I initiated the analysis by importing economic indicators data and performing data preprocessing, which included converting the ‘Year’ and ‘Month’ columns to a date-time format. This step was crucial for temporal analysis as it allowed for a more nuanced exploration of trends over time.
Also, I employed Matplotlib to create a line plot, offering a visual representation of the passenger counts at Logan Airport across the temporal dimension. The resulting plot highlighted a discernible trend in passenger counts and notable fluctuations suggested potential variations in travel patterns or external factors influencing airport activity.
To delve deeper into the economic context, I computed a correlation matrix for three key indicators: total jobs, unemployment rate, and labor force participation rate. The matrix gave insightful relationships, including a robust negative correlation (-0.87) between total jobs and the unemployment rate, signifying an inverse relationship between employment levels and unemployment. Simultaneously, a robust positive correlation (0.86) emerged between total jobs and the labor force participation rate, suggesting that as job opportunities increased, so did the participation in the labor force. Additionally, a moderate negative correlation (-0.57) between the unemployment rate and labor force participation rate hinted at the complex interplay between these two indicators.
To enhance the analytical depth, I turned to Plotly Express for dynamic and interactive visualizations. The initial line chart provided a comprehensive view of the temporal evolution of total jobs, unemployment rate, and labor force participation rate. The subsequent dynamic bubble chart introduced additional dimensions, with the size of bubbles representing the unemployment rate, the color denoting the year, and an animated sequence unfolding over months. The third visualization, a scatter plot with animation, lets us in into the relationship between total jobs and labor force participation rate over the years, employing size and color variations to incorporate the unemployment rate as a contextual element.
Further exploring the analysis, I created a heatmap to visually represent the correlation matrix, providing an easily interpretable snapshot of the interrelationships among the economic indicators. Additionally, a 3D scatter plot was generated to explore the intricate relationships among total jobs, unemployment rate, and labor force participation rate in a three-dimensional space, offering a nuanced perspective on their co-variation.
In summary, the analysis encompassed a comprehensive exploration of spatiotemporal trends in Logan Airport passenger counts. It further delved into the intricate correlations among key economic indicators over time, leveraging a diverse set of visualization techniques to provide a nuanced understanding of the underlying dynamics.