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From Spreadsheet to Garment Tag

Python Automation for Fashion Archives

Caution

DISCLAIMER OF FACTUAL ACCURACY

The dataset provided in this repository is designed purely for demonstration and practice coding purposes. While the general scenario and structure may be inspired by real-world experiences of the author, all identifying information, specific details, names, entities, and events have been significantly modified, abstracted, and fictionalized.

The data does not represent an exact factual account of any specific case, person, or entity. It has been altered solely to protect privacy and provide a generalized, abstract scenario for educational use.

Users should not draw real-world conclusions, apply this data as factual information, or use it for any purpose other than practicing code. We disclaim all liability for any reliance on this information as fact.

Introduction

This tutorial teaches archivists to automate garment label creation using Python. We'll transform a CSV spreadsheet into professional bag tags for fashion collections, processing 30 items into a print-ready PDF document in seconds rather than hours. You need to have a Google Account to run this on Google Colab/if you have Visual Studio Code, the code should run perfectly fine.

Before and After: Manual vs Automated Label Creation with no paper errors
From hours of manual work to minutes of automation
The Issue

Picture this: You're in a fashion archive storage room with 500 garments in protective bags on racks. A researcher needs "the purple McFadden evening dress from 1989." Without external tags, you'd have to:

The traditional method of creating these tags > typing each row individually in Word, is painfully slow. For 30 garments, this means:

graph LR
    %% Define the Top 3 Steps (Nodes A, B, C)
    A[1. Opening Word] --> B[2. Typing identifier, designer, description];
    B --> C[3. Formatting each label];

    %% Define the Bottom 2 Steps (Nodes D, E)
    D[4. Finding and inserting images] --> E[5. Copying and pasting into a grid];

    %% Connect the steps horizontally
    C --> D;

    %% Create the Cycle (Right to Left) with Annotation
    E -.->|Repeat 30 times...| A;

    %% Adjust styling for the loop annotation (optional: makes the loop line dotted)
    linkStyle 4 stroke-dasharray: 5 5;
Loading

This chart was made with mermaid chart

This tutorial automates the entire process and reduces paper waste from the margin of error we might have. What took 3-4 hours now takes ~15 minutes with a prepared .csv and images.

Sample Data

Use the included files in the 'Resource' Folder:

  • Garment_Bag_Tag_Dataset.csv file, which contains garment records.
  • Image Set.zip with 27 image files in .jpg format
  • the Google Colab or The Spreadsheet to Garment Tag automation code

Important

Please review the Dataset Usage Rights before using any images.

A Note About Images

Important: The photos on these tags are for quick identification, not publication. A phone photo taken in storage is perfectly adequate.

Dataset Considerations

Before starting, consider your collection size:

  • Medium (4-100 items): Perfect for this tutorial
  • Large (>100 items): Process in batches

--

Ready? Let's begin by opening the Google Colab below in a new tab.

Important

You need a Pratt Gmail account to access this Google Colab!

Open In Colab

📝 Note: If you are ready to make your own? Read the Customization Guide for data preparation tips.