Time Series Analysis with Python Cookbook, 2E

Time Series Python Cookbook

Time Series Python Cookbook is your complete hands-on guide to mastering the art of time series analysis using the powerful Python programming language. Whether you’re a data scientist, analyst, or AI enthusiast, this updated second edition delivers practical recipes to solve real-world forecasting and modeling problems.

What You’ll Learn

• Explore fundamental time series concepts: stationarity, seasonality, trend decomposition
• Build models using ARIMA, SARIMA, Prophet, and deep learning techniques like LSTM
• Use Python libraries such as Pandas, NumPy, Statsmodels, and TensorFlow
• Apply statistical tests and model diagnostics
• Implement real-world forecasting use cases
• Handle time zones, irregular time series, and missing values efficiently

Requirements

• Basic understanding of Python programming
• Familiarity with data analysis and visualization libraries (Pandas, Matplotlib)
• Optional but helpful: some knowledge of statistics or machine learning

Course Description

This course offers over 100 ready-to-use Python recipes to help you work with time series data like a professional. Starting with the basics of temporal data and progressing to advanced techniques, the Time Series Python Cookbook takes a practical approach to show how time series problems are tackled in real business and research settings.

You’ll learn how to clean and transform time-indexed data, visualize trends, and generate accurate forecasts. The course goes beyond traditional methods, guiding you into deep learning applications such as sequence modeling with LSTM and hybrid models using TensorFlow.

By the end of this course, you’ll be confident in building robust time series pipelines and forecasting systems, suitable for applications in finance, healthcare, energy, retail, and more.

About the Publication

Published by Packt, this second edition of the cookbook is authored by experts in time series analysis and Python development. Their deep industry insights and structured guidance ensure that learners can translate theory into practice effortlessly.

Explore These Valuable Resources

• Official Publisher’s Page
• Pandas Time Series Documentation
• Facebook Prophet Forecasting Guide

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