Python Programming Working With Csv And Json Files Complete Guide

1. How do you read a CSV file in Python?

Answer: To read a CSV file in Python, you can use the csv module. Here's a simple example:

import csv

with open('filename.csv', mode='r') as file:
    csv_reader = csv.reader(file)
    for row in csv_reader:
        print(row)

2. How can you write to a CSV file in Python?

Answer: To write to a CSV file, you also use the csv module. Here's how you can write a list of data to a CSV file:

import csv

data = [['Name', 'Age', 'City'], ['Alice', 28, 'New York'], ['Bob', 22, 'Los Angeles']]

with open('filename.csv', mode='w', newline='') as file:
    writer = csv.writer(file)
    for row in data:
        writer.writerow(row)

3. How do you handle CSV files with headers in Python?

Answer: Use csv.DictReader and csv.DictWriter to handle CSV files with headers.

Reading:

import csv

with open('filename.csv', mode='r') as file:
    csv_reader = csv.DictReader(file)
    for row in csv_reader:
        print(row['Name'], row['Age'], row['City'])

Writing:

import csv

data = [
    {'Name': 'Alice', 'Age': 28, 'City': 'New York'},
    {'Name': 'Bob', 'Age': 22, 'City': 'Los Angeles'}
]

with open('filename.csv', mode='w', newline='') as file:
    fieldnames = ['Name', 'Age', 'City']
    writer = csv.DictWriter(file, fieldnames=fieldnames)
    writer.writeheader()
    for row in data:
        writer.writerow(row)

4. How do you read a JSON file in Python?

Answer: Use the json module to read JSON files. Here's an example:

import json

with open('filename.json', 'r') as file:
    data = json.load(file)
    print(data)

5. How can you write to a JSON file in Python?

Answer: Similarly, the json module can be used to write data to a JSON file.

import json

data = {
    "people": [
        {"name": "Alice", "age": 28, "city": "New York"},
        {"name": "Bob", "age": 22, "city": "Los Angeles"}
    ]
}

with open('filename.json', 'w') as file:
    json.dump(data, file, indent=4)

6. How do you handle complex data structures (nested dictionaries/lists) in CSV/JSON?

Answer: CSV is primarily suited for tabular data. Complex nested structures are better handled in JSON. Here’s how to manage nested dictionaries in JSON:

import json

nested_data = {
    "name": "Alice",
    "age": 28,
    "address": {
        "street": "123 Main St",
        "city": "New York"
    },
    "hobbies": ["reading", "cycling", "coding"]
}

with open('nested_data.json', 'w') as file:
    json.dump(nested_data, file, indent=4)

7. How do you handle errors and exceptions when working with CSV and JSON files in Python?

Answer: Use try-except blocks to catch common I/O and parsing errors.

import csv
import json

try:
    with open('filename.csv', 'r') as file:
        csv_reader = csv.reader(file)
        for row in csv_reader:
            print(row)
except FileNotFoundError:
    print("CSV file not found.")
except csv.Error as e:
    print(f"Error reading CSV file at line {csv_reader.line_num}: {e}")

try:
    with open('filename.json', 'r') as file:
        data = json.load(file)
        print(data)
except FileNotFoundError:
    print("JSON file not found.")
except json.JSONDecodeError as e:
    print(f"Error decoding JSON: {e}")

8. How do you convert a CSV file to a JSON file and vice versa in Python?

Answer: CSV to JSON:

import csv
import json

csv_data = []
with open('filename.csv', mode='r') as file:
    csv_reader = csv.DictReader(file)
    for row in csv_reader:
        csv_data.append(row)

with open('data.json', 'w') as file:
    json.dump(csv_data, file, indent=4)

JSON to CSV:

import csv
import json

with open('data.json', 'r') as file:
    data = json.load(file)

keys = data[0].keys()
with open('output.csv', 'w', newline='') as file:
    dict_writer = csv.DictWriter(file, fieldnames=keys)
    dict_writer.writeheader()
    dict_writer.writerows(data)

9. How do you append data to an existing CSV and JSON file?

Answer: Appending to CSV:

import csv

new_data = ['Charlie', 35, 'Chicago']

with open('filename.csv', mode='a', newline='') as file:
    writer = csv.writer(file)
    writer.writerow(new_data)

Appending to JSON (not directly possible; you need to read, modify, and rewrite):

import json

new_person = {"name": "Charlie", "age": 35, "city": "Chicago"}

with open('filename.json', 'r') as file:
    data = json.load(file)

data['people'].append(new_person)

with open('filename.json', 'w') as file:
    json.dump(data, file, indent=4)

10. What are some best practices for working with CSV and JSON files in Python?

Answer:

• Always check file paths and existence to avoid errors.
• Use appropriate encoding (commonly UTF-8) to prevent character issues.
• Close files after operations or use with statements (context managers).
• Handle exceptions gracefully to ensure robust error management.
• Keep JSON files readable and maintainable by using indentation.
• Use CSV headers for readability and avoid mixing data types in CSV columns.
• Validate JSON data before processing to ensure correct structure.