/PredictingWaterQuality

Primary LanguageJupyter Notebook

Predicting Water Quality

Abstract

Humanity have some fundamental needs for existing and the most important of these is water. However, some people continue to pollute lakes, seas and oceans. Water pollution is mostly a result of oil spills and industrial wastes. On the other hand, studies are carried out in many areas to prevent water pollution. When we heard about the presence of algae that clean water and increase the water quality , we decided to focus on this issue. In this project, we aimed to create a model that predicts which waters needed this algae.

Directory Structure

  • Root
    • Notebooks
      • CollectData.ipynb (Collected data from WorldBank, SEDAC, Data Europa, Foursquare, OSM)
      • EDAWaterPolllutionDataFolium.ipynb (Visualized our main water pollution data with Folium)
      • PreProcessWaterPollutionData.ipynb (Prepared final data)
      • WaterPredictionModel.ipynb (Created classfication and regression models)
      • concatData.ipynb (Concatenated all external data with main data)
      • fullDataEDA.ipynb (Exploratory data analysis on final data)
    • Reports
      • PredictingWaterQualityReport.pdf
      • PredictingWaterQualityReport.tex
    • Datasets
      • climateData.csv
      • literacyRate.csv
      • migrationData.csv
      • population_2018.csv
      • protectedMarines.csv
      • renewable.csv
      • touristData.csv
      • wasteData.csv
      • waterPollution.csv
    • Images
    • requirements.txt

Because of some storage problem we couldn't upload all datasets. You can reach all datasets from this drive link

This repository is created by Ozgur Dogan, Dilara Sahan and Oguzhan Sahin.