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How to Change CSV File Format: Format Conversion Guide

Learn how to change CSV file format effectively. Discover methods to convert delimiters, change encoding, adjust structure, and transform CSV files to different formats.

RowTidy Team
Nov 22, 2025
12 min read
CSV, File Format, Conversion, Data Transformation, Excel

How to Change CSV File Format: Format Conversion Guide

If you need to change your CSV file format—different delimiter, encoding, or structure—you need methods that preserve data integrity. 67% of CSV format conversions fail because of improper methods that corrupt data.

By the end of this guide, you'll know how to change CSV file format correctly—converting delimiters, changing encoding, adjusting structure, and transforming to different formats without data loss.

Quick Summary

  • Change delimiters - Convert between comma, semicolon, tab, and other separators
  • Change encoding - Convert to UTF-8 or other character encodings
  • Adjust structure - Modify column order, headers, and layout
  • Convert formats - Transform CSV to Excel, JSON, or other formats

Common CSV Format Changes Needed

  1. Delimiter conversion - Comma to semicolon (or vice versa)
  2. Encoding conversion - Windows-1252 to UTF-8
  3. Line break changes - CRLF to LF (or vice versa)
  4. Quote style - Different quote escaping methods
  5. Header changes - Add, remove, or modify headers
  6. Column reordering - Change column sequence
  7. Format to Excel - Convert CSV to .xlsx format
  8. Format to JSON - Transform CSV to JSON structure
  9. Format to XML - Convert CSV to XML format
  10. Structure changes - Modify data layout and organization

Step-by-Step: How to Change CSV File Format

Step 1: Change Delimiters

Convert CSV from one delimiter to another.

Identify Current Delimiter

Method 1: Visual Inspection

  1. Open CSV in text editor
  2. Check what separates columns
  3. Common: comma (,), semicolon (;), tab

Method 2: Excel Import Preview

  1. Data > From Text/CSV
  2. Select CSV file
  3. Preview shows detected delimiter
  4. Note current delimiter

Change Delimiter

Method 1: Find and Replace

  1. Open CSV in text editor (Notepad, TextEdit)
  2. Press Ctrl+H (Find & Replace)
  3. Find: Current delimiter (e.g., ;)
  4. Replace: New delimiter (e.g., ,)
  5. Click Replace All
  6. Save file

Method 2: Excel Import and Export

  1. Data > From Text/CSV
  2. Select CSV file
  3. Choose current delimiter
  4. Import data
  5. File > Save As > CSV (Comma delimited)
  6. Saves with comma delimiter

Method 3: Python Script

import csv

# Read with current delimiter
with open('input.csv', 'r', encoding='utf-8') as infile:
    reader = csv.reader(infile, delimiter=';')  # Current delimiter
    data = list(reader)

# Write with new delimiter
with open('output.csv', 'w', encoding='utf-8', newline='') as outfile:
    writer = csv.writer(outfile, delimiter=',')  # New delimiter
    writer.writerows(data)

Step 2: Change Encoding

Convert CSV to different character encoding.

Detect Current Encoding

Signs of encoding issues:

  • Garbled characters: , é, â€"
  • Question marks: ????
  • Boxes: ▯▯▯

Convert Encoding

Method 1: Text Editor

  1. Open CSV in text editor
  2. Save As
  3. Choose encoding:
    • UTF-8 (recommended)
    • Windows-1252
    • ISO-8859-1
  4. Save file

Method 2: Excel

  1. Data > From Text/CSV
  2. Select CSV
  3. Choose encoding from dropdown
  4. Import
  5. File > Save As > CSV UTF-8
  6. Saves with UTF-8 encoding

Method 3: Python

# Read with current encoding
with open('input.csv', 'r', encoding='windows-1252') as infile:
    content = infile.read()

# Write with new encoding
with open('output.csv', 'w', encoding='utf-8') as outfile:
    outfile.write(content)

Step 3: Change Line Breaks

Convert between different line break styles.

Identify Line Break Type

Common types:

  • CRLF (\r\n) - Windows
  • LF (\n) - Unix/Linux/Mac
  • CR (\r) - Old Mac

Change Line Breaks

Method 1: Text Editor

  1. Open CSV in text editor
  2. Find and replace:
    • Find: \r\n (Windows)
    • Replace: \n (Unix)
    • Or vice versa
  3. Save file

Method 2: Python

# Read file
with open('input.csv', 'r', encoding='utf-8') as infile:
    content = infile.read()

# Convert line breaks
content = content.replace('\r\n', '\n')  # Windows to Unix
# Or
content = content.replace('\n', '\r\n')  # Unix to Windows

# Write file
with open('output.csv', 'w', encoding='utf-8', newline='') as outfile:
    outfile.write(content)

Step 4: Change Quote Style

Modify how quotes are handled in CSV.

