Python Looping Through Excel Sheets for Data Extraction and Formatting

Python, with its extensive libraries such as Pandas and OpenPyXL, provides robust tools for handling Excel files, enabling efficient data manipulation and analysis. This article discusses how to loop through an Excel sheet using Python, extract data, and format the output with a specific structure: title, content, and tags.

To start, ensure you have Pandas installed in your Python environment. If not, you can install it using pip:

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pip install pandas

Let’s assume we have an Excel file named data.xlsx with multiple sheets, and each sheet contains data in columns titled “Title”, “Content”, and “Tags”. Our goal is to loop through each sheet, read the data, and print it in a formatted manner.

Here’s how you can achieve this:

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import pandas as pd

# Load the Excel file

file_path = 'data.xlsx'

xlsx = pd.ExcelFile(file_path)
# Loop through each sheet in the Excel file

for sheet_name in xlsx.sheet_names:

    # Read the sheet into a DataFrame

    df = pd.read_excel(xlsx, sheet_name=sheet_name)
    # Iterate through each row in the DataFrame

    for index, row in df.iterrows():

        title = row['Title']

        content = row['Content']

        tags = row['Tags']
        # Print the formatted output

        print(f"[title] {title}")

        print(f"
As I write this, the latest version of Python is 3.12.4







	Tags: 
{tags}\n")and "Tags" and prints them in the specified format.and loops through each row in the DataFrame. For each rowcontentit extracts the "Title"reads the sheet into a DataFrameThis script starts by loading the Excel file into a pandas.ExcelFile objectwhich provides an interface for accessing the individual sheets. It then iterates through each sheet name





	

			

	

		

							
				Sam Emma	
				
						

		
		
		

					

		

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