Pandas & Data
Ship a real notebook: pandas the way a data analyst actually uses it.
🌿 Normal
Series & DataFrame Basics
Pandas core data structures: creating Series from lists and dicts, building DataFrames, reading CSV files, and inspecting your data.
Selection, Filtering & Indexing
Extract the data you need: select columns, filter rows with boolean conditions, and use loc/iloc for precise access.
Data Cleaning
Fix real-world mess: handle missing values, convert dtypes, apply string operations, and use loc/iloc for targeted edits.
GroupBy, Aggregation & Merging
Split-apply-combine with groupby, compute aggregations, and combine DataFrames with merge, join, and concat.
Guided Titanic EDA
Put it all together: load the Titanic dataset, explore its structure, clean it, and answer real analytical questions.
⚡ Hard
EDA Framework & Profiling
Learn to frame analytical questions, assess dataset quality, and build a systematic profiling workflow before touching any visualization.
Univariate Analysis & Visualization
Master distributions, summaries, and visual encoding for single variables using matplotlib and seaborn.
Bivariate & Multivariate Analysis
Explore relationships between variables with scatter plots, pair plots, and correlation matrices.
Advanced & Storytelling Visualizations
Move beyond default plots to publication-quality figures and data storytelling that drives action.
Students Performance EDA Report
Apply the full EDA pipeline to the Students Performance in Exams dataset and produce a polished final report.