Visualizing Extreme Weather Trends (2015) Introduction Welcome to the Extreme Weather Trends project! In this visualization, we explore the highs and lows of temperature data from 2015, focusing on identifying instances where records from the ten-year period (2005-2014) were broken. The goal is to assess whether extreme weather events are becoming more frequent.
Data Preparation To ensure accuracy, we've removed leap day data (February 29th) from our dataset. This step helps maintain consistency in our analysis and visualization.
Methodology We've overlaid a scatter plot of the 2015 data, highlighting points where record highs or lows from the previous decade were surpassed. This approach allows us to pinpoint specific instances of extreme weather events in 2015.
Visualization The graph is designed with clarity and precision in mind, adhering to the principles of correct data visualization techniques.
Here are the key features.
Scatter Plot: Each data point from 2015 is represented as a scatter point, with distinctive markers for record highs and lows.
Color Coding: Record highs and lows are visually differentiated using a color scheme, aiding quick identification.
Legend: A clear legend is provided, detailing the significance of each marker and ensuring the viewer can interpret the graph with ease.
Labels: Axes are labeled clearly, providing context for the temperature values. Additionally, a title conveys the purpose of the visualization.
Aesthetic Design: The graph is aesthetically pleasing, with a balanced use of color and minimal chart junk, ensuring a clean and professional appearance.
Observations Upon examination of the visualization, one can easily identify instances where 2015 broke temperature records. This allows for a visual assessment of whether extreme weather events were more frequent in that particular year.
Expected Visualization
Conclusion The Extreme Weather Trends project provides a visually compelling representation of temperature trends, offering insights into the occurrence of extreme weather events in 2015. This visualization aids in understanding whether the frequency of such events is on the rise, contributing valuable information to the ongoing discourse on climate patterns.
Final Output
