Dictionary-based CSV handling in Python - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to open a CSV file for reading using a dictionary reader.

Python

import csv
with open('data.csv', [1]) as file:
    reader = csv.DictReader(file)
    for row in reader:
        print(row)

Drag options to blanks, or click blank then click option'

A'x'

B'r'

C'a'

D'w'

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'w' or 'a' mode instead of 'r' causes errors or overwrites the file.

To read a CSV file, you open it in read mode using 'r'.

2fill in blank

medium

Complete the code to write a list of dictionaries to a CSV file using DictWriter.

Python

import csv
fieldnames = ['name', 'age']
data = [{'name': 'Alice', 'age': 30}, {'name': 'Bob', 'age': 25}]
with open('output.csv', 'w', newline='') as file:
    writer = csv.DictWriter(file, fieldnames=[1])
    writer.writeheader()
    writer.writerows(data)

Drag options to blanks, or click blank then click option'

Afieldnames

Bfile

Cwriter

Ddata

Attempts:

3 left

💡 Hint

Common Mistakes

Passing the data list instead of the fieldnames list to DictWriter.

The fieldnames parameter tells DictWriter the order and names of columns.

3fill in blank

hard

Fix the error in the code to correctly read and print the 'age' from each row in the CSV.

Python

import csv
with open('people.csv', 'r') as file:
    reader = csv.DictReader(file)
    for row in reader:
        print(row[[1]])

Drag options to blanks, or click blank then click option'

Arow['age']

B'name'

Cage

D'age'

Attempts:

3 left

💡 Hint

Common Mistakes

Using variable names without quotes as dictionary keys.

Trying to use row['age'] inside the brackets.

To access the 'age' value in each row dictionary, use the key as a string: 'age'.

4fill in blank

hard

Fill both blanks to create a dictionary comprehension that maps names to ages from a list of rows.

Python

rows = [{'name': 'Anna', 'age': '22'}, {'name': 'Ben', 'age': '28'}]
name_age = { [1]: [2] for row in rows }

Drag options to blanks, or click blank then click option'

Arow['name']

Brow['age']

Attempts:

3 left

💡 Hint

Common Mistakes

Swapping keys and values in the comprehension.

Using the same expression for both key and value.

The dictionary comprehension uses row['name'] as key and row['age'] as value.

5fill in blank

hard

Fill all three blanks to filter rows where age is greater than 25 and create a dictionary of name to age.

Python

rows = [{'name': 'Cara', 'age': 24}, {'name': 'Dave', 'age': 30}, {'name': 'Eve', 'age': 27}]
filtered = { [1]: [2] for row in rows if row[[3]] > 25 }

Drag options to blanks, or click blank then click option'

Arow['name']

Brow['age']

C'age'

D'name'

Attempts:

3 left

💡 Hint

Common Mistakes

Using the wrong key in the filter condition.

Swapping keys and values in the dictionary comprehension.

The comprehension uses row['name'] as key, row['age'] as value, and filters where row['age'] > 25.