Python Journey

My daily Python learning projects. Every day new topics learnt.

Progress

• Day 1: Rock Paper Scissors game
• Day 2: Word Analyzer
• Day 3: Grocery List Manager
• Day 4: Tuples & Sets
• Day 5: Contact Book
• Day 6: Grade Calculator
• Day 7: FizzBuzz
• Day 8: 20 Small functions
• Day 9: Multi-Function Calculator
• Day 10: List Comprehensions exercies
• Day 11: File Handling & Log Writer & Student Database System using CSV & Pandas
• Day 12: Error Handling — try/except/finally + hardened Student Database
• Day 13: Error Handling — Grade Manager with full error handling, repair_file() & logging
• Day 14: Modules, Packages & pathlib — Grade Manager refactored into a package with pathlib
• Day 15: Library Management System with OOP — classes, init, self, JSON persistence
• Day 16: Library Management System extended — search_by_author(), list_available(), export_to_csv(), CSV re-import
• Day 17: Library Management System with OOP — inheritance & polymorphism, EBook & AudioBook subclasses, display_clean_data()
• Day 18: Library Management System with OOP — dunder methods (str, repr, lt), display_sorted() using object comparison
• Day 19: Decorators — @timer, @retry(n) decorator factory, @log_calls with logging module
• Day 20: Generators & Iterators — yield, lazy evaluation, generator pipelines
• Day 21: collections, datetime & type hints — Counter, defaultdict, deque, strptime, full type hints, log analyzer
• Day 22: NumPy — arrays, shapes, reshape, flatten, transpose, broadcasting, indexing, slicing
• Day 23: Weather Analyzer CLI — NumPy operations (argmax, argmin, np.where, mean), zone classification, timer context manager + logging
• Day 24: Pandas — indexing & filtering basics
• Day 25: CLI Data Explorer — Pandas filtering conditions
• Day 26: CSV File Data Cleaner
• Day 27: Two Panel Figure using matplotlib
• Day 28: 4 week revision
• Day 29: Test Analyser using pytest
• Day 30: Type hints — advanced + mypy
• Day 31: Mini EDA Project — Titanic

Topics Covered

Core Python

• Variables & Data Types
• Strings & Methods
• Lists, Tuples, Sets, Dictionaries
• If/elif/else, For & While Loops
• Functions, *args & **kwargs
• List Comprehensions
• Lambda (map, filter, reduce)
• Closures

File & Data Handling

• File Handling (Read, Write, Append)
• CSV File Handling
• pathlib
• JSON config loading

Error Handling & Modules

• Exception Handling — try/except/finally, ValueError, FileNotFoundError
• Modules & Packages

OOP

• Classes & Objects, __init__, instance attributes, self keyword
• Inheritance, Polymorphism & Method Overriding
• Dunder Methods — __str__, __repr__, __lt__

Advanced Python

• Decorators, functools.wraps, Decorator Factory pattern
• Generators & Iterators, yield keyword
• Context Managers — __enter__/__exit__
• Type Hints, mypy, pytest
• logging module — basicConfig, logging.info
• collections — Counter, defaultdict, deque
• datetime — strptime, strftime, timedelta

NumPy

• ndarray, shape, dtype, reshape, flatten, transpose
• Array math & broadcasting
• Boolean indexing & filtering
• np.random, np.where, np.argmax, np.argmin, np.mean

Pandas

• read_csv, .head(), .info(), .describe(), .shape, .dtypes
• Indexing — .loc[] & .iloc[]
• Boolean filtering & multi-conditions (&, |)
• .value_counts(), .unique(), .nunique()
• .sort_values(), groupby, dropna, idxmax, idxmin
• .groupby().agg(), .pivot_table(). .fillna(), .dropna(), .duplicated(), .drop_duplicates()

Matplotlib

• show, title, grid, legend, plot, xlabel, ylabel, savefig(), subplots
• bar, barh, reverse, style, xticks, tight_layout
• hist, axvline, use, linewidth, color
• scatter, s, c, edgecolor, marker, alpha, cmap, colorbar, set_label, xscale, yscale

Seaborn

• set_theme, load_dataset, relplot, displot, multiple, hue, kde, data
• heatmap, annot, cbar_kws