📘 A complete collection of Python notes, exercises, and practical examples
from my learning journey with PW Skills, structured by topic for easy revision.
| Folder Name | Contents |
|---|---|
01_Python_Basics |
Variables, Operators, Typecasting, Conditionals, Loops |
02_Data_Structures |
Strings, Lists, Tuples, Sets, Dictionaries |
03_Functions_and_Lambda |
Functions, Scope, Lambda, map, reduce, filter |
04_Object_Oriented_Programming |
Classes, Inheritance, Abstraction, Polymorphism, Decorators |
05_Data_Toolkit_and_Visualization |
NumPy, pandas, Matplotlib, Seaborn, Plotly, Debugging |
06_File_Handling_and_Exceptions |
File I/O, JSON, Exception Handling, Logging |
📁 02_Data_Structures
- 📓 01_data_structure.ipynb
- 📓 02_strings.ipynb
- 📓 03_lists.ipynb
- 📓 [04_tupels and sets.ipynb](02_Data_Structures/04_tupels and sets.ipynb)
- 📓 05_ditionary.ipynb
- 🐍 test.py
📁 04_Object_Oriented_Programming_OOP
- 📓 01_oops.ipynb
- 📓 [02_inheritance and abstraction.ipynb](04_Object_Oriented_Programming_OOP/02_inheritance and abstraction.ipynb)
- 📓 [03_polymorphism and encapsulation.ipynb](04_Object_Oriented_Programming_OOP/03_polymorphism and encapsulation.ipynb)
- 📓 [04_class and static.ipynb](04_Object_Oriented_Programming_OOP/04_class and static.ipynb)
- 📓 05_dunder_method.ipynb
- 📓 06_decorators.ipynb
- 📓 07_property_dec.ipynb
- 📓 live_24aug.ipynb
- 📓 live_25aug.ipynb
- 📓 test.ipynb
📁 05_Data_Toolkit_and_Visualization
- 📓 01_Numpy.ipynb
- 📓 02_numpy_adv_1.ipynb
- 📓 03_numpy_adv_2.ipynb
- 📓 [04_pands basic.ipynb](05_Data_Toolkit_and_Visualization/04_pands basic.ipynb)
- 📓 [05_pandas adv1.ipynb](05_Data_Toolkit_and_Visualization/05_pandas adv1.ipynb)
- 📓 [06_pandas adv02.ipynb](05_Data_Toolkit_and_Visualization/06_pandas adv02.ipynb)
- 📓 07_pandas_adv03.ipynb
- 📓 08_pandas_adv04.ipynb
- 📓 09_Matplotlib.ipynb
- 📓 10_seaborn.ipynb
- 📓 11_plotly.ipynb
- 📓 12_bokeh.ipynb
- 📓 13_logging&debugging.ipynb
- 📄 Bank_churn.csv
- 📄 [LUSID Excel - Setting up your market data.xlsx](05_Data_Toolkit_and_Visualization/LUSID Excel - Setting up your market data.xlsx)
- 📓 [live 1st sep.ipynb](05_Data_Toolkit_and_Visualization/live 1st sep.ipynb)
- 📓 [live 31st.ipynb](05_Data_Toolkit_and_Visualization/live 31st.ipynb)
- 📄 services.csv
- 📄 taxonomy.csv
- 🌐 test.html
📁 06_File_Handling_and_Exceptions
- 📄 Memory maanagement
- 📄 pwskills
- 📄 test
- 📓 [01_FIlesHandling basic.ipynb](06_File_Handling_and_Exceptions/01_FIlesHandling basic.ipynb)
- 📓 [02_Reading and writing.ipynb](06_File_Handling_and_Exceptions/02_Reading and writing.ipynb)
- 📓 [03_Exceptional handling.ipynb](06_File_Handling_and_Exceptions/03_Exceptional handling.ipynb)
- 📓 [04_General use of exception handling.ipynb](06_File_Handling_and_Exceptions/04_General use of exception handling.ipynb)
- 📓 05_interpreted_vs_complied.ipynb
- 📓 13_logging&debugging.ipynb
- 📄 exam.txt
- 📄 example.txt
- 📄 example_csv.csv
- 📄 file.txt
- 📄 file_json.json
- 📓 live14th.ipynb
- 📦 test_bin.bin
- 📄 test_buf.txt
⚙️ Other Files
- ⚙️ .gitattributes
- ⚙️ .gitignore
- 📖 README.md
✅ Clean Jupyter Notebooks with examples
✅ Practice tests & live session notes
✅ Structured for revision & project reference
✅ Useful for data science interviews and coding rounds
🧠 Python Basics
- Variables, Mutability
- Conditionals, Loops, Operators
📦 Data Structures
- Lists, Tuples, Sets, Dictionaries
- String methods & manipulations
🔁 Functions & Lambda Tools
- Iterators, Generators
- Lambda Expressions,
map(),reduce(),filter()
🧱 OOP Concepts
- Classes & Objects
- Inheritance, Encapsulation, Abstraction, Polymorphism
- Decorators & Dunder Methods
📊 Data Toolkit & Visualization
- NumPy, pandas (beginner to advanced)
- Matplotlib, Seaborn, Plotly, Bokeh
- Logging & Debugging
🗂️ File Handling & Exception Handling
- Reading/writing
.txt,.csv,.json - Try-Except blocks & Logging
- Memory management basics
| Topic | Status |
|---|---|
| Python Basics | ✅ Done |
| Data Structures | ✅ Done |
| Functions & Lambda | 🔄 In Progress |
| OOP | 🔄 In Progress |
| Data Toolkit & Visualization | 🔄 In Progress |
| File Handling & Exception Handling | 🔄 In Progress |
🔹 To revise Python efficiently
🔹 To showcase my skills and organized learning
🔹 To build a strong base for Data Science & Analytics
🔹 To maintain a reusable reference for projects
- Clone this repo or download ZIP
- Open any notebook by topic
- Run & tweak examples to reinforce learning
- Update progress and notes
- 👨🏫 Special thanks to PW Skills, Ajay Kumar Gupta, and the entire teaching team.
- 💡 Inspired by live classes and real-world practice.
📍 LinkedIn: Swaraj Ranjan Behera
📬 Email: swarajranjan2003@gmail.com
🌱 Currently Revising: Python + ML + SQL
⭐ If you find this helpful, consider starring the repo or sharing feedback!