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

View More author details

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

Join our book community on Discord

https://packt.link/zmkOY

In this chapter, you will use the pandas library to persist your time series DataFrames to different file formats, such as CSV, Excel, Parquet, and pickle files. When performing analysis or data transformations on DataFrames, you essentially leverage pandas' in-memory analytics capabilities, offering great performance. However, being in memory means the data can easily be lost since it has not yet persisted in disk storage.

When working with DataFrames, you will need to persist your data for future retrieval, creating backups, or sharing your data with others. The pandas library is bundled with a rich set of writer functions to persist your in-memory DataFrame (or series) to disk in various file formats. These writer functions allow you to store data on a local drive or a remote server location, such as a cloud storage filesystem, including Google Drive, AWS S3, Azure Blob Storage, and Dropbox.

In this chapter, you will...