✅SQL Checklist for Data Analysts 📀🧠
1. SQL Basics⦁ SELECT, WHERE, ORDER BY
⦁ DISTINCT, LIMIT, BETWEEN, IN⦁ Aliasing (AS)
2. Filtering & Aggregation
⦁ GROUP BY & HAVING⦁ COUNT(), SUM(), AVG(), MIN(), MAX()
⦁ NULL handling with COALESCE, IS NULL
3. Joins
⦁ INNER JOIN, LEFT JOIN, RIGHT JOIN, FULL OUTER JOIN
⦁ Joining multiple tables
⦁ Self Joins
4. Subqueries & CTEs
⦁ Subqueries in SELECT, WHERE, FROM
⦁ WITH clause (Common Table Expressions)
⦁ Nested subqueries
5. Window Functions
⦁ ROW_NUMBER(), RANK(), DENSE_RANK()
⦁ LEAD(), LAG()
⦁ PARTITION BY & ORDER BY within OVER()
6. Data Manipulation
⦁ INSERT, UPDATE, DELETE
⦁ CREATE TABLE, ALTER TABLE
⦁ Constraints: PRIMARY KEY, FOREIGN KEY, NOT NULL
7. Optimization Techniques
⦁ Indexes
⦁ Query performance tips
⦁ EXPLAIN plans
8. Real-World Scenarios
⦁ Writing complex queries for reports
⦁ Customer, sales, and product data
⦁ Time-based analysis (e.g., monthly trends)
9. Tools & Practice Platforms
⦁ MySQL, PostgreSQL, SQL Server
⦁ DB Fiddle, Mode Analytics, LeetCode (SQL), StrataScratch
10. Portfolio & Projects
⦁ Showcase queries on GitHub
⦁ Analyze public datasets (e.g., ecommerce, finance)
⦁ Document business insights
1. SQL Basics⦁ SELECT, WHERE, ORDER BY
⦁ DISTINCT, LIMIT, BETWEEN, IN⦁ Aliasing (AS)
2. Filtering & Aggregation
⦁ GROUP BY & HAVING⦁ COUNT(), SUM(), AVG(), MIN(), MAX()
⦁ NULL handling with COALESCE, IS NULL
3. Joins
⦁ INNER JOIN, LEFT JOIN, RIGHT JOIN, FULL OUTER JOIN
⦁ Joining multiple tables
⦁ Self Joins
4. Subqueries & CTEs
⦁ Subqueries in SELECT, WHERE, FROM
⦁ WITH clause (Common Table Expressions)
⦁ Nested subqueries
5. Window Functions
⦁ ROW_NUMBER(), RANK(), DENSE_RANK()
⦁ LEAD(), LAG()
⦁ PARTITION BY & ORDER BY within OVER()
6. Data Manipulation
⦁ INSERT, UPDATE, DELETE
⦁ CREATE TABLE, ALTER TABLE
⦁ Constraints: PRIMARY KEY, FOREIGN KEY, NOT NULL
7. Optimization Techniques
⦁ Indexes
⦁ Query performance tips
⦁ EXPLAIN plans
8. Real-World Scenarios
⦁ Writing complex queries for reports
⦁ Customer, sales, and product data
⦁ Time-based analysis (e.g., monthly trends)
9. Tools & Practice Platforms
⦁ MySQL, PostgreSQL, SQL Server
⦁ DB Fiddle, Mode Analytics, LeetCode (SQL), StrataScratch
10. Portfolio & Projects
⦁ Showcase queries on GitHub
⦁ Analyze public datasets (e.g., ecommerce, finance)
⦁ Document business insights
30-day roadmap to learn Python up to an intermediate level
Week 1: Python Basics
*Day 1-2:*
- Learn about Python, its syntax, and how to install Python on your computer.
- Write your first "Hello, World!" program.
- Understand variables and data types (integers, floats, strings).
*Day 3-4:*
- Explore basic operations (arithmetic, string concatenation).
- Learn about user input and how to use the
- Practice creating and using variables.
*Day 5-7:*
- Dive into control flow with if statements, else statements, and loops (for and while).
- Work on simple programs that involve conditions and loops.
Week 2: Functions and Modules
*Day 8-9:*
- Study functions and how to define your own functions using
- Learn about function arguments and return values.
*Day 10-12:*
- Explore built-in functions and libraries (e.g.,
- Understand how to import modules and use their functions.
*Day 13-14:*
- Practice writing functions for common tasks.
- Create a small project that utilizes functions and modules.
Week 3: Data Structures
*Day 15-17:*
- Learn about lists and their operations (slicing, appending, removing).
- Understand how to work with lists of different data types.
*Day 18-19:*
- Study dictionaries and their key-value pairs.
- Practice manipulating dictionary data.
*Day 20-21:*
- Explore tuples and sets.
- Understand when and how to use each data structure.
Week 4: Intermediate Topics
*Day 22-23:*
- Study file handling and how to read/write files in Python.
- Work on projects involving file operations.
*Day 24-26:*
- Learn about exceptions and error handling.
- Explore object-oriented programming (classes and objects).
