Skill
SQL for Data Practitioners: Filtering
April 2022 with Jonathan Barrios
- Entry
- 5 videos
- 59 mins
So far, you’ve learned to use the SELECT statement to return data from tables. You also used the SELECT DISTINCT keywords together to return unique results. Finally, you learned how to use the COUNT() function to count the number of rows that match a specific query.
In this set of videos, you will learn about filtering to select subsets of data that match specific criteria. To accomplish this, you will combine the SELECT and WHERE statements, which are a fundamental part of SQL statements you will often use. Additionally, you will use the WHERE keyword to specify conditions on columns to return rows that contain particular data. For example, SELECT will specify the columns FROM a specific table, WHERE conditions are met.
In this set of videos, you will learn about filtering to select subsets of data that match specific criteria. To accomplish this, you will combine the SELECT and WHERE statements, which are a fundamental part of SQL statements you will often use. Additionally, you will use the WHERE keyword to specify conditions on columns to return rows that contain particular data. For example, SELECT will specify the columns FROM a specific table, WHERE conditions are met.
Recommended Experience
Jonathan Barrios has been a CBT Nuggets trainer since 2021. His expertise areas include full-stack software development, data science, and machine learning. He has experience using the following technologies: HTML, CSS, JavaScript, PHP, Python, SQL, NoSQL, and frameworks/libraries such as Vue, React, Django, NumPy, Pandas, Matplotlilb, Scrappy, BeautifulSoup, SciPy, Seaborn, Plotly, Scikit-learn, Tensorflow, and PySpark.
- None
- Data Analysts
- Data Practitioners
- SQL Developers
Jonathan Barrios has been a CBT Nuggets trainer since 2021. His expertise areas include full-stack software development, data science, and machine learning. He has experience using the following technologies: HTML, CSS, JavaScript, PHP, Python, SQL, NoSQL, and frameworks/libraries such as Vue, React, Django, NumPy, Pandas, Matplotlilb, Scrappy, BeautifulSoup, SciPy, Seaborn, Plotly, Scikit-learn, Tensorflow, and PySpark.

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