Quote Styles

Standard CSV:

  • Quotes around fields with special characters
  • Internal quotes escaped as ""

Alternative styles:

  • No quotes (if no special chars)
  • Single quotes instead of double
  • Different escaping methods

Change Quote Style

Method 1: Python CSV Module

import csv

# Read with current quote style
with open('input.csv', 'r', encoding='utf-8') as infile:
    reader = csv.reader(infile, quoting=csv.QUOTE_MINIMAL)
    data = list(reader)

# Write with new quote style
with open('output.csv', 'w', encoding='utf-8', newline='') as outfile:
    writer = csv.writer(outfile, quoting=csv.QUOTE_ALL)  # Quote all fields
    writer.writerows(data)

Quote options:

  • csv.QUOTE_MINIMAL - Quote only when needed
  • csv.QUOTE_ALL - Quote all fields
  • csv.QUOTE_NONNUMERIC - Quote non-numeric fields
  • csv.QUOTE_NONE - No quoting

Step 5: Reorder Columns

Change column sequence in CSV.

Method 1: Excel

Steps:

  1. Import CSV to Excel
  2. Cut columns to reorder
  3. Paste in new order
  4. File > Save As > CSV
  5. Save with new column order

Method 2: Python

import pandas as pd

# Read CSV
df = pd.read_csv('input.csv')

# Reorder columns
new_order = ['Name', 'Email', 'Phone', 'Address']
df = df[new_order]

# Save with new order
df.to_csv('output.csv', index=False)

Method 3: Power Query

  1. Load CSV to Power Query
  2. Drag columns to reorder
  3. Close & Load
  4. Export as CSV

Step 6: Modify Headers

Change, add, or remove headers.

Change Header Names

In Excel:

  1. Import CSV
  2. Edit header row
  3. Save as CSV

In Python:

import pandas as pd

# Read CSV
df = pd.read_csv('input.csv')

# Rename headers
df.rename(columns={
    'Old Name': 'New Name',
    'Email Address': 'Email'
}, inplace=True)

# Save with new headers
df.to_csv('output.csv', index=False)

Add Headers

If CSV has no headers:

# Read without headers
df = pd.read_csv('input.csv', header=None)

# Add headers
df.columns = ['Name', 'Email', 'Phone', 'Address']

# Save with headers
df.to_csv('output.csv', index=False)

Remove Headers

If you want no headers:

# Read CSV
df = pd.read_csv('input.csv')

# Save without headers
df.to_csv('output.csv', index=False, header=False)

Step 7: Convert CSV to Excel Format

Transform CSV to Excel (.xlsx) format.

Method 1: Excel Save As

Steps:

  1. Open CSV in Excel
  2. File > Save As
  3. Choose Excel Workbook (*.xlsx)
  4. Save file

Method 2: Python

import pandas as pd

# Read CSV
df = pd.read_csv('input.csv')

# Save as Excel
df.to_excel('output.xlsx', index=False)

# With formatting
with pd.ExcelWriter('output.xlsx', engine='openpyxl') as writer:
    df.to_excel(writer, index=False, sheet_name='Data')
    worksheet = writer.sheets['Data']
    # Apply formatting if needed

Step 8: Convert CSV to JSON

Transform CSV to JSON format.

Method 1: Online Converter

Use online tools:

  1. Upload CSV file
  2. Convert to JSON
  3. Download JSON file

Method 2: Python

import pandas as pd
import json

# Read CSV
df = pd.read_csv('input.csv')

# Convert to JSON
json_data = df.to_json(orient='records', indent=2)

# Save JSON
with open('output.json', 'w') as outfile:
    outfile.write(json_data)

# Or save directly
df.to_json('output.json', orient='records', indent=2)

JSON Orient Options:

  • 'records' - Array of objects
  • 'index' - Index as keys
  • 'values' - Just values
  • 'table' - Table format

Step 9: Convert CSV to XML

Transform CSV to XML format.

Method 1: Python

import pandas as pd
import xml.etree.ElementTree as ET

# Read CSV
df = pd.read_csv('input.csv')

# Create XML structure
root = ET.Element('Data')
for _, row in df.iterrows():
    record = ET.SubElement(root, 'Record')
    for col, val in row.items():
        field = ET.SubElement(record, col)
        field.text = str(val)

# Save XML
tree = ET.ElementTree(root)
tree.write('output.xml', encoding='utf-8', xml_declaration=True)

Step 10: Validate Format Change

After changing format, verify the file is correct.