*Day 27-28:*
- Dive into more advanced topics like list comprehensions and generators.
- Study Python's built-in libraries for web development (e.g., requests).
*Day 29-30:*
- Explore additional libraries and frameworks relevant to your interests (e.g., NumPy for data analysis, Flask for web development, or Pygame for game development).
- Work on a more complex project that combines your knowledge from the past weeks.
Throughout the 30 days, practice coding daily, and don't hesitate to explore Python's documentation and online resources for additional help. Learning Python is a dynamic process, so adapt the roadmap based on your progress and interests.
Best Programming Resources: https://topmate.io/coding/886839
ENJOY LEARNING 👍👍
Week 1: Python Basics
*Day 1-2:*
- Learn about Python, its syntax, and how to install Python on your computer.
- Write your first "Hello, World!" program.
- Understand variables and data types (integers, floats, strings).
*Day 3-4:*
- Explore basic operations (arithmetic, string concatenation).
- Learn about user input and how to use the
input() function.- Practice creating and using variables.
*Day 5-7:*
- Dive into control flow with if statements, else statements, and loops (for and while).
- Work on simple programs that involve conditions and loops.
Week 2: Functions and Modules
*Day 8-9:*
- Study functions and how to define your own functions using
def.- Learn about function arguments and return values.
*Day 10-12:*
- Explore built-in functions and libraries (e.g.,
len(), random, math).- Understand how to import modules and use their functions.
*Day 13-14:*
- Practice writing functions for common tasks.
- Create a small project that utilizes functions and modules.
Week 3: Data Structures
*Day 15-17:*
- Learn about lists and their operations (slicing, appending, removing).
- Understand how to work with lists of different data types.
*Day 18-19:*
- Study dictionaries and their key-value pairs.
- Practice manipulating dictionary data.
*Day 20-21:*
- Explore tuples and sets.
- Understand when and how to use each data structure.
Week 4: Intermediate Topics
*Day 22-23:*
- Study file handling and how to read/write files in Python.
- Work on projects involving file operations.
*Day 24-26:*
- Learn about exceptions and error handling.
- Explore object-oriented programming (classes and objects).
*Day 27-28:*
- Dive into more advanced topics like list comprehensions and generators.
- Study Python's built-in libraries for web development (e.g., requests).
*Day 29-30:*
- Explore additional libraries and frameworks relevant to your interests (e.g., NumPy for data analysis, Flask for web development, or Pygame for game development).
- Work on a more complex project that combines your knowledge from the past weeks.
Throughout the 30 days, practice coding daily, and don't hesitate to explore Python's documentation and online resources for additional help. Learning Python is a dynamic process, so adapt the roadmap based on your progress and interests.
Best Programming Resources: https://topmate.io/coding/886839
ENJOY LEARNING 👍👍
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Question: What are Python set comprehensions?
Answer:Set comprehensions are similar to list comprehensions but create a set instead of a list. The syntax is:
For example, to create a set of squares of even numbers:
This will create a set with the values
Answer:Set comprehensions are similar to list comprehensions but create a set instead of a list. The syntax is:
{expression for item in iterable if condition}For example, to create a set of squares of even numbers:
squares_set = {x**2 for x in range(10) if x % 2 == 0}This will create a set with the values
{0, 4, 16, 36, 64}🐍 Python Roadmap
1️⃣ Basics: 📝📜 Syntax, Variables, Data Types
2️⃣ Control Flow: 🔄🤖 If-Else, Loops, Functions
3️⃣ Data Structures: 🗂️🔢 Lists, Tuples, Dictionaries, Sets
4️⃣ OOP in Python: 📦🎭 Classes, Inheritance, Decorators
5️⃣ File Handling: 📄📂 Read/Write, JSON, CSV
6️⃣ Modules & Libraries: 📦🚀 NumPy, Pandas, Matplotlib
7️⃣ Web Development: 🌍🔧 Flask, Django, FastAPI
8️⃣ Automation & Scripting: 🤖🛠️ Web Scraping, Selenium, Bash Scripting
9️⃣ Machine Learning: 🧠📈 TensorFlow, Scikit-learn, PyTorch
🔟 Projects & Practice: 📂🎯 Create apps, scripts, and contribute to open source
1️⃣ Basics: 📝📜 Syntax, Variables, Data Types
2️⃣ Control Flow: 🔄🤖 If-Else, Loops, Functions
3️⃣ Data Structures: 🗂️🔢 Lists, Tuples, Dictionaries, Sets
4️⃣ OOP in Python: 📦🎭 Classes, Inheritance, Decorators
5️⃣ File Handling: 📄📂 Read/Write, JSON, CSV
6️⃣ Modules & Libraries: 📦🚀 NumPy, Pandas, Matplotlib
7️⃣ Web Development: 🌍🔧 Flask, Django, FastAPI
8️⃣ Automation & Scripting: 🤖🛠️ Web Scraping, Selenium, Bash Scripting
9️⃣ Machine Learning: 🧠📈 TensorFlow, Scikit-learn, PyTorch
🔟 Projects & Practice: 📂🎯 Create apps, scripts, and contribute to open source
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