This is my first Data Science project, leveraging real-world data from multiple sources to produce actionable insights. The focus of this project is on analyzing temperature, rainfall, and river flow rate data for São Félix do Xingu, a city located in the Amazon Rainforest in the State of Pará, Brazil. The objective is to answer key questions: Have temperatures risen over the past 30+ years? Has this impacted rainfall patterns and the river's flow rate?
The goal is to understand the effects of deforestation on the city's climate and provide insights into potential future changes. The entire project is implemented in Python, utilizing libraries such as Pandas, NumPy, and Matplotlib for data analysis and visualization.
The project is divided into three main parts:
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Temperature Analysis This section is built using historical data from the INMET (National Institute of Meteorology) Weather Station. Here, we focus on temperature data, covering everything from data cleaning to final analysis.
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Rainfall Analysis Using additional data from INMET, this part analyzes daily rainfall levels, recorded in millimeters.
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River Flow Rate Analysis Leveraging open data from the National Water Agency (ANA), we analyze the flow rate levels of the Xingu River.
After thoroughly examining these three datasets, we draw conclusions about the impact of deforestation on local climate patterns.