ankkur13/driven-data-hackathon-pump-it-up-data-mining-the-water-table

Online Data Science Competition on Driven Data website under top 5% of the leaderboard

Pump-it-Up-Data-Mining-the-Water-Table

Goal is to predict the operating condition of a waterpoint for each record in the dataset. You are provided the following set of information about the waterpoints:

• amount_tsh - Total static head (amount water available to waterpoint)
• date_recorded - The date the row was entered
• funder - Who funded the well
• gps_height - Altitude of the well
• installer - Organization that installed the well
• longitude - GPS coordinate
• latitude - GPS coordinate
• wpt_name - Name of the waterpoint if there is one
• num_private -
• basin - Geographic water basin
• subvillage - Geographic location
• region - Geographic location
• region_code - Geographic location (coded)
• district_code - Geographic location (coded)
• lga - Geographic location
• ward - Geographic location
• population - Population around the well
• public_meeting - True/False
• recorded_by - Group entering this row of data
• scheme_management - Who operates the waterpoint
• scheme_name - Who operates the waterpoint
• permit - If the waterpoint is permitted
• construction_year - Year the waterpoint was constructed
• extraction_type - The kind of extraction the waterpoint uses
• extraction_type_group - The kind of extraction the waterpoint uses
• extraction_type_class - The kind of extraction the waterpoint uses
• management - How the waterpoint is managed
• management_group - How the waterpoint is managed
• payment - What the water costs
• payment_type - What the water costs
• water_quality - The quality of the water
• quality_group - The quality of the water
• quantity - The quantity of water
• quantity_group - The quantity of water
• source - The source of the water
• source_type - The source of the water
• source_class - The source of the water
• waterpoint_type - The kind of waterpoint
• waterpoint_type_group - The kind of waterpoint

Distribution of Labels

The labels in this dataset are simple. There are three possible values:

• functional - the waterpoint is operational and there are no repairs needed
• functional needs repair - the waterpoint is operational, but needs repairs
• non functional - the waterpoint is not operational

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Link for DataSet : https://www.drivendata.org/competitions/7/data/