Interactive Pokemon Explorer

🎮 Interactive Pokémon Explorer

Explore correlations and patterns across 1,025+ Pokémon

# Load data
pokemon_data <- read_csv("data/pokemon_data_final_evolutions_enriched.csv") %>%
  mutate(
    generation_num = as.numeric(str_extract(generation, "\\d+")),
    is_legendary = as.logical(is_legendary),
    display_name = paste0(name, " (", type_1,
                         ifelse(is.na(type_2) | type_2 == "", "", paste0("/", type_2)), ")")
  ) %>%
  filter(!is.na(hp), !is.na(attack))  # Remove rows with missing data

# Summary stats
total_pokemon <- nrow(pokemon_data)
legendary_count <- sum(pokemon_data$is_legendary)
avg_total <- round(mean(pokemon_data$total, na.rm = TRUE))

Dataset Overview

742

Total Pokémon

101

Legendary

519

Avg Base Stats

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Interactive Exploration

🎯 Correlation Explorer

Explore relationships between different Pokémon attributes. Use the filters below to customize your view and discover patterns in the data!

Filter Options

Legendary Status

Legendary

Regular

Primary Type

Generation

Total Base Stats

Correlation Visualizations

⚔️ Attack vs Speed

🛡️ Defense vs HP

✨ Special Attack vs Special Defense

📋 Data Table

Browse and search through the complete Pokémon dataset. Click on column headers to sort, use the search boxes to filter data!

📊 Type Statistics

View aggregated statistics grouped by primary type. Discover which types have the highest average stats and legendary rates!

Tips & Usage

💡 Tip: Click and drag on any chart to zoom in. Double-click to reset. Use the filters in the Correlation Explorer tab to interactively explore different subsets of Pokémon!