Hello,
In our analysis, i started by preparing the data for time series exploration. We created a new date column by combining the existing “Year” and “Month” columns and set it as the index for our DataFrame. This step was crucial for organizing the data in a time series format, enabling us to analyze how economic indicators change over time.
After the data preparation, we focused on trend analysis for several key economic indicators. These indicators included “Logan Passengers,” “Logan International Flights,” “Hotel Occupancy Rate,” “Hotel Average Daily Rate,” “Total Jobs,” “Unemployment Rate,” “Median Housing Price,” and “Housing Sales Volume.” Our objective was to visualize the trends in these economic factors over time.
I presented the trend analysis results through a series of line plots. Each plot represented one economic indicator, and the x-axis displayed time, while the y-axis represented the values of the respective indicator. This visualization allowed us to observe how these economic variables evolved over the years.
My analysis provided valuable insights into the long-term trends of these economic factors, which can be instrumental in making informed decisions related to economic planning, tourism strategies, and housing market assessments.