stogaja/Tanzanian-Water-Project

Data Science Project to predict the state of pumps in Tanzania. Data Mining the water table # Tanzania Water Project : Data Mining the Water Table ## My analysis for the Driven Data competition By Sons of Analysts | Moringa School 2022 ## Research question The Driven Data competition describes the question as follows: >Can you predict which water pumps are faulty, broken or functional? >Using data from Taarifa and the Tanzanian Ministry of Water, can you predict which pumps are functional, which need some repairs, and which don't work at all? ... Predict one of these three classes based on a number of variables about what kind of pump is operating, when it was installed, and how it is managed. A smart understanding of which waterpoints will fail can improve maintenance operations and ensure that clean, potable water is available to communities across Tanzania. Picture: Wikimedia Commons ## The data Data can be obtained from the competition site by registering and downloading the data sets. Data set contains training variables, labels and test set for participating the competition. Total data size is 74250 observations, 40 independent variables and 1 dependent variable. Predicted status group can be either "functional", "non functional" or "functional needs repair". ## Tools * Google Colab + Jupyter * Numpy Stack, pandas, scikit-learn * Jira Kanban * Streamlit ## Methods * basic exploration methods * Decision Tree * XG Boost ### 1. Ask A Question This question is provided by the competition. >Can you predict which water pumps are faulty, functional or broken? ### 2. Get the Data * Colab notebook: Get the data ### 3. Explore the Data * Jupyter notebook: Explore the data * The main problem with the data is missing values: 12 of the 40 variables have missing data, which needs to be dealt with. Exploration revealed some potential ways to do imputation. * Categorical values need to be converted numerical. Numerical values might need to be normalized. Plotting 2000 pumps each by status_group ### 4. Model the data * Jupyter notebook: P …