When working with CSV files in Python, you often need to filter and write specific rows to a new file, including handling headers properly. This blog post will guide you through the process using Python’s csv module.

Reading and Writing CSV Files

The csv module in Python provides functionality to read from and write to CSV files. Here’s a step-by-step guide to filter rows based on a condition and include a custom header in the output file.

Example Scenario

Suppose you have a CSV file with multiple rows and columns, and you want to filter rows based on a specific condition in one of the columns. Additionally, you need to ensure the header is written correctly.

Step-by-Step Solution

1. Import the Required Module

First, import the csv module:

import csv

2. Define File Paths

Specify the input and output file paths:

input_file_path = 'path/to/input_file.csv'
output_file_path = 'path/to/output_file.csv'

3. Read the Header and Data

Read the CSV file and extract the header and rows:

with open(input_file_path, 'r', encoding='utf8') as file:
    reader = csv.reader(file)
    header = next(reader)  # Read the header row
    rows = list(reader)    # Read the remaining rows

4. Filter Rows Based on a Condition

Filter the rows based on a specific condition. For example, if you want to select rows where the value in the 5th column is '1':

filtered_rows = [row for row in rows if row[4] == '1']

5. Write the Header and Filtered Rows to a New File

Open the output file and write the header and filtered rows:

with open(output_file_path, 'w', encoding='utf8', newline='') as file:
    writer = csv.writer(file)
    writer.writerow(header)  # Write the header
    writer.writerows(filtered_rows)  # Write the filtered rows

Complete Example

Here is the complete code:

import csv

input_file_path = 'path/to/input_file.csv'
output_file_path = 'path/to/output_file.csv'

with open(input_file_path, 'r', encoding='utf8') as file:
    reader = csv.reader(file)
    header = next(reader)  # Read the header row
    rows = list(reader)    # Read the remaining rows

filtered_rows = [row for row in rows if row[4] == '1']

with open(output_file_path, 'w', encoding='utf8', newline='') as file:
    writer = csv.writer(file)
    writer.writerow(header)  # Write the header
    writer.writerows(filtered_rows)  # Write the filtered rows

Handling Extra New Lines

If you encounter extra new lines in your output file, you can ensure that the newline='' parameter is used when opening the output file. This prevents additional blank lines from appearing in the CSV.

Conclusion

Handling CSV files in Python involves reading, filtering, and writing data effectively. By using the csv module, you can easily manipulate CSV files and include custom headers in your output. This approach ensures that you have precise control over the data you work with and produce clean, formatted CSV files.