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  • Time Series with Python: How to Implement Time Series Analysis and Forecasting Using Python by Bob Mather book cover
  • Time Series with Python: How to Implement Time Series Analysis and Forecasting Using Python by Bob Mather book cover
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Time Series with Python: How to Implement Time Series Analysis and Forecasting Using Python

by Bob Mather

A Python-based introduction to time-series analysis

$34.20 USD
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AlbakiReads Editorial

A Python-based introduction to time-series analysis

Bob Mather’s guide moves from foundational time-series concepts to more advanced methods, pairing the material with Python setup instructions and more than 20 coded examples. Its emphasis is practical implementation: the examples show how the concepts are applied through Python, giving the book a clear place at the intersection of statistics and programming. The description also situates time-series work within data analysis, particularly its use in examining data over time and forecasting future events.

Good fit for readers who enjoy

  • Beginners seeking an introduction to time-series concepts alongside Python setup.
  • Data analysts or programmers interested in worked Python examples of time-series methods.
  • Readers looking for a progression from basic to more advanced time-series topics.

Themes

Time-series analysisForecastingPython programmingStatistics and data analysis

Based on publisher information and book metadata.

Book overview

Are you looking to learn more about Time Series, but struggling to find them in traditional Data Science textbooks?

This book is your answer.


Time Series is an exciting and important part of Data Analysis. Time Series Data is more readily available than most forms of data and answers questions that cross-sectional data struggle to do. It also has more real world application in the prediction of future events. However it is not generally found in a traditional data science toolkit. There is also limited centralized resources on the applications of Time Series, especially using traditional programming languages such as Python.


This book solves all these problems, and more. It starts off with basic concepts in Time Series, and switches to more advanced topics. It shows you how to set up Python from start, and goes through over 20 examples of applying both simple and advanced Time Series concepts with Python code.

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