How to Import Dataset From GitHub to Colab? (Full Step-by-Step Guide)

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Introduction

If you’re working with Google Colab, sooner or later you’ll need to load external data. One of the easiest sources is GitHub — but many beginners still ask: How to import a dataset from GitHub to Colab?

In this guide, you’ll learn every method: downloading with raw GitHub URLs, cloning repos, using wget, mounting Google Drive, and more. Each method includes code examples, best practices, and troubleshooting tips.

Let’s start.

How to Import Dataset From GitHub to Colab

Below are the most reliable and beginner-friendly ways to bring any dataset from GitHub directly into Google Colab.

Method 1: Import Dataset From GitHub Using the Raw File URL (Easiest Method)

This method works best for CSV, TXT, JSON, and small files.

Step-by-step

1. Open the GitHub file (e.g., dataset.csv).
2. Click Raw.
3. Copy the URL (it should start with https://raw.githubusercontent.com/...).
4. In Colab, run:

import pandas as pd

url = "https://raw.githubusercontent.com/username/repo/main/dataset.csv"
df = pd.read_csv(url)

df.head()

When to use this method

• Simple CSV files
• Public GitHub repos
• No authentication needed

Method 2: Clone the Entire GitHub Repository into Colab

Best for datasets stored across multiple files or folders.

Steps

Run:

!git clone https://github.com/username/repo.git

Then access the dataset:

import pandas as pd
df = pd.read_csv("repo/data/dataset.csv")
df.head()

Pros

✔ Works for large projects
✔ Folder structures preserved

Cons

✘ Slower
✘ Downloads entire repo (not just the dataset)

Method 3: Use wget or curl to Download Files from GitHub

Works well when Python cannot load the file directly.

Example using wget

!wget https://raw.githubusercontent.com/username/repo/main/dataset.csv

Then:

import pandas as pd
df = pd.read_csv("dataset.csv")

Example using curl

!curl -L -o dataset.csv https://raw.githubusercontent.com/username/repo/main/dataset.csv

Method 4: Import Private GitHub Dataset to Colab

You must use a GitHub Personal Access Token.

import pandas as pd

url = "https://raw.githubusercontent.com/username/repo/main/private.csv"
token = "YOUR_TOKEN"

df = pd.read_csv(f"https://{token}:x-oauth-basic@raw.githubusercontent.com/username/repo/main/private.csv")

Security Tip

⚠ Never expose your token in public notebooks.

Method 5: Download GitHub Dataset to Google Drive then Load in Colab

Step 1 — Mount Drive

from google.colab import drive
drive.mount('/content/drive')

Step 2 — Download Manually or via Script

Use:

!wget -P /content/drive/MyDrive https://raw.githubusercontent.com/username/repo/main/dataset.csv

Step 3 — Load dataset

df = pd.read_csv('/content/drive/MyDrive/dataset.csv')

Comparison Table: Best Way to Import GitHub Dataset to Colab

Troubleshooting & Common Errors

1. “HTTPError: 404 Not Found”

• The Raw URL is incorrect
• The file path changed
• Repo or branch is private

Fix: Always copy the link from the Raw button.

2. “UnicodeDecodeError when loading CSV”

The dataset has a different encoding.

pd.read_csv(url, encoding='latin1')

3. “File not found” after cloning

Check folder structure:

!ls repo/

4. Git Large File Storage (LFS) issues

GitHub blocks files >100MB unless using LFS.

Fix:
Download directly using the Release assets page or use Google Drive.

5. Cannot access private repo

Make sure your token has:

• repo
• read:packages

permissions.

Best Practices When Importing GitHub Data to Colab

• Prefer raw URLs for simplicity.
• For multiple files, always clone.
• Store repeating datasets in Google Drive.
• Avoid exposing tokens in notebooks.
• Use df.info() and df.head() after loading to verify.

Examples: Load Different File Types

CSV

pd.read_csv(url)

JSON

import json
import requests

data = requests.get(url).json()

Excel

pd.read_excel(url)

Image files

from PIL import Image
import requests
from io import BytesIO

img = Image.open(BytesIO(requests.get(url).content))
img

Conclusion

Importing a dataset from GitHub to Colab is simple once you know the correct method. Whether you choose raw URLs, cloning, or using Drive, this guide gives you every tool you need.

If this tutorial helped, share it and bookmark the page for future reference!

FAQ — People Also Ask

1. How do I load CSV files from GitHub to Google Colab?

Use the Raw URL and pd.read_csv(). It’s the easiest method.

2. Why is my GitHub file not loading in Colab?

The raw link may be wrong, the repo is private, or the file path changed.

3. How do I access private GitHub datasets in Colab?

Use a GitHub Personal Access Token in the URL.

4. Can I import large datasets from GitHub to Colab?

Yes, but GitHub limits files >100MB. Use Google Drive or Releases for large files.

5. How do I clone a GitHub repo in Colab?

Run:

!git clone https://github.com/user/repo.git

6. Can I import multiple files from GitHub?

Yes — cloning the repo is the best method.

7. How do I download GitHub data into Google Drive using Colab?

Use wget with the Drive path.

8. Why does Colab show Unicode errors when loading GitHub CSV?

The file uses a different encoding. Try encoding="latin1".

9. Can I import a GitHub folder directly?

Not directly. You must clone the entire repo.

10. Does GitHub raw URL work with all formats?

Yes for most text-based formats (CSV, JSON, txt). For binary formats, use wget.

11. How do I fix 403 errors when loading GitHub files?

Wait and retry — GitHub rate limiting might be triggered.

12. How do I import GitHub notebooks into Colab?

Open the .ipynb file → click Open in Colab (if enabled) — or download with wget.