Pandas Data Analysis

SKILL.md

Data manipulation, analysis, and visualization with Pandas, NumPy, and Matplotlib.

Covers DataFrame and Series creation, indexing, filtering, and type conversions for structured data handling

Includes data cleaning techniques: missing value handling, deduplication, string operations, and date/time parsing

Provides GroupBy aggregation, pivot tables, multi-level indexing, and window functions for exploratory analysis

Integrates Matplotlib and Seaborn for statistical plotting, trend visualization, and correlation analysis

Three hands-on projects cover customer analytics, time series analysis, and automated data quality reporting

Pandas Data Analysis

Overview

Master data analysis with Pandas, the powerful Python library for data manipulation and analysis. Learn to clean, transform, analyze, and visualize data effectively.

Learning Objectives

Load and manipulate data from various sources (CSV, Excel, SQL, APIs)

Clean and transform messy datasets

Perform exploratory data analysis (EDA)

Aggregate and group data for insights

Create compelling visualizations

Optimize performance for large datasets

Core Topics