Book Image

Applying Math with Python

By : Sam Morley
Book Image

Applying Math with Python

By: Sam Morley

Overview of this book

Python, one of the world's most popular programming languages, has a number of powerful packages to help you tackle complex mathematical problems in a simple and efficient way. These core capabilities help programmers pave the way for building exciting applications in various domains, such as machine learning and data science, using knowledge in the computational mathematics domain. The book teaches you how to solve problems faced in a wide variety of mathematical fields, including calculus, probability, statistics and data science, graph theory, optimization, and geometry. You'll start by developing core skills and learning about packages covered in Python’s scientific stack, including NumPy, SciPy, and Matplotlib. As you advance, you'll get to grips with more advanced topics of calculus, probability, and networks (graph theory). After you gain a solid understanding of these topics, you'll discover Python's applications in data science and statistics, forecasting, geometry, and optimization. The final chapters will take you through a collection of miscellaneous problems, including working with specific data formats and accelerating code. By the end of this book, you'll have an arsenal of practical coding solutions that can be used and modified to solve a wide range of practical problems in computational mathematics and data science.
Table of Contents (12 chapters)

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...