176. CSV Parsing with DictReader

Snippet 1: Basic CSV Parsing with DictReader

import csv

# Example CSV content
csv_data = """name,age,city
Alice,30,New York
Bob,25,Los Angeles
Charlie,35,Chicago"""

# Writing the CSV content to a file
with open('people.csv', 'w', newline='') as file:
    file.write(csv_data)

# Reading the CSV file with DictReader
with open('people.csv', mode='r') as file:
    reader = csv.DictReader(file)
    for row in reader:
        print(dict(row))

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Snippet 2: Accessing Data by Column Names

import csv

# Example CSV content
csv_data = """name,age,city
Alice,30,New York
Bob,25,Los Angeles
Charlie,35,Chicago"""

# Writing the CSV content to a file
with open('people.csv', 'w', newline='') as file:
    file.write(csv_data)

# Reading the CSV file with DictReader
with open('people.csv', mode='r') as file:
    reader = csv.DictReader(file)
    for row in reader:
        print(f"Name: {row['name']}, Age: {row['age']}, City: {row['city']}")

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Snippet 3: Handling Missing Fields in CSV

import csv

# Example CSV content with a missing "city" field for one row
csv_data = """name,age,city
Alice,30,New York
Bob,25,
Charlie,35,Chicago"""

# Writing the CSV content to a file
with open('people.csv', 'w', newline='') as file:
    file.write(csv_data)

# Reading the CSV file with DictReader
with open('people.csv', mode='r') as file:
    reader = csv.DictReader(file)
    for row in reader:
        print(f"Name: {row['name']}, Age: {row['age']}, City: {row.get('city', 'N/A')}")

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Snippet 4: Specifying Fieldnames in DictReader

import csv

# Example CSV content without headers
csv_data = """Alice,30,New York
Bob,25,Los Angeles
Charlie,35,Chicago"""

# Writing the CSV content to a file
with open('people_no_headers.csv', 'w', newline='') as file:
    file.write(csv_data)

# Defining fieldnames
fieldnames = ['name', 'age', 'city']

# Reading the CSV file with DictReader
with open('people_no_headers.csv', mode='r') as file:
    reader = csv.DictReader(file, fieldnames=fieldnames)
    for row in reader:
        print(f"Name: {row['name']}, Age: {row['age']}, City: {row['city']}")

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Snippet 5: Skipping Rows with DictReader

import csv

# Example CSV content with a header row and extra data rows
csv_data = """name,age,city
# Comment line, not to be processed
Alice,30,New York
Bob,25,Los Angeles
Charlie,35,Chicago"""

# Writing the CSV content to a file
with open('people_with_comments.csv', 'w', newline='') as file:
    file.write(csv_data)

# Reading the CSV file with DictReader and skipping commented lines
with open('people_with_comments.csv', mode='r') as file:
    reader = csv.DictReader(file)
    for row in reader:
        if row['name'].startswith('#'):
            continue
        print(dict(row))

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Snippet 6: Iterating Over Rows as Dictionaries

import csv

# Example CSV content
csv_data = """name,age,city
Alice,30,New York
Bob,25,Los Angeles
Charlie,35,Chicago"""

# Writing the CSV content to a file
with open('people.csv', 'w', newline='') as file:
    file.write(csv_data)

# Reading and iterating over rows as dictionaries
with open('people.csv', mode='r') as file:
    reader = csv.DictReader(file)
    rows = list(reader)
    print(rows)

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Snippet 7: Counting Rows in a CSV File Using DictReader

import csv

# Example CSV content
csv_data = """name,age,city
Alice,30,New York
Bob,25,Los Angeles
Charlie,35,Chicago"""

# Writing the CSV content to a file
with open('people.csv', 'w', newline='') as file:
    file.write(csv_data)

# Counting rows in the CSV file
with open('people.csv', mode='r') as file:
    reader = csv.DictReader(file)
    row_count = sum(1 for row in reader)
    print(f"Total number of rows: {row_count}")

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Snippet 8: Converting CSV Rows to JSON Using DictReader

import csv
import json

# Example CSV content
csv_data = """name,age,city
Alice,30,New York
Bob,25,Los Angeles
Charlie,35,Chicago"""

# Writing the CSV content to a file
with open('people.csv', 'w', newline='') as file:
    file.write(csv_data)

# Converting CSV rows to JSON
with open('people.csv', mode='r') as file:
    reader = csv.DictReader(file)
    data = list(reader)
    json_data = json.dumps(data, indent=4)
    print(json_data)

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Snippet 9: Writing Processed Data to a New CSV with DictWriter

import csv

# Example CSV content
csv_data = """name,age,city
Alice,30,New York
Bob,25,Los Angeles
Charlie,35,Chicago"""

# Writing the CSV content to a file
with open('people.csv', 'w', newline='') as file:
    file.write(csv_data)

# Reading and writing processed data to a new CSV file
with open('people.csv', mode='r') as infile, open('processed_people.csv', mode='w', newline='') as outfile:
    reader = csv.DictReader(infile)
    fieldnames = reader.fieldnames
    writer = csv.DictWriter(outfile, fieldnames=fieldnames)
    writer.writeheader()
    
    for row in reader:
        row['age'] = int(row['age']) + 1  # Adding 1 to the age for each person
        writer.writerow(row)

print("Processed data written to 'processed_people.csv'")

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Snippet 10: Sorting Rows in a CSV Using DictReader

import csv

# Example CSV content
csv_data = """name,age,city
Alice,30,New York
Bob,25,Los Angeles
Charlie,35,Chicago"""

# Writing the CSV content to a file
with open('people.csv', 'w', newline='') as file:
    file.write(csv_data)

# Sorting rows by age
with open('people.csv', mode='r') as file:
    reader = csv.DictReader(file)
    sorted_rows = sorted(reader, key=lambda row: int(row['age']))
    for row in sorted_rows:
        print(row)