SQL to Python for Beginners

Name: SQL to Python for Beginners
Rating: 4.5 (184 reviews)

An intro Course illustrating SQL equivalents in Python

Created byOscar Valles

Last updated 4/2022

English

What you'll learn

Learn Python by Example
Learn to translate SQL into Python
Manipulate data in Python like you would with SQL
Become familiar with the Pandas library in Python

Course content

3 sections • 20 lectures • 43m total length

Introduction1:39
Quick intro to the course and the suggested prerequisites.
The following resource information is also found here:
Data Connection properties
github code URL

SQL Limit Records1:11
To select a sample of rows in SQL, you use the keyword "LIMIT", the equivalent function in Python is shown here.
SQL Distinct1:27
Covering the equivalent of Select Distinct using Python Pandas
SQL Select Columns1:26
How to select only a subset of columns using Python Pandas
SQL Where Clause1:44
Simple filtering in Python Pandas, the "Where" clause in SQL
SQL Multiple Where Clause1:54
How to apply multiple filter conditions in Python Pandas (i.e. the counterpart to where, and in SQL)
SQL IN ( )3:09
Selecting a subset of values using Python, just like the SQL IN statement
SQL NOT IN ( )2:28
Selecting items not in a subset of values using Python (i.e. just like SQL NOT IN statement)
SQL Average1:45
Computing the average on your data in Python
SQL Max1:09
Retrieving the max in your data using Python
SQL Min0:49
Retrieving the min in your data using Python
Computing the Mode1:53
The rarely easy to compute in most SQL databases. Python does it with ease.
SQL Group by Sum2:17
Group By aggregates in Python: sum
SQL Group by Avg2:36
Group By aggregates in Python: average/mean
SQL Group by Count1:34
Group By aggregates in Python: count
SQL Group with Multiple Aggregates2:00
Group By aggregates in Python: multiple and different aggregates
SQL Row Number Function4:15
I use row_number in SQL alot, what is the Python counterpart?
SQL Case Statement5:15
Using functions to parallel SQL case statements. (spoiler, you can get more sophisticated with Python)
SQL Joins4:11
Our favorite must have feature are SQL Joins when working with data! So how do we do this using Python Pandas?

Requirements

Basic Knowledge of Python

Description

Overview

In this course you will learn how to use the Python Pandas library to achieve the core SQL functionality listed below.

If you are ready to make the leap from SQL to Python, this course will help you through your adoption and increased usage of Python for data manipulation, transformation and ultimately data analysis.

Understanding how to achieve SQL data manipulation features in Python will serve as your foundation for using Python for advanced analysts, data science and other machine learning tasks.

Prerequisites

This course is recommended for anyone who is comfortable with SQL and would like to increase their adoption of Python for their day to day. It's also recommended that you have a base understanding of Python or some familiarity of any programming language in order to get the most of this course. Other prerequisites will be outlined in the Introduction video, but having the following set up on your computer ahead of time will allow you to dive right in.

Python 3.7 or above installed
pandas library installed (pip install pandas)
IDE (e.g. PyCharm, VS Code)
Git (optional, for cloning repo with code examples)

Core Concepts taught in this course

Core SQL Concepts translated to Python Pandas code are:

SQL Limit
SQL Distinct
SQL Where
SQL WHERE / AND (Multiple Predicates)
SQL IN ( )
SQL NOT IN ( )
SQL Aggregate Functions
- SQL MIN
- SQL MAX
- SQL COUNT
- SQL COUNT DISTINCT
- SQL AVERAGE / MEAN
Mode (Not usually available in most SQL databases)
SQL Group by Aggregates
SQL Row Number over (partition by / order by)
SQL Case Statements
SQL Joins

Thank you for enrolling in this course! Enjoy!

Who this course is for:

Data Analysts
Data Scientists new to Python
Business Intelligence Analysts

SQL to Python for Beginners

What you'll learn

Explore related topics

Course content

Introduction1 lecture • 2min

SQL to Python using Python Pandas18 lectures • 41min

Outro1 lecture • 1min

Requirements

Description

Who this course is for: