Extract Matching Data from Two Files Using Python

This tutorial explains how to use Python and the pandas library to extract matching data from two files.

Step 1: Import Necessary Libraries

import pandas as pd

Step 2: Read Input Files

Load the data from your files using pandas.read_csv(). Assume the files are tab-separated (TSV) and encoded in Latin-1.

# Reading the first file
df1 = pd.read_csv('File1.txt', sep='\t', encoding='latin1')

# Reading the second file
df2 = pd.read_csv('File2.txt', sep='\t', encoding='latin1')

Step 3: Extract Matching Data

Filter rows in df2 where values in the column1 match the values in column1 of df1.

# Extracting matching data
matching_data = df2[df2['column1'].isin(df1['column1'])]

Step 4: Save the Extracted Data

Save the matching data to a new file.

# Saving the extracted data
matching_data.to_csv('extracted_data.txt', sep='\t', index=False)

Example

Here is an example using species data:

Input Files

File1.txt (list of species to extract):

Specie
Species_A
Species_C

File2.txt (data with species and codes):

Specie     Code
Species_A  ABC123
Species_B  DEF456
Species_C  GHI789

Extracted Data

The script will produce a file named extracted_data.txt with the following content:

Specie      Code
Species_A   ABC123
Species_C   GHI789

Usage Notes

1. Ensure your input files are in the correct format (e.g., TSV or CSV).
2. Adjust the column names and encoding as necessary to match your data.
3. Verify that the column names in both files are consistent.

Summary

Using pandas, this script efficiently matches data between two files and saves the result in a new file. Adjust the file names, column names, and formats to suit your dataset.