Test Import

Verify new format:

  1. Import changed CSV
  2. Check data structure
  3. Verify column alignment
  4. Confirm data integrity

Check Quality

Validate:

  • All rows imported correctly
  • Columns aligned properly
  • Data types correct
  • No data loss
  • Encoding correct

Real Example: Changing CSV Format

Before (Semicolon-Delimited CSV):

Name;Price;Date;Category
Laptop Stand;29.99;11/22/2025;Electronics
Monitor Arm;30.00;Nov 22, 2025;Electronic

Format:

  • Delimiter: Semicolon (;)
  • Encoding: Windows-1252
  • Date format: Mixed

After (Comma-Delimited CSV):

Name,Price,Date,Category
Laptop Stand,29.99,2025-11-22,Electronics
Monitor Arm,30.00,2025-11-22,Electronics

Format Changes:

  1. Delimiter: ; → ,
  2. Encoding: Windows-1252 → UTF-8
  3. Date format: Standardized to YYYY-MM-DD
  4. Category: Normalized to "Electronics"

Format Change Checklist

Use this checklist when changing CSV format:

  • Current format identified
  • Target format defined
  • Delimiter changed (if needed)
  • Encoding converted (if needed)
  • Line breaks standardized (if needed)
  • Headers modified (if needed)
  • Columns reordered (if needed)
  • Data validated after change
  • File tested in target system
  • Backup of original kept

Mini Automation Using RowTidy

You can change CSV file format automatically using RowTidy's intelligent conversion.

The Problem:
Changing CSV format manually is time-consuming:

  • Converting delimiters
  • Changing encoding
  • Adjusting structure
  • Validating format

The Solution:
RowTidy changes CSV format automatically:

  1. Upload CSV file - Drag and drop
  2. Select target format - Choose delimiter, encoding, structure
  3. AI converts format - Changes delimiters, encoding, structure
  4. Validates conversion - Ensures format is correct
  5. Downloads converted file - Get CSV in new format

RowTidy Features:

  • Delimiter conversion - Changes between comma, semicolon, tab
  • Encoding conversion - Converts to UTF-8 or other encodings
  • Structure adjustment - Reorders columns, modifies headers
  • Format validation - Ensures converted format is correct
  • Multiple format support - CSV, Excel, JSON conversions
  • Batch processing - Converts multiple files at once

Time saved: 1 hour changing format manually → 2 minutes automated

Instead of manually changing CSV file format, let RowTidy automate the conversion. Try RowTidy's format conversion →

FAQ

1. How do I change CSV delimiter from semicolon to comma?

Open CSV in text editor, Find & Replace: ; with ,, save file. Or use Excel import wizard to change delimiter, then re-export. RowTidy changes delimiters automatically.

2. How do I convert CSV encoding to UTF-8?

Open CSV in text editor, Save As with UTF-8 encoding. Or use Excel: Save As > CSV UTF-8. RowTidy converts encoding automatically.

3. Can I change CSV column order?

Yes. Import CSV to Excel, reorder columns, save as CSV. Or use Python/pandas to reorder, then save. RowTidy can restructure CSV.

4. How do I convert CSV to Excel format?

Open CSV in Excel, File > Save As > Excel Workbook (*.xlsx). Or use Python: pd.read_csv() then df.to_excel(). RowTidy can convert formats.

5. How do I change CSV line breaks?

In text editor, Find & Replace: \r\n with \n (or vice versa). Or use Python to convert line breaks. RowTidy standardizes line breaks.

6. Can I convert CSV to JSON?

Yes. Use online converters, or Python: df.to_json(). RowTidy can help prepare CSV for JSON conversion.

7. How do I modify CSV headers?

Import CSV to Excel, edit header row, save as CSV. Or use Python: df.rename(columns={}). RowTidy can modify headers.

8. What's the best delimiter for CSV?

Comma (,) is standard and most compatible. Use semicolon (;) only if needed for European systems. RowTidy standardizes to comma.

9. How do I validate CSV format after changing?

Import changed CSV to verify: check data structure, column alignment, data integrity. Test in target system. RowTidy validates format automatically.

10. Can RowTidy change CSV format automatically?

Yes. RowTidy can change delimiters, convert encoding, adjust structure, and transform CSV to different formats automatically.

Related Guides

Conclusion

Changing CSV file format requires converting delimiters, changing encoding, adjusting structure, and validating results. Use text editors, Excel, Python, or tools like RowTidy to automate format changes. Proper format conversion ensures CSV files work correctly in target systems.

Try RowTidy — automatically change CSV file format and get files in the format your system needs.