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Python Data Analysis

You're reading from   Python Data Analysis Perform data collection, data processing, wrangling, visualization, and model building using Python

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Product type Paperback
Published in Feb 2021
Publisher Packt
ISBN-13 9781789955248
Length 478 pages
Edition 3rd Edition
Languages
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Authors (2):
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Ivan Idris Ivan Idris
Author Profile Icon Ivan Idris
Ivan Idris
Avinash Navlani Avinash Navlani
Author Profile Icon Avinash Navlani
Avinash Navlani
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Toc

Table of Contents (20) Chapters Close

Preface 1. Section 1: Foundation for Data Analysis
2. Getting Started with Python Libraries FREE CHAPTER 3. NumPy and pandas 4. Statistics 5. Linear Algebra 6. Section 2: Exploratory Data Analysis and Data Cleaning
7. Data Visualization 8. Retrieving, Processing, and Storing Data 9. Cleaning Messy Data 10. Signal Processing and Time Series 11. Section 3: Deep Dive into Machine Learning
12. Supervised Learning - Regression Analysis 13. Supervised Learning - Classification Techniques 14. Unsupervised Learning - PCA and Clustering 15. Section 4: NLP, Image Analytics, and Parallel Computing
16. Analyzing Textual Data 17. Analyzing Image Data 18. Parallel Computing Using Dask 19. Other Books You May Enjoy

Reading and writing data from MySQL

MySQL is a fast, open-source, and easy-to-use relational or tabular database. It is suitable for small and large business applications. It is very friendly with database-driven web development applications. There are lots of ways to access data in Python from MySQL. Connectors such as MySQLdb, mysqlconnector, and pymysql are available for MySQL database connectivity. For this connectivity purpose, you should install a MySQL relational database and the mysql-python connector. The MySQL setup details are available on its website: https://www.mysql.com/downloads/.

You can use the pymysql connector as the client library and it can be installed using pip:

pip install pymysql

We can establish a connection with the following steps:

  1. Import the library.
  2. Create a database connection.
  3. Create a cursor object.
  4. Execute the SQL query.
  5. Fetch the records or response for the update or insert the record.
  6. Close the connection.

In our examples, we are trying database...

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