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

Product type Paperback

Published in Apr 2025

Publisher

ISBN-13 9781805124283

Length 98 pages

Edition 2nd Edition

Languages

Python

Concepts

Data Analysis

Author (1):

Tarek A. Atwan

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Table of Contents (13) Chapters

1. Time Series Analysis with Python Cookbook, Second Edition: Practical recipes for exploratory data analysis, data preparation, forecasting, and model evaluation FREE CHAPTER

2. Getting Started with Time Series Analysis

3. Reading Time Series Data from Files

4. Reading Time Series Data from Databases

5. Persisting Time Series Data to Files

6. Persisting Time Series Data to Databases

7. Working with Date and Time in Python

8. Handling Missing Data

9. Outlier Detection Using Statistical Methods

10. Exploratory Data Analysis and Diagnosis

11. Building Univariate Time Series Models Using Statistical Methods

12. Additional Statistical Modeling Techniques for Time Series

13. Outlier Detection Using Unsupervised Machine Learning

Reading data from a relational database

In this recipe, you will read data from PostgreSQL, a popular open-source relational database.

You will explore two methods for connecting to and interacting with PostgreSQL. First, you will use psycopg, a PostgreSQL Python connector, to connect and query the database, then parse the results into a pandas DataFrame. In the second approach, you will query the same database again, but this time, you will use SQLAlchemy, an object-relational mapper (ORM) that is well-integrated with pandas.

Getting ready

In this recipe, it is assumed that you have the latest PostgreSQL installed. At the time of writing, version 16 is the latest stable version.

To connect to and query the database in Python, you will need to install psycopg, a popular PostgreSQL database adapter for Python. You will also need to install SQLAlchemy, which provides flexibility regarding how you want to manage the database, whether for writing or reading data.

To install the libraries...

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

Table of Contents (13) Chapters

Reading data from a relational database

Getting ready

Authors (1)

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

Table of Contents (13) Chapters

Reading data from a relational database

Getting ready

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