How to Extract Data from Multiple Online Sources

in #method • 7 hours ago

Moving data from a website to Excel can be ridiculously simple—or an absolute nightmare. Dynamic content, login walls, CAPTCHAs, bot traps… one misstep, and your spreadsheet ends up empty.
If your goal is Wikipedia or another cooperative site, Excel alone might do the trick. Try BestBuy, LinkedIn, or Amazon, though, and you’ll quickly see how fragile a naive approach can be.
This guide walks you through every viable method to pull website data into Excel automatically—from Excel’s built-in tools to no-code scrapers, APIs, VBA, and Python automation.

Method 1: Utilizing Excel’s Built-In Tools

Most professionals already have Excel, which makes it a natural starting point. But let’s be clear, this is not true scraping. You are not tricking a browser or bypassing bot defenses. You are simply asking politely and hoping the site cooperates.
Excel’s web queries and Power Query can pull HTML tables directly. Simple. Clean. Quick. But dynamic pages? JavaScript-driven tables? Excel will shrug.

Power Query

Power Query is your hidden weapon. It sends a GET request, parses HTML, and extracts tables automatically. Perfect for static pages, repeated updates, and pre-processing data without writing a single line of code.

Ideal when:

  • Working with simple HTML tables
  • Automating updates inside Excel
  • Filtering, reshaping, or renaming columns before import
  • Avoiding coding altogether

Example: Extract IMDb’s Top 250 Movies

  1. Open Excel → New Workbook.
  2. Go to Data → Get Data → From Other Sources → From Web.
  3. Paste the IMDb URL → select Basic → click OK.
  4. Navigator pane appears → preview tables → click Table 1.
  5. Click Load (or Transform Data to filter/clean first).

IMDb’s Top 250 is now structured in Excel. No coding, no headaches.

Web Queries

If you’ve been using Excel for a while, you’ll remember web queries—the OG tool for pulling data from HTML tables. Works only for plain HTML, no JavaScript.

Setup:

  1. Enable legacy wizards: File → Options → Data → Show legacy data import wizards → From Web (Legacy).
  2. Data → Get Data → Legacy Wizards → From Web (Legacy).
  3. Paste URL (Wikipedia tables are perfect).
  4. Click Import → Excel fills your sheet automatically.

Fast, simple, and still useful for static content.

Method 2: No-Code Web Scraping Tools

Excel breaks on dynamic sites. That’s where no-code scrapers shine.
These tools simulate a browser: scrolling, clicking, logging in, handling JavaScript—and exporting straight to Excel. Some even handle CAPTCHAs and proxies automatically.

Key features to check:

  • Ease of use: Shouldn’t feel like coding.
  • Browser emulation: Render pages, scroll, click, log in.
  • Precision targeting: CSS selectors, XPath.
  • Pagination handling: Click or URL-based.
  • Scheduler/automation: Export to Excel, send alerts.
  • Anti-block measures: CAPTCHA solving, randomized delays, proxy rotation.

Right tool = hours saved. Wrong tool = frustration.

Method 3: Using APIs

Sometimes scraping isn’t worth it. If a site offers an API, use it. APIs give clean, structured data—no JavaScript, no redirects, no CAPTCHAs.

Example: Random User Generator API

  1. Excel → New Workbook → Data → Get Data → From Web
  2. Paste https://randomuser.me/api/?results=50 → OK
  3. Expand the results list → Convert list to table → Flatten nested fields
  4. Close and Load → clean data appears in Excel

APIs are faster, cleaner, and more stable than scraping. Always check first.

More Automation Approaches

VBA

VBA isn’t ideal for scraping anymore. But it automates everything after the data lands in Excel.
For example, imagine 50 fake profiles from the Random User API, but you only need the female profiles for another team.

VBA Macro:

Sub CopyFemaleProfilesToNewWorkbook()
    Dim wsSource As Worksheet
    Dim wbTarget As Workbook
    Dim wsTarget As Worksheet
    Dim lastRow As Long
    Dim writeRow As Long
    Dim i As Long
    Dim savePath As String

    Set wsSource = ThisWorkbook.Sheets("original")
    Set wbTarget = Workbooks.Add
    Set wsTarget = wbTarget.Sheets(1)
    wsTarget.Name = "Female Profiles"

    Application.ScreenUpdating = False
    wsSource.Rows(1).Copy Destination:=wsTarget.Rows(1)
    writeRow = 2
    lastRow = wsSource.Cells(wsSource.Rows.Count, 1).End(xlUp).Row

    For i = 2 To lastRow
        If LCase(wsSource.Cells(i, 1).Value) = "female" Then
            wsSource.Rows(i).Copy Destination:=wsTarget.Rows(writeRow)
            writeRow = writeRow + 1
        End If
    Next i

    savePath = ThisWorkbook.Path and Application.PathSeparator and "female_acc.xlsx"
    wbTarget.SaveAs Filename:=savePath, FileFormat:=xlOpenXMLWorkbook
    wbTarget.Close SaveChanges:=False
    Application.ScreenUpdating = True
    MsgBox "Female profiles saved to: " and savePath, vbInformation
End Sub

Run → filtered dataset ready. Easy automation.

Python

Excel and no-code tools have limits. JavaScript, redirects, IP blocks? They all fail eventually.

Python gives full control:

  • requests + proxies for server-rendered pages
  • Selenium + Undetected ChromeDriver for full browser simulation
  • Residential proxies, timing tricks, and behavioral scripts for stealth

Python is slower—but stable. When scraping at scale or bypassing defenses, stability wins.

Conclusion

With the right approach, moving data from websites into Excel can be smooth and efficient. Excel handles simple tables, no-code scrapers tackle dynamic sites, APIs provide clean data, and Python handles the toughest cases. By combining these tools wisely and following best practices, you can transform even the most complex web pages into structured, usable insights.

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