By analyzing snowfall data and developing predictive models for cost-effective snow removal, you’ll build the skills that are critical for local governments, especially those in snow-prone regions. In this guided project, you’ll use the History on Demand Direct API from IBM Environmental Intelligence to access and analyze historical weather data. You’ll correlate that snowfall data with maintenance costs, building your skills in budget planning and resource management. This project gives you the opportunity to get hands-on experience in data-driven decision-making, preparing you to make a tangible impact on the planning and efficiency of snow removal operations. Whether you are an aspiring data analyst, a local government official, or simply interested in the intersection of weather data and public resource management, this project is a valuable addition to your skillset.

Note: To complete this project, you must register to receive free access to the IBM Environmental Intelligence API keys. The process is simple and steps are provided in the project.

After completing this project, you will be able to:
– Access and extract historical weather data using the History on Demand Direct API.
– Correlate snowfall data with maintenance costs to identify trends and insights.
– Develop predictive models for budget planning and resource allocation in snow removal.
– Enhance your data-driven decision-making skills for efficient management of public resources.

Example: Can you analyze and apply lessons from this graph

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Before starting this guided project, ensure that you have:
– Basic knowledge of data analysis and statistics.
– Familiarity with Python programming language.
– Access to a modern web browser like Chrome, Edge, Firefox, Internet Explorer, or Safari.