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You're reading from  Data Wrangling with SQL

Product typeBook
Published inJul 2023
PublisherPackt
ISBN-139781837630028
Edition1st Edition
Concepts
Data Engineering
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Authors (2):
Raghav Kandarpa
Raghav Kandarpa
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Raghav Kandarpa

Raghav Kandarpa is an experienced Data Scientist in Finance and logistics industry with expertise in SQL, Python, Building Machine Learning Models, Financial Data Modelling, and Statistical Analysis. He holds a Masters' degree in Business Analytics specializing in Data Science from the University of Texas at Dallas.
Read more about Raghav Kandarpa

Shivangi Saxena
Shivangi Saxena
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Shivangi Saxena

Shivangi Saxena is an experienced BI Engineer with proficiency in SQL, Data Visualization, and Statistical Analysis. She holds a master's degree in Information Technology and Management from the University of Texas at Dallas. She has several years of experience building several BI tools and products using SQL and BI reporting tools which has helped stakeholders to get visibility to the right data points
Read more about Shivangi Saxena

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Overview of aggregate functions in SQL

Aggregate functions in SQL are used to summarize and analyze data in a table or a query’s result set. These functions allow us to perform calculations on multiple rows of data and return a single value.

Figure 8.1 – Aggregate functions

Figure 8.1 – Aggregate functions

The most common aggregate functions include the following:

  • COUNT: This function returns the number of rows in a table or a result set that match a specific condition.
  • SUM: This function returns the sum of all values in a specific column. It is commonly used to calculate the total value of a numeric column, such as total sales or total salary.
  • AVG: This function returns the average value of a specific column. It is commonly used to calculate the average value of a numeric column, such as average salary or average price.
  • MIN: This function returns the minimum value of a specific column. It is commonly used to determine the lowest value in a column, such...
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Data Wrangling with SQL
Published in: Jul 2023Publisher: PacktISBN-13: 9781837630028
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Authors (2)

author image
Raghav Kandarpa

Raghav Kandarpa is an experienced Data Scientist in Finance and logistics industry with expertise in SQL, Python, Building Machine Learning Models, Financial Data Modelling, and Statistical Analysis. He holds a Masters' degree in Business Analytics specializing in Data Science from the University of Texas at Dallas.
Read more about Raghav Kandarpa

author image
Shivangi Saxena

Shivangi Saxena is an experienced BI Engineer with proficiency in SQL, Data Visualization, and Statistical Analysis. She holds a master's degree in Information Technology and Management from the University of Texas at Dallas. She has several years of experience building several BI tools and products using SQL and BI reporting tools which has helped stakeholders to get visibility to the right data points
Read more about Shivangi Saxena

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