Data Science Tutorials

If you're coming from one of my data science tutorials, you'll find the code and the links to the tutorials here.

| Article| Code| |----|------| |Build a Data Science App with Python in 10 Easy Steps|Code| |A Practical Guide to Deploying Machine Learning Models|Code| |FastAPI Tutorial: Build APIs with Python in Minutes|Code| |The Beginner’s Guide to Natural Language Processing with Python|Code| |How to Perform Statistical Analysis on Sparse Data in Python|Code| |10 Essential Statistical Functions in Python|Code| |How to Calculate Joint and Conditional Probabilities in Python|[Code]()| |How to Use the Geometric Distribution in Python|Code| |How to Use the Beta Distribution in Python|Code| |How to Use the Cauchy Distribution in Python|Code| |Tips for Effective Outlier Detection in Real-World Datasets|Code| |How to Interpret Statistical Plots in Python|Code| |Data Cleaning with Bash: A Handbook for Developers|Code| |Analyzing JSON Data with DuckDB & SQL|Code| |The Poisson Distribution: From Basics to Real-World Examples|Code| |Why & How to Containerize Your Existing Python Apps|Code| |How to Analyze Parquet Files with DuckDB|Code| |How to Analyze CSV Files with DuckDB|Code| |How to Query Pandas DataFrames with DuckDB|Code| |How to Calculate Descriptive Statistics in DuckDB|Code| |How to Perform Hypothesis Testing in DuckDB|Code| |Top 5 Statistical Techniques to Detect and Handle Outliers in Data|Code| |Why & How to Containerize Your Existing Python Apps|Code| |Step-by-Step Guide to Deploying Machine Learning Models with FastAPI and Docker|Code| |Build a Data Cleaning & Validation Pipeline in Under 50 Lines of Python|Code| |Vibe Coding a Speed Reading App with Python in Just 15 Minutes|Code| |Build ETL Pipelines for Data Science Workflows in About 30 Lines of Python|Code| |5 Useful Python Scripts for Busy Data Scientists|Code| |How to Perform Data Cleaning in PySpark|Code| |How to Write DataFrames to Parquet Files in PySpark|Code| |How to Read CSV Files into PySpark DataFrames|Code| |Tips for Effective Outlier Detection in Real-World Datasets|Code| |How to Perform Time Series Analysis with SciPy|Code| |Time Series Decomposition: Separating Signal from Noise|Code| |How to Work with Excel Files in Python|Code| |How to Process CSV Files in Python|Code| |The Essential Guide to Regular Expressions for Data Scientists|Code| |Shortcuts for the Long Run: Automated Workflows for Aspiring Data Engineers|Code| |10 NumPy One-Liners to Simplify Feature Engineering|Code| |10 Useful NumPy One-Liners for Time Series Analysis|Code| |Distance Metrics: Euclidean, Manhattan, Minkowski, Oh My!|Code| |Vector and Matrix Norms with NumPy Linalg Norm|Code| |SQL in Pandas with Pandasql|Code| |Principal Component Analysis (PCA) with Scikit-Learn|Code| |Beginner’s Guide to Data Analysis with Polars | Code| |10 Useful Python One-Liners for Data Engineering|Code| |MinMax vs Standard vs Robust Scaler: Which One Wins for Skewed Data?|Code| |7 NumPy Tricks to Vectorize Your Code|Code| |10 Useful Python One-Liners for CSV Processing|Code| |The Complete Guide to Building Data Pipelines That Don’t Break|Code| |5 Useful Python Scripts for Busy Data Analysts|Code| |5 Essential Python Scripts for Intermediate Machine Learning Practitioners|Code| |5 Useful Python Scripts for Busy Data Engineers|Code| |Data Cleaning at the Command Line for Beginner Data Scientists|Code| |The Complete Guide to Docker for Machine Learning Engineers|Code| |Building a Simple Data Quality DSL in Python|Code| |The Complete Guide to Using Pydantic for Validating LLM Outputs|Code| |Statistics at the Command Line for Beginner Data Scientists|Code| |5 Useful Python Scripts to Automate Boring Everyday Tasks|Code| |5 Useful Python Scripts to Automate Data Cleaning|Code| |5 Useful Python Scripts for Effective Feature Engineering|Code| |Building Your Modern Data Analytics Stack with Python, Parquet, and DuckDB|Code| |5 Useful Python Scripts to Automate Boring File Tasks|Code| |The Machine Learning Practitioner’s Guide to Speculative Decoding| Code| |5 DIY Python Decorators for Building Cleaner Data Pipelines|Code| |5 Useful Python Scripts for Automated Data Quality Checks|Code| |5 Useful Python Scripts to Automate Exploratory Data Analysis|Code| | Pandas vs. Polars: A Complete Comparison of Syntax, Speed, and Memory|Code| |7 Essential Python Itertools for Feature Engineering|Code| |5 Useful Python Scripts for Effective Feature Selection|Code| |5 Useful Python Scripts to Automate Boring Excel Tasks|Code| |5 Useful Python Scripts for Advanced Data Validation & Quality Checks|Code| | Building AI Agents in Python with Pydantic AI|Code| |5 Useful Python Scripts for Time Series Analysis | Code| |Time-Series Feature Engineering with Python Itertools|Code| |How to Clean Time Series Data in Python|Code| |5 Useful Python Scripts to Automate Boring PDF Tasks|Code| |Building Time-Series Machine Learning Models with sktime in Python|Code| |Stop Writing Loops in Pandas: 7 Faster Alternatives to Try|Code|