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Pandas 1.x Cookbook - Second Edition

You're reading from  Pandas 1.x Cookbook - Second Edition

Product type Book
Published in Feb 2020
Publisher Packt
ISBN-13 9781839213106
Pages 626 pages
Edition 2nd Edition
Languages
Authors (2):
Matt Harrison Matt Harrison
Profile icon Matt Harrison
Theodore Petrou Theodore Petrou
Profile icon Theodore Petrou
View More author details

Table of Contents (17) Chapters

Preface 1. Pandas Foundations 2. Essential DataFrame Operations 3. Creating and Persisting DataFrames 4. Beginning Data Analysis 5. Exploratory Data Analysis 6. Selecting Subsets of Data 7. Filtering Rows 8. Index Alignment 9. Grouping for Aggregation, Filtration, and Transformation 10. Restructuring Data into a Tidy Form 11. Combining Pandas Objects 12. Time Series Analysis 13. Visualization with Matplotlib, Pandas, and Seaborn 14. Debugging and Testing Pandas 15. Other Books You May Enjoy
16. Index

Working with databases

We mentioned that pandas is useful for tabular or structured data. Many organizations use databases to store tabular data. In this recipe, we will work with databases to insert and read data.

Note that this example uses the SQLite database, which is included with Python. However, Python has the ability to connect with most SQL databases and pandas, in turn, can leverage that.

How to do it...

  1. Create a SQLite database to store the Beatles information:
    >>> import sqlite3
    >>> con = sqlite3.connect("data/beat.db")
    >>> with con:
    ...     cur = con.cursor()
    ...     cur.execute("""DROP TABLE Band""")
    ...     cur.execute(
    ...         """CREATE TABLE Band(id INTEGER PRIMARY KEY,
    ...         fname TEXT, lname TEXT, birthyear INT)"""
    ...     )
    ...     cur.execute(
    ...         """INSERT INTO Band VALUES(
    ...         0, &apos...
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