Merge Multiple CSV Files: Complete Guide

Last updated: March 2026 • 6 min read

Need to combine data from multiple CSV files? This guide covers every scenario from simple stacking to complex joins with different column structures.

Types of CSV Merges

1. Vertical Stack (Append)

Add rows from one file below another. Files should have the same columns.

2. Horizontal Join

Combine columns from different files based on a common key (like VLOOKUP).

Method 1: Command Line (Fast)

# Stack files (skip headers except first file)
head -1 file1.csv > merged.csv
tail -n +2 -q *.csv >> merged.csv

# Or simpler if headers are identical
cat *.csv > merged.csv

Method 2: Python Pandas

import pandas as pd
import glob

# Stack all CSVs in a folder
files = glob.glob('data/*.csv')
df = pd.concat([pd.read_csv(f) for f in files])
df.to_csv('merged.csv', index=False)

# Join on a key column
df1 = pd.read_csv('customers.csv')
df2 = pd.read_csv('orders.csv')
merged = pd.merge(df1, df2, on='customer_id', how='left')
merged.to_csv('customer_orders.csv', index=False)

Method 3: Excel Power Query

1. Data → Get Data → From File → From Folder
2. Select folder containing CSVs
3. Click "Combine & Transform"
4. Power Query will stack all files automatically

Handling Mismatched Columns

When files have different columns:

# Pandas handles this automatically
df = pd.concat([pd.read_csv(f) for f in files], 
               ignore_index=True, 
               sort=False)
# Missing columns become NaN