Pokémon Data Analytics Dashboard

An interactive Streamlit dashboard for exploring Pokémon statistics, type patterns, capture difficulty, and legendary classification.

An interactive data analytics dashboard that transforms Pokémon data into structured visual insights through exploratory analysis, statistical profiling, and machine learning.

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Highlights

  • Built a modular Streamlit dashboard with interactive navigation and Plotly-based visualizations.
  • Analyzed dual-type combinations, type distributions, base-stat profiles, and legendary ratios.
  • Developed a normalized capture difficulty metric to compare Pokémon across types and generations.
  • Created type-level statistical profiles based on HP, Attack, Defense, Special Attack, Special Defense, and Speed.
  • Trained an SGD-based logistic classifier to predict legendary status using numerical and categorical Pokémon features.
  • Structured the project into reusable modules for data cleaning, analysis, visualization, machine learning, and UI rendering.

Analysis Pipeline

Pokémon Dataset
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Data Cleaning & Feature Processing
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Exploratory Analysis + Machine Learning
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Interactive Plotly Visualizations
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Streamlit Dashboard

Tech Stack: Python · Streamlit · Pandas · NumPy · Plotly · scikit-learn