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Data Wrangling with SQL

Data Wrangling with SQL

By : Raghav Kandarpa, Shivangi Saxena
4.6 (25)
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Data Wrangling with SQL

Data Wrangling with SQL

4.6 (25)
By: Raghav Kandarpa, Shivangi Saxena

Overview of this book

The amount of data generated continues to grow rapidly, making it increasingly important for businesses to be able to wrangle this data and understand it quickly and efficiently. Although data wrangling can be challenging, with the right tools and techniques you can efficiently handle enormous amounts of unstructured data. The book starts by introducing you to the basics of SQL, focusing on the core principles and techniques of data wrangling. You’ll then explore advanced SQL concepts like aggregate functions, window functions, CTEs, and subqueries that are very popular in the business world. The next set of chapters will walk you through different functions within SQL query that cause delays in data transformation and help you figure out the difference between a good query and bad one. You’ll also learn how data wrangling and data science go hand in hand. The book is filled with datasets and practical examples to help you understand the concepts thoroughly, along with best practices to guide you at every stage of data wrangling. By the end of this book, you’ll be equipped with essential techniques and best practices for data wrangling, and will predominantly learn how to use clean and standardized data models to make informed decisions, helping businesses avoid costly mistakes.
Table of Contents (21 chapters)
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1
Part 1:Data Wrangling Introduction
4
Part 2:Data Wrangling Techniques Using SQL
9
Part 3:SQL Subqueries, Aggregate And Window Functions
13
Part 4:Optimizing Query Performance
15
Part 5:Data Science And Wrangling

SQL aggregate functions

We've covered aggregate functions in the previous chapter, but here's a quick refresher before we compare them with window functions. SQL aggregate functions are functions that perform calculations on a set of values and return an aggregated result after summarization. These functions are used to summarize data within a specified window of rows related to the current row in the result set.

Figure 9.2 – SQL aggregate functions

Figure 9.2 – SQL aggregate functions

Some of the most commonly used SQL aggregate functions are as follows:

  • SUM: Returns the sum of values for a specified column
  • AVG: Returns the average of values for a specified column
  • MIN: Returns the minimum value for a specified column
  • MAX: Returns the maximum value for a specified column
  • COUNT: Returns the number of rows in a specified window

These aggregate functions can be used in conjunction with a window specification to perform complex calculations and...

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