PokemonGo is a mobile AR game, where players can catch virtual creatures Pokemon useGPS and camera on their phone. In this project, we predict where pokemon may appear and what king of pokemon will appear based on historical data in PokemonGo.
https://www.kaggle.com/semioniy/predictemall/home
This dataset consists of roughly 293,000 pokemon sightings (historical appearances of Pokemon), having coordinates, time, weather, population density, distance to pokestops/ gyms etc. as features.
pokemonCatch
|--Data
| |--pokemonNumbers.csv
| |--smalldata.csv
|--DataVisual
| |--OriginDataVisual.ipynb # original data visualization
| |--PredictDataVisual.ipynb # predict data visualiztion
|--FeatureExtraction
| |--CorrelationAnalysis.ipynb # Analysis correlation between features
| |--feature_abstract.ipynb #
| |--FeatureSelection.ipynb #
| |--OutputasCity.ipynb
| |--/PredictPokemonid.ipynb # predict pokemon id based on historical data
|--Pic
|--Predict
| |--predict_id.ipynb
| |--predic_location.ipynb
| |--SimilarPokemonPredict.ipynb
+--Result
python3.7 jupyter notebook pyspark
numpy pandas basemap seaborn matplotlib
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