Python for Data Analysis
🎥 Python with Data Analysis Course - 25 Days to Mastery! 📊
Welcome to our in-depth 25-day Python with Data Analysis course! Whether you're a beginner or looking to deepen your skills, this comprehensive series will guide you through Python programming and data analysis step-by-step.
🔍 What You'll Learn:
Week 1: Python Fundamentals
Day 1: Install Python, set up Jupyter Notebooks, and explore basic syntax, variables, and data types.
Day 2: Control structures including conditionals and loops.
Day 3: Functions and modules: defining, calling, and importing.
Day 4: Essential data structures: lists, tuples, dictionaries, and sets.
Day 5: String handling, formatting, and regular expressions.
Day 6: File handling: reading and writing text and CSV files.
Day 7: Error handling and custom exceptions.
Week 2: NumPy and Pandas Basics
Day 8: Introduction to NumPy: arrays, operations, and indexing.
Day 9: Advanced NumPy: mathematical functions and broadcasting.
Day 10: Pandas basics: creating and operating on Series and DataFrames.
Day 11: DataFrame manipulation: indexing, selecting, and handling missing data.
Day 12: Data cleaning with Pandas: renaming, dropping columns, and changing data types.
Day 13: Working with dates and times; basics of time series analysis.
Day 14: Data aggregation and grouping with GroupBy operations.
Week 3: Data Visualization
Day 15: Introduction to Matplotlib: basic and customized plots.
Day 16: Advanced Matplotlib: subplots and exporting plots.
Day 17: Getting started with Seaborn: creating and customizing statistical plots.
Day 18: Advanced Seaborn: pairplots and heatmaps.
Day 19: Interactive visualizations with Plotly.
Day 20: Mini-project: Create a dashboard with interactive visualizations.
Week 4: Applied Data Analysis
Day 21: Starting a data analysis project: defining the problem and understanding the data.
Day 22: Exploratory Data Analysis (EDA): descriptive statistics and visualizing relationships.
Day 23: Data preprocessing: feature engineering and transformation.
Day 24: Case Study: Analyze a real-world dataset.
Day 25: Capstone Project: Define, collect, clean, analyze data, and present findings.
📚 Resources:
Course Materials: [Link to materials]
Code Samples: [Link to GitHub repo or other resources]
📅 Follow Along:
Subscribe: [Subscribe link]
Join the Community: [Link to forum or social media group]
Leave a Comment: Share your progress or ask questions below!
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