Climate Change Analysis and Weather Forecasting

Climate change refers to long-term shifts in temperature patterns and weather conditions on Earth, primarily caused by human activities, such as the burning of fossil fuels and deforestation. It leads to a variety of adverse effects, including rising global temperatures, melting ice caps, extreme weather events, and rises in sea level. Such changes disrupt ecosystems, threaten biodiversity, and impact human livelihoods. Analyzing climate change over the years and making weather predictions helps us understand the long-term impact of human activities on the environment, mitigate potential risks, and adapt to changing conditions, ensuring the well-being of ecosystems, economies, and human populations.

In this project, we’ll explore climate change patterns over a 60-year period, from 1960 to 2020, using a dataset containing temperature and precipitation data. We’ll leverage popular data analysis tools like pandas and seaborn to visualize and analyze the historical weather data. Additionally, we’ll implement Facebook’s Prophet, a time series forecasting library, to make predictions about weather conditions for the next five years. The project will help us gain valuable insights into long-term climate trends and enhance data analysis skills and forecasting using Python libraries, such as Matplotlib and Plotly.