Working with Real Datasets

Working with real-world datasets is fundamentally different from working with clean, pre-processed toy data. Real data is messy, incomplete, and often surprising. This lesson covers where to find datasets, how to handle common real-world challenges, and how to conduct an end-to-end analysis on a genuine dataset.

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Where to Find Datasets

Open Data Portals

Source	URL	Description
Kaggle	kaggle.com	Thousands of datasets across every domain
UCI Machine Learning Repository	archive.ics.uci.edu	Classic ML datasets
Google Dataset Search	datasetsearch.research.google.com	Search engine for datasets
data.gov	data.gov	US government open data
data.gov.uk	data.gov.uk	UK government open data
World Bank	data.worldbank.org	Global development data
WHO	who.int/data	Global health data
Eurostat	ec.europa.eu/eurostat	European statistics

Built-in Datasets

# Scikit-Learn datasets
from sklearn.datasets import (
    load_iris,                # Classification: flower species
    load_wine,                # Classification: wine quality
    fetch_california_housing, # Regression: house prices
    load_digits,              # Classification: handwritten digits
    fetch_20newsgroups        # Text classification: newsgroup posts
)