Pokeanalysis and Predicting Legendaries
This dataset consist a 721 pokemons of the 1 to 6 Generations, including several features like stats, types, catch rate, if the pokemon is legendary and others, totaling 21 variables. With him we will try to answer the fallowing questions:
- How the amount of pokemons is distributed per generation?
- Is there missing data in this dataset?
- Is there any relationship between the type of pokemon and it’s color?
- Which pokemons have the highest attributes values? and lowest?
- Are there correlations between other attributes?
- Can we find clusters among pokemons?
- Can we create a classifying model for legendary pokemons?
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Project link: https://github.com/SergioSJS/data_science_portfolio/tree/master/pokemon-data-analysing