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Applying Math with Python

You're reading from   Applying Math with Python Practical recipes for solving computational math problems using Python programming and its libraries

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Product type Paperback
Published in Jul 2020
Publisher Packt
ISBN-13 9781838989750
Length 358 pages
Edition 1st Edition
Languages
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Authors (2):
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Sam Morley Sam Morley
Author Profile Icon Sam Morley
Sam Morley
Sam Morley Sam Morley
Author Profile Icon Sam Morley
Sam Morley
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Table of Contents (12) Chapters Close

Preface 1. Basic Packages, Functions, and Concepts 2. Mathematical Plotting with Matplotlib FREE CHAPTER 3. Calculus and Differential Equations 4. Working with Randomness and Probability 5. Working with Trees and Networks 6. Working with Data and Statistics 7. Regression and Forecasting 8. Geometric Problems 9. Finding Optimal Solutions 10. Miscellaneous Topics 11. Other Books You May Enjoy

Using Prophet to model time series data


        

The tools we have seen so far for modeling time series data are very general and flexible methods, but they require some knowledge of time series analysis in order to be set up. The analysis needed to construct a good model that can be used to make reasonable predictions into the future can be intensive and time-consuming, and may not be viable for your application. The Prophet library is designed to automatically model time series data quickly, without the need for input from the user, and make predictions into the future.

In this recipe, we will learn how to use Prophet to produce forecasts from a sample time series.

Getting ready

For this recipe, we will need the Pandas package imported as pd, the Matplotlib pyplot package imported as plt, and the Prophet object from the Prophet library, which can be imported using the following command:

from fbprophet import Prophet

We also need to import...

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