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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 Pandas Foundations Essential DataFrame Operations Creating and Persisting DataFrames Beginning Data Analysis Exploratory Data Analysis Selecting Subsets of Data Filtering Rows Index Alignment Grouping for Aggregation, Filtration, and Transformation Restructuring Data into a Tidy Form Combining Pandas Objects Time Series Analysis Visualization with Matplotlib, Pandas, and Seaborn Debugging and Testing Pandas Other Books You May Enjoy
Index

Translating SQL WHERE clauses

Many pandas users will have experience of interacting with a database using Structured Query Language (SQL). SQL is a standard to define, manipulate, and control data stored in a database

SQL is an important language for data scientists to know. Much of the world's data is stored in databases that require SQL to retrieve and manipulate it SQL syntax is fairly simple and easy to learn. There are many different SQL implementations from companies such as Oracle, Microsoft, IBM, and more.

Within a SQL SELECT statement, the WHERE clause is very common and filters data. This recipe will write pandas code that is equivalent to a SQL query that selects a certain subset of the employee dataset.

Suppose we are given a task to find all the female employees who work in the police or fire departments who have a base salary of between 80 and 120 thousand dollars.

The following SQL statement would answer this query for us:

SELECT
    UNIQUE_ID...
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