Free notebooks: Google Colab and Kaggle

You will set up a free data science workspace in your browser, run your first code, upload a file, and learn the habits that stop you losing work. You need a Google account (for Colab) and an email address (for Kaggle). A phone or a basic laptop is enough, because the computing happens on remote servers.

A notebook is a document made of cells. Some cells hold code, some hold text. You run code cell by cell and the output (numbers, tables, charts) appears right below it. This is why data scientists love notebooks: you can try an idea, see the result and explain it in one place.

Both are free at the time of writing (2026), but limits on GPU time, memory and session length change, and are not guaranteed. Check each site's help page for current numbers. For this track, either works. Use Colab if you like Google Drive, and Kaggle if you want ready datasets.

import sys
import pandas as pd
import numpy as np

print(sys.version)
print("pandas", pd.__version__)
print("numpy", np.__version__)

Colab already has pandas, NumPy, matplotlib and scikit-learn installed. This cell prints their versions, so you know the environment.

Your notebook is saved to your Google Drive automatically (in a folder called Colab Notebooks), but the running session is temporary. If you leave it idle for a while, or close the tab for long, the session ends and everything in memory and in the session's file storage is lost.

A data science notebook needs data. There are three common ways in Colab.

# Option 1: upload from your computer (files vanish when the session ends)
from google.colab import files
uploaded = files.upload()   # opens a file picker
print(list(uploaded.keys()))

After you choose a CSV, it is saved in the notebook's working folder. Read it with pd.read_csv("your_file.csv").

# Option 2: mount Google Drive (files stay in your Drive)
from google.colab import drive
drive.mount('/content/drive')

import pandas as pd
df = pd.read_csv('/content/drive/MyDrive/data/sales.csv')
df.head()

A pop-up asks you to allow access to your Drive. Put your CSV in a folder named data first, or change the path.

# Option 3: download from a public URL (replace the link)
!wget -q -O sales.csv "https://example.com/path/to/sales.csv"
!ls -lh sales.csv

A line starting with ! runs a shell command inside the notebook. The link above is only a placeholder; use a real direct CSV link.

!pip install -q seaborn

Use !pip install in a cell. Packages you install vanish when the session ends, so keep this line at the top of your notebook.

import os

for dirname, _, filenames in os.walk('/kaggle/input'):
    for filename in filenames:
        print(os.path.join(dirname, filename))

This is the default first cell Kaggle gives you. Copy a printed path into pd.read_csv(...).

I am running a Python notebook in [Google Colab / Kaggle]. This cell fails:

```
[paste your code]
```

Error message:

```
[paste the full error]
```

Explain in simple English what the error means, point to the exact line that causes it, and show the corrected code. Then tell me one way to avoid this error next time.

What to expect: The answer should name the line, explain the cause (for example a wrong file path or a missing import) and give runnable code. Re-run it yourself rather than trusting it.