session-02-part-02.md

Session 2 | Part 2

In Session 2, we start working with CSV files using dictionary-style rows. This is quite different from arrays, because we can use column names as keys to access data (not indexes anymore).

1. Goal

First, you will practice core CSV dictionary logic using:

• csv.DictReader
• key-based access (for example row["title"])
• counters
• for loops
• break for first-match search

2. Prerequisites

Before starting:

1. Open the session2 folder in Visual Studio Code.
2. Create and activate your virtual environment:

python3 -m venv .venv
source .venv/bin/activate

Windows PowerShell:

python -m venv .venv
.venv\Scripts\Activate.ps1

3. Install requirements:

pip install -r requirements.txt

4. Create your exercise file inside session2/solutions, for example:

session2/solutions/exercise-02-01.py

3. Basics you should know

The csv.DictReader(file) reads each CSV row as a dict (dictionary). Keys come from the header row (column names). Values are still strings, so numeric conversion is manual when needed.

Let's start with the basics of dictionaries.

A Python dictionary lets you store data as key → value pairs (like word → meaning). Instead of using numbers like lists, you use names (keys) to find values, which is easier to read and understand.

person = {
    "name": "Stelios",
    "age": 20, # I wish
    "city": "London"
}

Access values

print(person["name"])   # Stelios

Add or change values

person["job"] = "Developer"   # add new
person["city"] = "Athens"     # update

Remove values

del person["city"]

Loop through dictionary using items()

for key, value in person.items():
    print(key, value)

4. Read CSV rows as dictionaries

To run this tutorial, first download movies.csv from the Hugging Face repo: Birkbeck/movies

hf download Birkbeck/movies movies.csv --repo-type dataset --local-dir .

Expected result: movies.csv appears in your current folder.

Run your scripts from the session2 folder, so open("movies.csv", "r") works directly. If you run from the bda root folder instead, use open("session2/movies.csv", "r").

Let's create our first script. File: session2/solutions/exercise-02-01.py

import csv

with open("movies.csv", "r") as file:
    reader = csv.DictReader(file)
    for row in reader:
        print(row)

Expected output shape:

{'movie_id': '1', 'title': 'Movie 1', 'year': '2020', ...}
{'movie_id': '2', 'title': 'Movie 2', 'year': '1994', ...}

Tip

What are the time and space complexities of this script?

Show answer

Time: O(n)

Space: O(1)

5. Print one named column

File: session2/solutions/exercise-02-01.py

import csv

with open("movies.csv", "r") as file:
    reader = csv.DictReader(file)
    for row in reader:
        print(row["genres"])

Expected output shape:

Romance
Action, 
Animation, 
Thriller
...

Tip

What are the time and space complexities of this script?

Show answer

Time: O(n)

Space: O(1)

6. Count rows using a counter

Count how many rows are from 2020. Complete the missing code.

File: session2/solutions/exercise-02-01.py

import csv

count = 0

with open("movies.csv", "r") as file:
    reader = csv.DictReader(file)
    ...

print(count)

Tip

Show solution

...
for row in reader:
    if row["year"] == "2020":
        count += 1
...

7. Find first match with break

Find the first row where genres contains Action. Fill up the missing code.

File: session2/solutions/exercise-02-01.py

import csv

with open("movies.csv", "r") as file:
    reader = csv.DictReader(file)
    for row in reader:
      ...

Tip

What are the time and space complexities of this script?

Show answer

Time: O(n) worst case

Space: O(1)

...
if "Action" in row["genres"]:
   print(row)
   break
...

8. Call Stelios for a quick challenge 🔥

Call Stelios for a quick challenge question before moving to the exercise.

9. Exercise

Add your answers to:

session2/solutions/exercise-02-01.py

Use the Birkbeck/movies dataset from Hugging Face.

1. Examine the field names using reader.fieldnames. Print the names.
2. Print only the first 5 data rows.
3. Count how many movies are from the USA.
4. Find and print the first movie where genres is exactly Action.
5. Find and print the first movie where Action appears inside genres.
6. In one short comment, explain one benefit of DictReader over csv.reader.
7. What are the time and space complexities of your script(s)?

Use the Birkbeck/movies_incomplete dataset from Hugging Face. Download it into a separate folder so it does not overwrite movies.csv:

mkdir -p data/movies_incomplete
hf download Birkbeck/movies_incomplete movies.csv --repo-type dataset --local-dir data/movies_incomplete

1. Find the missing data point and print row and column.
2. Find the average of votes from data/movies_incomplete/movies.csv. Why does the naive script fail? How can you fix it?

10. Quiz

Complete the following quiz.

quizmd quizzes/python-csv-dictreader-quiz.md

If you want to choose a theme:

quizmd --theme light quizzes/python-csv-dictreader-quiz.md
quizmd --theme dark quizzes/python-csv-dictreader-quiz.md