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https://github.com/PacktPublishing/Practical-Time-Series-Analysis
Practical Time-Series Analysis, published by Packt
https://github.com/PacktPublishing/Practical-Time-Series-Analysis
Last synced: 3 months ago
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Practical Time-Series Analysis, published by Packt
- Host: GitHub
- URL: https://github.com/PacktPublishing/Practical-Time-Series-Analysis
- Owner: PacktPublishing
- License: mit
- Created: 2017-09-27T05:38:26.000Z (over 7 years ago)
- Default Branch: master
- Last Pushed: 2023-01-30T08:34:37.000Z (almost 2 years ago)
- Last Synced: 2024-08-02T14:09:40.858Z (6 months ago)
- Language: Jupyter Notebook
- Homepage:
- Size: 2.42 MB
- Stars: 402
- Watchers: 21
- Forks: 250
- Open Issues: 3
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- awesome-time-series - repo with code
README
# Practical Time-Series Analysis
This is the code repository for [Practical Time-Series Analysis](https://www.packtpub.com/big-data-and-business-intelligence/practical-time-series-analysis?utm_source=github&utm_medium=repository&utm_campaign=9781788290227), published by [Packt](https://www.packtpub.com/?utm_source=github). It contains all the supporting project files necessary to work through the book from start to finish.
## About the Book
Time-series analysis allows us to analyze certain data over a period of time and understand patterns in the data over time.This book will get you understanding the logic behind time-series analysis and implementing it in various fields, including financial, business, and social media.
## Instructions and Navigation
All of the code is organized into folders. Each folder starts with a number followed by the application name. For example, Chapter02.
The code will look like the following:
```
import os
import pandas as pd
%matplotlib inline
from matplotlib import pyplot as plt
import seaborn as sns
```
You will need the Anaconda Python Distribution to run the examples in this book and write
your own Python programs for time series analysis. This is freely downloadable from
https://www.continuum.io/downloads.
The code samples of this book have been written using the Jupyter Notebook development
environment. To run the Jupyter Notebooks, you need to install Anaconda Python
Distribution, which has the Python language essentials, interpreter, packages used to
develop the examples, and the Jupyter Notebook server.
## Related Products
* [Practical Real-time Data Processing and Analytics](https://www.packtpub.com/big-data-and-business-intelligence/practical-real-time-data-processing-and-analytics?utm_source=github&utm_medium=repository&utm_campaign=9781787281202)
* [Building Python Real-Time Applications with Storm](https://www.packtpub.com/big-data-and-business-intelligence/building-python-real-time-applications-storm?utm_source=github&utm_medium=repository&utm_campaign=9781784392857)
* [SignalR – Real-time Application Development - Second Edition](https://www.packtpub.com/application-development/signalr-real-time-application-development-second-edition?utm_source=github&utm_medium=repository&utm_campaign=9781785285455)
### Download a free PDF
If you have already purchased a print or Kindle version of this book, you can get a DRM-free PDF version at no cost.
Simply click on the link to claim your free PDF.