📊 Data Science Foundations

Complete hands-on learning notebooks for Pandas,NumPy,Polars,Plotly,Rich,SQL,DuckDB and Streamlit — built through structured practice, chapter by chapter.
Every chapter includes concept explanations, working code, and a dedicated practice set.

🔄 Actively updated as learning progresses toward freelance Data Science.

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📚 Pandas — Complete Reference Notebook

12 Chapters | Practice Sets Included

Chapter	Topic	Key Methods
1	Introduction to Pandas	pd.DataFrame(), pd.__version__
2	DataFrame Basics	head(), tail(), describe(), info()
3	Saving & Loading Data	to_csv(), read_csv(), read_excel()
4	Rows & Columns Selection	loc[], iloc[], boolean masking
5	Add, Update & Delete	drop(), sort_values()
6	Working with Dates	to_datetime(), .dt accessor, Timedelta
7	Missing Values	fillna(), dropna(), ffill(), bfill()
8	GroupBy & Aggregation	groupby(), agg(), transform(), apply()
9	Concat & Merge	pd.concat(), pd.merge()
10	AI-Assisted Coding	Prompting strategies, query()
11	Duplicate Values	duplicated(), drop_duplicates()
12	Reshape	melt(), pivot(), pivot_table()

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📚 NumPy — Complete Reference Notebook

8 Chapters | Practice Sets Included

Chapter	Topic	Key Methods
1	Lists vs NumPy	np.array, np.mean
2	Creating Arrays	zeros, ones, arange, eye, randint
3	Array Properties	shape, size, ndim, dtype, astype
4	Mathematical Operations	sum, mean, std, median, percentile
5	Indexing & Slicing	Boolean masking, fancy indexing
6	Important Functions	reshape, flatten, concatenate, split
7	Broadcasting & Vectorization	Scalar × array, np.newaxis, one-hot encoding
8	Handling Missing Values	isnan, nanmean, nan_to_num, isinf

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🐻 Polars — Complete Reference Notebook

8 Chapters | Pandas vs Polars Benchmark Included

Chapter	Topic	Key Methods
1	Installation & Setup	!pip install polars, pl.__version__
2	Creating DataFrames	pl.DataFrame(), pl.read_csv()
3	Select & Filter	select(), filter(), pl.col()
4	Adding & Modifying Columns	with_columns(), .alias()
5	GroupBy & Sort	group_by(), .agg(), sort()
6	Join & Concat	join(), concat()
7	Lazy vs Eager Execution	.lazy(), .explain(), .collect()
8	Polars vs Pandas Benchmark	Polars 6x faster on 1M rows

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📊 Plotly — Complete Reference Notebook

6 Chapters | Polars + Plotly Dark Theme Included

Chapter	Topic	Key Methods
1	Installation & Setup	import plotly.express as px, import polars as pl
2	Loading DataFrames	pl.DataFrame(), sample sales / trend / scatter data
3	Bar Chart	px.bar(), x=, y=, title=, template=
4	Line Chart	px.line(), markers=True, trend visualization
5	Scatter Plot	px.scatter(), size=, color=, relationship analysis
6	Layout Customization	fig.update_layout(), axis labels, dark theme

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🎨 Rich for Data Science — Professional CLI Reference

3 Essential Chapters | Terminal Styling & Progress Tracking

Chapter	Topic	Key Methods
1	Beautiful Prints	from rich import print for colored, nested data inspection
2	Structured Tables	Table(), add_column(), add_row() for grids
3	Progress Tracking	track(iterable) for live status bars in loops

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🦆 DuckDB + SQL — Complete Reference Notebook

8 Lessons | Polars vs SQL Comparison Included

Lesson	Topic	Key Methods
1	Installation & Connection	duckdb.connect(':memory:'), con.execute()
2	SELECT & WHERE	SELECT col FROM df WHERE condition
3	GROUP BY & Aggregation	GROUP BY, SUM(), AVG(), AS
4	Hybrid Workflow	Query Polars DataFrames directly — no import needed
5	Full Pipeline	DuckDB query → .df() → Plotly chart

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Approach: Every SQL concept is shown side-by-side with its Polars equivalent. Zero SQL background needed — if you know Polars, you already know the logic.

Stack: Python 3.12 · DuckDB · Polars · Plotly · Rich · Google Colab

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📚 Streamlit Basics – Lessons 1 to 3

5 Core Topics | Beginner Friendly

Chapter	Topic	Key Methods
1	UI Foundation	st.title(), st.write()
2	Layout & Navigation	st.sidebar
3	Interactive Widgets	st.selectbox()
4	Data Display	st.dataframe()
5	Visualization	st.plotly_chart()

🛠️ Tools & Environment

🗺️ Learning Roadmap

Phase 01 ✅  Python + OOP          — Completed
Phase 02 ✅  Pandas + NumPy        — Completed (this repo)
Phase 03 ✅  Polars + Plotly       — Completed (this repo)
Phase 04 ✅  Rich                  — Completed (this repo)
Phase 05 ✅  DuckDB + SQL          — Completed (this repo)
Phase 06 ✅  Streamlit             — Completed (this repo)

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👤 Author

Muhammad Ali Rajput
Python Developer | Aspiring Data Scientist
GitHub