22 Chapters

Textbook Reference

Integrated Educational Content for Data Science

Chapter Overview

The textbook client provides access to 22 markdown chapters covering the full data science stack. Use textbook_search and textbook_explain tools for on-demand reference.

Python Fundamentals

Chapter Title Topics
01 Python Getting Started Variables, types, control flow, functions
02 Python Advanced List comprehensions, generators, decorators
21 Object-Oriented Programming Classes, inheritance, encapsulation

Pandas & Data Manipulation

Chapter Title Topics
03 Pandas Getting Started DataFrames, Series, indexing, selection
04 Pandas Advanced Groupby, merge, pivot, reshaping
05 Summary Statistics Describe, aggregation, missing values

Visualization

Chapter Title Topics
06 Matplotlib Plots, axes, figures, customization
07 Pandas Plotting Built-in DataFrame plotting
08 Plotly Interactive charts, mapbox, express
09 Seaborn Statistical visualization, themes

Databases

Chapter Title Topics
10 SQL Databases SQLite, queries, joins, aggregation
11 MongoDB NoSQL, documents, queries, aggregation

Machine Learning

Chapter Title Topics
12 ML Core Scikit-learn, pipelines, cross-validation
13 Data Pre-Processing Imputation, scaling, encoding, production
14 Classification Logistic regression, trees, metrics
15 Regression Linear, Ridge, Lasso, evaluation
16 Unsupervised Learning K-Means, PCA, clustering evaluation

Time Series

Chapter Title Topics
17 Time Series Core DateTime, resampling, stationarity
18 Time Series Models AR, ARMA, ARIMA, GARCH, forecasting

Additional Topics

Chapter Title Topics
19 Linux Command Line Bash, navigation, scripts, environment
20 Statistics Distributions, hypothesis testing, confidence intervals
22 APIs REST, requests, JSON, authentication

Example Queries

# Search for concept "Explain logistic regression" # Chapter reference "Show me chapter 15 on regression" # Combined with project "Explain GARCH and show example from project 8"