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 Jun 2022

Publisher Packt

ISBN-13 9781801075541

Length 630 pages

Edition 1st Edition

Languages

Python

Tools

Keras

Concepts

Data Analysis

Author (1):

Tarek A. Atwan

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Table of Contents (18) Chapters

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

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Writing time series data to Snowflake

Snowflake has become a very popular cloud database option for building big data analytics, due to its scalability, performance, and being SQL-oriented (a columnar-stored relational database).

Snowflake's connector for Python simplifies the interaction with the database whether it's for reading or writing data, or, more specifically, the built-in support for pandas DataFrames. In this recipe, you will use the sensor IoT dataset prepared in the Writing time series data to InfluxDB recipe. The technique applies to any pandas DataFrame that you plan to write to Snowflake.

Getting ready

To connect to Snowflake, you will need to install the Snowflake Python connector.

To install using Conda, run the following:

conda install -c conda-forge snowflake-sqlalchemy snowflake-connector-python

To install using pip, run the following:

pip install "snowflake-connector-python[pandas]"
pip install --upgrade snowflake-sqlalchemy...

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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 (18) Chapters

Writing time series data to Snowflake

Getting ready

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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 (18) Chapters

Writing time series data to Snowflake

Getting ready

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Authors (1)

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