Malombejoe/Tanzania_Water_Wells_Project

Tanzania-Water-Wells-Project # Tanzanian Water Wells Classification ## Business Case Basic sanitation facilities, clean water, and proper hygiene are necessary for children's survival and growth. Water- and sanitation-related infections rank among the top causes of death for children under five. More than 800 kids perish every day from diseases that could be prevented, brought on by dirty water and inadequate sanitation and hygiene. The water, sanitation, and hygiene (WASH) team of UNICEF works in more than 100 countries to enhance access to basic hygiene practices as well as water and sanitation services. Through UNICEF's efforts, almost 11 million people received basic toilets and close to 14 million people received clean water in the previous year. Given Tanzania's severe water issue, our present task is to forecast the state of the country's water wells. ## Objective of the project *Create a multi-classifier employing different machine learning methods to forecast the state of water wells.* #### Technologies Used: * Pandas for Data Cleaning * Matplotlib and Seaborn for Data Visualization * Numpy for Basic Calculations * Scikit Learn for Logistic Regression, Decision Trees, Random Forests, AdaBoost, and Gradient Boost ### Process Overview * Cast columns to the appropriate data types * Convert data types of 'object' to appropriate numerical data type * Identify and deal with null values appropriately * Filter data set * Convert all columns to contain only the top 5 most frequently seen values * Use Boruta algorithm in later stages to determine which features I wanted to keep for my model * Deal with categorical variables using dummy variables for modelling purposes ## Exploratory Data Analysis ### Distribution of Well Conditions ### Date Recorded of Wells ### Construction Years of Wells ### Distribution of the Altitude of Wells ### Distribution of the region codes of Wells ### Best Water Sources ### Best Water Quantity ### Best Wat …