5 Ways to Fetch Data from Excel Easily

When it comes to working with data, Excel has long been the standard tool for many professionals and hobbyists alike. The ability to fetch data from Excel efficiently can significantly enhance your workflow, whether you're integrating data into your applications, performing analyses, or automating reporting tasks. In this comprehensive guide, we'll explore five proven methods to fetch data from Excel files easily and effectively.

1. Using Python with Openpyxl Library

Python, with its rich ecosystem of libraries, provides an excellent platform for extracting data from Excel. Here’s how to do it using the openpyxl library:

• Install the Library: Use pip to install openpyxl:

pip install openpyxl

• Load an Excel Workbook: Here’s a snippet of how you can load an Excel file:

from openpyxl import load_workbook



wb = load_workbook(filename=‘data.xlsx’)

• Navigate and Read Data: Access sheets, rows, and cells:

sheet = wb.active



cell_value = sheet[‘A1’].value



for row in sheet.iter_rows(min_row=2, max_col=4, max_row=20):
    for cell in row:
        print(cell.value)

💡 Note: Remember that openpyxl uses a 1-based indexing for both rows and columns.

2. Microsoft Power Automate (formerly Microsoft Flow)

For those familiar with the Microsoft ecosystem, Power Automate offers a GUI-based approach to fetch data:

• Create a Flow: Start a new flow in Power Automate, selecting Excel Online (Business) as one of your triggers.
• Select Data: Use the action ‘Get rows’ to extract data from specified rows and columns.
• Integrate with Other Services: Connect Excel with SharePoint, Teams, or any other app in your workflow.

3. Google Sheets API with Python

If you’re open to transferring your Excel data to Google Sheets for ease of use, Google Sheets API provides a seamless method:

• Setup Google Sheets API: Enable the Sheets API in the Google Developers Console and set up OAuth 2.0.
• Install Google API Client Library:

pip install –upgrade google-api-python-client google-auth-httplib2 google-auth-oauthlib

• Fetch Data: Here’s a basic example to fetch data from Google Sheets:

from googleapiclient.discovery import build
from google.oauth2.credentials import Credentials

creds = Credentials.from_authorized_user_file(‘credentials.json’, SCOPES)
service = build(‘sheets’, ‘v4’, credentials=creds)



sheet = service.spreadsheets()
result = sheet.values().get(spreadsheetId=SPREADSHEET_ID, range=RANGE_NAME).execute()
values = result.get(‘values’, [])

if not values:
    print(‘No data found.’)
else:
    print(‘Name, Major:’)
    for row in values:
        # Print columns A and E, which correspond to indices 0 and 4.
        print(‘%s, %s’ % (row[0], row[4] if len(row) > 4 else “))

4. Visual Basic for Applications (VBA)

VBA, if you’re sticking within the Excel environment, can be very powerful:

• Write a Macro: Automate the process of copying data from one sheet to another or exporting data to other applications.

Sub FetchData()
    Dim wsSource As Worksheet
    Set wsSource = ThisWorkbook.Sheets(“SourceData”)

Dim wsTarget As Worksheet
Set wsTarget = ThisWorkbook.Sheets("TargetData")

Dim lastRow As Long
lastRow = wsSource.Cells(wsSource.Rows.Count, "A").End(xlUp).Row

wsSource.Range("A1:A" & lastRow).Copy Destination:=wsTarget.Range("A1")


End Sub

5. Using C# with EPPlus

For developers working in .NET, EPPlus is a library that allows you to interact with Excel files:

• Install EPPlus:

Install-Package EPPlus

• Open an Excel File and Read Data:

using OfficeOpenXml;
using System.IO;

// Load the Excel file
FileInfo file = new FileInfo(@“path\to\your\file.xlsx”);
using (ExcelPackage package = new ExcelPackage(file))
{
    ExcelWorksheet worksheet = package.Workbook.Worksheets[“Sheet1”];

// Read data
for (int row = 2; row <= worksheet.Dimension.End.Row; row++)
{
    object column1 = worksheet.Cells[row, 1].Value;
    object column2 = worksheet.Cells[row, 2].Value;
    // Process data
}


}

Wrapping up this guide, fetching data from Excel can be streamlined through various methods, each catering to different needs and levels of technical expertise. Whether you're a programmer using Python or C#, an Excel user leveraging VBA, or a workflow enthusiast employing Microsoft Power Automate or Google Sheets API, the tools are out there to make data extraction efficient and less of a hassle. The methods above not only help in fetching data but also enable you to perform further analysis, transformations, and integration into broader systems. This opens up a world of possibilities for data handling, automation, and enhanced productivity. Keep exploring these tools and tailor them to your workflow for the best results in your data-driven projects.

Can I use openpyxl to write to an Excel file as well?

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Yes, openpyxl can be used to both read from and write to Excel files. Here’s how you can write data:

from openpyxl import Workbook

wb = Workbook()
ws = wb.active
ws[‘A1’] = “Some Data”
wb.save(‘example.xlsx’)

What are the limitations of using Power Automate for Excel data extraction?

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The main limitations are:

• Dependence on Microsoft cloud services which might not be suitable for all scenarios.
• Premium connectors or actions might require additional licensing or subscriptions.
• The complexity of setting up workflows can be a barrier for users without technical backgrounds.

Is VBA still relevant for modern data handling in Excel?

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Yes, VBA remains highly relevant for automating tasks within Excel, especially for complex data manipulation and integration with other Office applications. While external programming languages provide more modern alternatives, VBA’s native integration with Excel is still unmatched for some use cases.