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GitHubMay 2, 20256 min read

How to Export GitHub README Tables to Excel

Step-by-step guide to exporting GitHub README Markdown tables to Excel. Copy the table, paste it into the converter, and download your .xlsx file.

How to Export GitHub README Tables to Excel (Step-by-Step)

GitHub README files are full of useful tables — dependency lists, API parameter references, benchmark results, configuration options, changelog entries. If you have ever tried to copy one of those tables into Excel for further analysis, sorting, or sharing with a non-technical colleague, you know how frustrating the process can be.

Paste the rendered table from GitHub and you lose the structure. Copy the raw Markdown and Excel does not know what to do with it. This guide shows you the cleanest, fastest methods to get GitHub README tables into Excel — including a one-step approach that takes under 30 seconds.

Why GitHub Tables Do Not Paste Directly into Excel

When you look at a GitHub README, you are seeing a rendered version. GitHub converts the raw Markdown syntax into an HTML table displayed in your browser. When you select and copy that rendered table and paste into Excel, one of two things typically happens:

  • The entire table pastes into a single cell as plain text
  • The structure breaks and column data merges together incorrectly

This is because GitHub's table rendering uses HTML elements that Excel's paste function does not reliably interpret as spreadsheet columns. The raw Markdown source — with pipe characters and hyphens — is equally unhelpful for Excel, which does not understand Markdown syntax.

The solution is to convert the Markdown table syntax into a format Excel can read: specifically, a proper .xlsx file or TSV (tab-separated values) that Excel parses into columns automatically.

Method 1: Using markdowntoexcel.com (Fastest — Under 30 Seconds)

This is the recommended approach. It requires no software, no account, and processes everything in your browser.

Step 1: Get the raw Markdown from GitHub

Open the GitHub repository with the README you want to copy from.

In the top-right corner of the README file view, click the Raw button. This opens the raw Markdown source of the file in your browser.

Alternatively, append /raw/main/README.md to the repository URL:

https://github.com/user/repo/raw/main/README.md

Step 2: Copy the Markdown table

In the raw view, find the table you want. It will look something like this:

| Package       | Version | License    | Size    |
|---------------|---------|------------|---------|
| react         | 18.2.0  | MIT        | 6.4 kB  |
| typescript    | 5.0.4   | Apache-2.0 | 72.3 kB |
| axios         | 1.4.0   | MIT        | 11.2 kB |
| lodash        | 4.17.21 | MIT        | 24.3 kB |

Select the entire table — from the first pipe character on the header row to the last pipe character on the final data row — and copy it (Ctrl+C or Cmd+C).

Step 3: Paste into the converter

Go to markdowntoexcel.com and paste your copied Markdown into the input panel on the left. The tool instantly shows you a preview of how the data will look in Excel.

Step 4: Download as Excel

Click the Download Excel button. A .xlsx file downloads to your computer immediately.

Step 5: Open in Excel

Open the downloaded file in Microsoft Excel or Google Sheets. Your table is perfectly formatted with headers in row 1 and all data in the correct columns. From here you can sort, filter, apply formulas, or share with anyone.

That is it — the entire process takes under 30 seconds for a single table.

Method 2: Copy Raw Markdown and Use Text-to-Columns in Excel

If you prefer to work entirely within Excel without using a browser tool, this method works but requires a few more steps.

Step 1: Get the raw Markdown

Follow Step 1 from Method 1 above — click Raw on GitHub to get the Markdown source.

Step 2: Copy just the data rows (not the separator row)

Copy all rows except the separator row (the |---|---| line). For example:

| Package    | Version | License |
| react      | 18.2.0  | MIT     |
| typescript | 5.0.4   | Apache  |

Step 3: Paste into Excel as plain text

In Excel, right-click the destination cell and choose Paste Special → Text. This pastes the raw content without Excel trying to interpret it.

Step 4: Use Text to Columns

Select the pasted column. Go to Data → Text to Columns. Choose Delimited, then check Other and type | as the delimiter. Click Finish.

Excel splits the content at each pipe character into separate columns. You may end up with empty columns at the start and end (from the leading and trailing | characters) — simply delete those.

Step 5: Clean up

Remove the extra empty columns, fix the header row, and your table is ready.

This method works but is error-prone with complex tables that contain special characters or varied spacing. Method 1 is significantly faster and more reliable.

Method 3: GitHub API (For Developers)

If you frequently need to extract tables from GitHub READMEs programmatically, the GitHub API gives you direct access to file contents.

curl -H "Accept: application/vnd.github.v3.raw" \
  https://api.github.com/repos/OWNER/REPO/contents/README.md

This returns the raw Markdown content. You can then parse the Markdown table using a library in your preferred language and export to Excel:

Python example:

import re
import pandas as pd

def parse_markdown_table(md_text):
    lines = md_text.strip().split('\n')
    # Filter out separator rows
    data_lines = [l for l in lines if not re.match(r'^\|[-| :]+\|$', l.strip())]
    rows = []
    for line in data_lines:
        cells = [c.strip() for c in line.strip('|').split('|')]
        rows.append(cells)
    headers = rows[0]
    data = rows[1:]
    return pd.DataFrame(data, columns=headers)

# df is now a pandas DataFrame — export to Excel:
df = parse_markdown_table(your_markdown_text)
df.to_excel('output.xlsx', index=False)

This approach is ideal for automated pipelines where you need to regularly pull and process README table data.

Tips for Working with GitHub README Tables in Excel

Tip 1: Check for merged or complex tables first. Some GitHub READMEs contain tables with HTML inside cells (links, images, code spans). The converter handles inline code and text well, but complex nested HTML in cells may not translate perfectly. Preview the result before downloading.

Tip 2: Multi-table READMEs. If the README contains multiple tables, copy each one separately and run them through the converter individually. This gives you cleaner, separate sheets for each table.

Tip 3: Very large tables. For tables with hundreds of rows, Method 1 (markdowntoexcel.com) remains the fastest. The tool handles large tables entirely in your browser without any size limits.

Tip 4: Google Sheets instead of Excel. If you want to use Google Sheets instead, use our Markdown to CSV tool and import the CSV into Google Sheets via File → Import.

Tip 5: Reverse the workflow. If you have data in Excel that needs to go into a GitHub README as a Markdown table, use our Excel to Markdown converter to do the reverse in the same amount of time.

Common GitHub Table Scenarios

Package dependency tables

Many projects list their dependencies in a README table with package names, versions, and licenses. These are ideal for converting to Excel to sort by version, filter by license type, or share with legal or compliance teams.

API parameter reference tables

Projects often document their API parameters in a table with parameter name, type, required/optional, and description. Converting to Excel lets you filter by required status or sort alphabetically — useful when working with large APIs.

Benchmark and performance tables

Performance benchmarks in README files typically show test conditions and metric values. Excel's sorting and charting features are much more powerful than static Markdown tables for analyzing this data.

Changelog tables

Some projects format their changelogs as tables with version, date, and changes columns. Converting to Excel makes it easy to search and filter across large changelogs.

Conclusion

Exporting GitHub README tables to Excel is straightforward once you know the right approach. The fastest method is to copy the raw Markdown from GitHub's Raw view, paste it into markdowntoexcel.com, and download the resulting .xlsx file — the whole process takes under 30 seconds.

For developers who need to automate this process, the GitHub API combined with a Markdown parser and pandas makes it easy to build a repeatable pipeline.

Whichever method you choose, you now have your GitHub table data in Excel where you can sort, filter, apply formulas, build charts, and share it with anyone — not just those who can read a GitHub README.