🧠 Data Anaylsis Portfolio — DataCamp EDA Projects

📚 Python Data Fundamentals Course Overview

• Python Data Fundamentals Track Overview
  • Introduction to Python
  • Intermediate Python
  • Data Manipulation with pandas
  • Joining Data with pandas
  • Introduction to Statistics in Python
  • Introduction to Data Visualization with Seaborn
  • Exploratory Data Analysis in Python

🎓 Data Analyst in Python – Learning Journey

Welcome! This repository documents my learning progress in the Data Analyst in Python career track on DataCamp. Each course has its own folder, and each chapter is saved as a Jupyter notebook. Projects and assessments are also included to showcase applied learning.

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📈 Learning Progress

Category	Completed	Total	Progress
📘 Courses	7	9	78%
📊 Projects	3	4	75%
🧪 Assessments	2	2	✅
Total	12	15	80% 🎉

Overall Progress: [████████████████████████████████████████░░░░░░░░░] 80%

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🏅 Badges Earned

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📚 Course Overview

1. Introduction to Python

• Python Basics
• Python Lists
• Functions and Packages
• NumPy

2. Intermediate Python

• Logic, Control Flow and Filtering
• Loops
• Dictionaries and Pandas
• Pandas Techniques

3. Data Manipulation with pandas

• Transforming DataFrames
• Aggregating Data
• Filtering and Sorting
• Grouping Data

4. Joining Data with pandas

• Inner Joins
• Outer Joins
• Merging Multiple Tables
• Merging with Join Types

5. Introduction to Statistics in Python

• Summary Statistics
• Random Numbers & Probability
• More Distributions and the Central Limit Theorem

6. Introduction to Data Visualization with Seaborn

• Introduction to Seaborn
• Creating Visualizations
• Customizing Plots
• Advanced Visualization Techniques

7. Exploratory Data Analysis in Python

• Data Cleaning & Imputation
• Getting to Know a Dataset
• Relationships in Data
• Turning Exploratory Analysis into Insights

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🛠 Projects

• Investigating Netflix Movies
• Exploring NYC Public School Test Results
• Visualizing the History of Nobel Prize Winners
• Analyzing Crime in Los Angeles

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⚠️ Disclaimer

All course content, datasets, and exercises used in this repository are based on the Data Analyst in Python career track by DataCamp.

This repository is intended for personal learning purposes only.
All materials and solutions are my own notes or interpretations and do not replicate DataCamp’s proprietary content verbatim.

Please respect DataCamp’s content license and terms of use.