Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Time Series Analysis with Python Cookbook

You're reading from   Time Series Analysis with Python Cookbook Practical recipes for exploratory data analysis, data preparation, forecasting, and model evaluation

Arrow left icon
Product type Paperback
Published in Jun 2022
Publisher Packt
ISBN-13 9781801075541
Length 630 pages
Edition 1st Edition
Languages
Tools
Arrow right icon
Author (1):
Arrow left icon
Tarek A. Atwan Tarek A. Atwan
Author Profile Icon Tarek A. Atwan
Tarek A. Atwan
Arrow right icon
View More author details
Toc

Table of Contents (18) Chapters Close

Preface 1. Chapter 1: Getting Started with Time Series Analysis 2. Chapter 2: Reading Time Series Data from Files FREE CHAPTER 3. Chapter 3: Reading Time Series Data from Databases 4. Chapter 4: Persisting Time Series Data to Files 5. Chapter 5: Persisting Time Series Data to Databases 6. Chapter 6: Working with Date and Time in Python 7. Chapter 7: Handling Missing Data 8. Chapter 8: Outlier Detection Using Statistical Methods 9. Chapter 9: Exploratory Data Analysis and Diagnosis 10. Chapter 10: Building Univariate Time Series Models Using Statistical Methods 11. Chapter 11: Additional Statistical Modeling Techniques for Time Series 12. Chapter 12: Forecasting Using Supervised Machine Learning 13. Chapter 13: Deep Learning for Time Series Forecasting 14. Chapter 14: Outlier Detection Using Unsupervised Machine Learning 15. Chapter 15: Advanced Techniques for Complex Time Series 16. Index 17. Other Books You May Enjoy

Reading data from a document database (MongoDB)

MongoDB, a NoSQL database, stores data in documents and uses BSON (a JSON-like structure) to store schema-less data. Unlike relational databases, where data is stored in tables that consist of rows and columns, document-oriented databases store data in collections and documents.

A document represents the lowest granular level of data being stored, as rows do in relational databases. A collection, like a table in relational databases, stores documents. Unlike relational databases, a collection can store documents of different schemas and structures.

Getting ready

In this recipe, it is assumed that you have a running instance of MongoDB. To get ready for this recipe, you will need to install the PyMongo Python library to connect to MongoDB.

To install MongoDB using conda, run the following command:

$ conda install -c anaconda pymongo -y

To install MongoDB using pip, run the following command:

$ python -m pip install...
lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime
Banner background image