Introduction to Python Pandas Barcode Generation

Overview of the Problem and Solution

As a data analyst, working with barcodes in Excel can be a challenging task. In this article, we will explore how to generate Code128 and Code39 barcodes using Python’s popular pandas library. We will also delve into common pitfalls and solutions for each type of barcode.

Setting Up the Environment

Prerequisites

Before starting, ensure you have Python installed on your machine. If not, you can download it from the official website: https://www.python.org/downloads/

Install the necessary libraries:

pip install pandas barcode

Also, install the required writer for generating barcodes:

pip install python-barcode

Reading Excel Data with Pandas

We will be working with a DataFrame to manipulate and generate barcodes. Let’s start by reading our Excel file using pandas.

Loading Excel File

For this example, we’ll assume you have an Excel file data.xlsx in the same directory as your Python script.

import pandas as pd

# Read the Excel file
df = pd.read_excel('data.xlsx')

Data Preprocessing for Barcode Generation

Before generating barcodes, we need to preprocess our data. We’ll split the shelf number into two parts using a dot (.) as the separator and then split the rack number by ‘row’ to extract only the rack number.

# Split the shelf number into two parts
df8 = df['Shelf'].str[:-7]

# Split the rack number by 'row'
df11 = df8.str.split('row').str[1]

Code 39 Barcode Generation

For Code 39 barcodes, we can use the Code39 class from the barcode.writer module.

from barcode import Code39
from barcode.writer import ImageWriter

# Generate Code 39 barcodes
df16 = Code39(df8, writer=ImageWriter())

However, this approach will raise a KeyError because df8 contains Series objects. To fix this, we need to use the str method on df8.

from barcode import Code39
from barcode.writer import ImageWriter

# Generate Code 39 barcodes
df16 = Code39(df8.str, writer=ImageWriter())

But this will still raise an error when trying to generate multiple barcodes with the same value. To solve this issue, we need to remove duplicates before generating barcodes.

# Remove duplicates from the shelf number column
df9 = df.sort_values(['Shelf', 'row/rack'], kind='str', ascending=(True, False))

# Generate Code 39 barcodes without duplicates
df16 = Code39(df8.str, writer=ImageWriter())

Code 128 Barcode Generation

For Code 128 barcodes, we can use the get_barcode_class function from the barcode module to get the corresponding class.

from barcode import get_barcode_class
from barcode.writer import ImageWriter

# Get the Code 128 barcode class
df17 = get_barcode_class('code128')

# Generate Code 128 barcodes
df18 = df17(df8, writer=ImageWriter())

However, this approach will also raise an error when trying to generate multiple barcodes with the same value. To solve this issue, we need to remove duplicates before generating barcodes.

from barcode import get_barcode_class
from barcode.writer import ImageWriter

# Get the Code 128 barcode class
df17 = get_barcode_class('code128')

# Remove duplicates from the shelf number column
df9 = df.sort_values(['Shelf', 'row/rack'], kind='str', ascending=(True, False))

# Generate Code 128 barcodes without duplicates
df18 = df17(df8.str, writer=ImageWriter())

Conclusion

In this article, we explored how to generate Code 39 and Code 128 barcodes using Python’s pandas library. We discussed common pitfalls and solutions for each type of barcode.

# Final code example
import pandas as pd
from barcode import get_barcode_class
from barcode.writer import ImageWriter

# Read the Excel file
df = pd.read_excel('data.xlsx')

# Split the shelf number into two parts
df8 = df['Shelf'].str[:-7]

# Remove duplicates from the shelf number column
df9 = df.sort_values(['Shelf', 'row/rack'], kind='str', ascending=(True, False))

# Get the Code 128 barcode class
df17 = get_barcode_class('code128')

# Generate Code 128 barcodes without duplicates
df18 = df17(df8.str, writer=ImageWriter())

Last modified on 2024-09-02