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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

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Product type Paperback
Published in Jun 2022
Publisher Packt
ISBN-13 9781801075541
Length 630 pages
Edition 1st Edition
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Author (1):
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Tarek A. Atwan Tarek A. Atwan
Author Profile Icon Tarek A. Atwan
Tarek A. Atwan
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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

Writing to CSV and other delimited files

In this recipe, you will export a DataFrame to a CSV file and leverage the different parameters available to use in the DataFrame.to_csv() writer function.

Getting ready

The file is provided in the GitHub repository for this book, which you can find here: https://github.com/PacktPublishing/Time-Series-Analysis-with-Python-Cookbook. The file is named movieboxoffice.csv.

To prepare, let's first read the file into a DataFrame with the following code:

import pandas as pd
from pathlib import Path
filepath = Path('../../datasets/Ch4/movieboxoffice.csv')
movies = pd.read_csv(filepath,
                 header=0,
                 parse_dates=[0],
                 index_col...
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