 90:
        return "A"
    if score >= 80:
        return "B"
    if score >= 70:
        return "C"
    return "D"

rows = []
with open("scores.csv") as f:
    next(f)
    for line in f:
        line = line.strip()
        if not line:
            continue
        name, raw = line.split(",")
        rows.append({"name": name, "score": int(raw), "band": band(int(raw))})

names = [r["name"] for r in rows]
scores = [r["score"] for r in rows]
plt.figure()
plt.bar(names, scores)
plt.axhline(90, linestyle="--")
plt.title("Scores")
plt.show()

Next

You now have Python itself. For tables, groupby, and CSV pipelines, continue with Learn pandas.

You should see

If scores.csv is missing, attach it and run again. FileNotFoundError means the notebook cannot see the file in /uploads.