{"categories":[{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/10"}],"enrichment":{"capability":"Datazets provides a simple interface to download and import well-known example datasets for machine learning, data science, and educational purposes without manual data collection.","skillfed_tags":["datasets","machine-learning","data-science"],"use_cases":["Quickly prototype machine learning models using well-known datasets like titanic or breast_cancer without manual data sourcing","Teach data science concepts with standardized datasets that students can reproduce across different environments","Benchmark classification or regression algorithms against established datasets for fair performance comparison","Test data pipelines and ETL workflows with diverse data types (images, text, tabular, network) in one package","Develop cybersecurity models using labeled malicious URL datasets for phishing and malware detection","Experiment with time-series forecasting using historical price data (bitcoin, gas prices, stock prices)"],"what_it_does":"Datazets is a Python package that centralizes access to a curated collection of example datasets commonly used in machine learning, data science, and educational contexts. Instead of hunting down datasets from multiple sources or generating synthetic data, you import datazets and call a single function to load datasets like titanic, iris, mnist, or bitcoin directly into a pandas DataFrame. The package wraps network retrieval and parsing, so you get clean, ready-to-use data in one line.\n\nThe library covers diverse data types\u2014continuous time series (stock prices, bitcoin), discrete synthetic data (for probability modeling), text data (malicious URLs for cybersecurity), network graphs (character relationships from fiction), images (handwritten digits, faces), and mixed tabular datasets (census, student performance, predictive maintenance). It depends on numpy, pandas, and requests to handle data loading and transformation, and supports current Python versions. The package is aimed at researchers, educators, and practitioners who need standard benchmark datasets for prototyping, testing, or teaching without the overhead of data collection.","worth_installing":"Yes. Datazets is a lightweight, actively maintained utility with permissive licensing and no known vulnerabilities. It solves a genuine friction point\u2014sourcing standard datasets\u2014and has low install overhead. Install it if you regularly prototype with example data or teach data science; skip it if you work exclusively with proprietary or custom datasets."},"id":"datazets","links":{"html":"https://skillfed.io/packages/datazets","md":"https://skillfed.io/packages/datazets.md","pypi":"https://pypi.org/project/datazets/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-07-12","license_spdx":"MIT","license_treatment":"permissive","name":"datazets","python_support":"supports_current","summary":"Datazets is a python package to import well known example data sets."},"popularity":{"monthly_downloads":105771,"position":12681,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"1.1.4"}