🚀 SQL & Python Quick Cheatsheet for Beginners
🗄️ SQL Programming
1. What is SQL?
SQL stands for Structured Query Language. It is used to communicate with databases and work with stored data.
You can use SQL to:
✅ Retrieve data
✅ Filter data
✅ Analyze data
✅ Insert data
✅ Update data
✅ Delete data
2. SELECT
Used to retrieve data from a table.
SELECT name, salary FROM employees;
SELECT → columns you want
FROM → table you want data from
To get all columns:
SELECT * FROM employees;
3. WHERE
Used to filter rows.
SELECT * FROM employees WHERE salary > 50000;
Common operators:
= Equal
Greater than
< Less than
= Greater than or equal
<= Less than or equal
<> Not equal
4. AND, OR, NOT
Used to combine conditions.
SELECT * FROM employees WHERE salary > 50000 AND department = 'IT';
AND → both conditions must be true.
SELECT * FROM employees WHERE department = 'IT' OR department = 'HR';
OR → at least one condition must be true.
5. ORDER BY
Used to sort your results.
SELECT * FROM employees ORDER BY salary DESC;
ASC → Lowest to highest
DESC → Highest to lowest
6. DISTINCT
Used to remove duplicate values.
SELECT DISTINCT department FROM employees;
7. LIMIT
Used to restrict the number of rows returned.
SELECT * FROM employees LIMIT 10;
Note: Some databases use TOP or FETCH.
8. Aggregate Functions
Used to perform calculations on multiple rows.
COUNT() -- Count
SUM() -- Total
AVG() -- Average
MIN() -- Minimum
MAX() -- Maximum
Example:
SELECT AVG(salary) FROM employees;
9. GROUP BY
Used to create groups and calculate results for each group.
SELECT department, AVG(salary) AS average_salary FROM employees GROUP BY department;
10. HAVING
Used to filter grouped results.
SELECT department, AVG(salary) AS average_salary FROM employees GROUP BY department HAVING AVG(salary) > 70000;
WHERE → filters rows
HAVING → filters groups
🐍 Python — Beginner Fundamentals
1. What is Python?
Python is a general-purpose programming language used for:
✅ Data Analytics
✅ Automation
✅ AI & Machine Learning
✅ Data Engineering
✅ Web Development
2. Variables
Variables store values.
name = "Alex" age = 25 salary = 50000
3. Data Types
Important beginner data types:
name = "Alex" # str age = 25 # int salary = 50000.5 # float active = True # bool
type(age)
4. Strings
Strings represent text.
name = "Python"
name.upper() # PYTHON name.lower() # python name.strip() # removes spaces
5. Numbers
Python supports integers and floating-point numbers.
age = 25 price = 99.50
10 + 5 # Addition 10 - 5 # Subtraction 10 * 5 # Multiplication 10 / 5 # Division 10 % 3 # Remainder 10 ** 2 # Power
6. Boolean
Boolean values represent True or False.
is_logged_in = True
7. Lists
Lists store multiple values in an ordered collection.
numbers = [10, 20, 30, 40]
numbers[0] # Output: 10
Python indexing starts from 0.
8. Dictionaries
Dictionaries store data as key-value pairs.