1. Visualizing the Impact of Covid-19: Temporal Trends in Crude and Vaccination Rates by Zip Code in San Diego (ACM_COVID_MLC_SD)
Link: https://drive.google.com/file/d/1EK3WSMiQ6k5U9DjrUZrPgYaHu2eTmEnX/view?usp=drive_link
Dashboard Summary: Title: Visualizing the Impact of Covid-19 in San Diego: This interactive dashboard utilizes the Adaptive Choropleth Mapper (ACM) library to visualize and analyze the impact of Covid-19 in San Diego. The data for visualization is sourced from the "SD_Confirmed_Vaccine_Final_v5.csv" dataset, containing crucial variables such as geo IDs, confirmed cases, vaccination rates, and other Covid-19 metrics. Additionally, geographical coordinates of San Diego places are loaded from the "SanDiego_Zip_COVID.shp" shapefile using the geospatial library, Geopandas. The dashboard's primary objective is to provide an insightful analysis of Covid-19 trends and vaccination rates across different zip codes in San Diego. It offers a user-friendly interface with multiple linked charts to facilitate data exploration and comparison. The dashboard comprises two side-by-side choropleth maps, a bar chart, and temporal line charts that enable users to gain a comprehensive understanding of the pandemic's impact on various regions.
Link: https://drive.google.com/file/d/1FLXNJ9ZWvZz7n3fPdevXtB498urajhem/view?usp=drive_link
Dashboard Summary: Visualizing Covid-19 Crude Rates Across San Diego Zip Codes Over Time This interactive dashboard utilizes the Adaptive Choropleth Mapper (ACM) library to visualize and compare the impact of Covid-19 crude rates across different zip codes in San Diego over time. The data for visualization is sourced from the "SD_Confirmed_Vaccine_Final_v5.csv" dataset, which contains relevant variables such as geo IDs and confirmed cases per 10,000 population. The geographical coordinates of San Diego places are loaded from the "SanDiego_Zip_COVID.shp" shapefile using the geospatial library, Geopandas.
Link: https://drive.google.com/file/d/1_wT78jS54IsvFjtu3045xIeXaKmfvBJy/view?usp=drive_link Dashboard Summary: Visualizing Covid-19 Vaccination Trends Across San Diego Zip Codes Over Time This interactive dashboard leverages the Adaptive Choropleth Mapper (ACM) library to visualize and compare Covid-19 vaccination trends across different zip codes in San Diego over time. The data for visualization is sourced from the "Vaccine" dataset, which contains relevant variables such as vaccination rates per 10,000 population. Geographical coordinates of San Diego places are loaded from the "SanDiego_Zip_COVID.shp" shapefile using the geospatial library, Geopandas. Functions and Key Concepts:
Dashboard Objective: The primary objective of this dashboard is to provide a visual comparison of Covid-19 vaccination rates across different zip codes in San Diego over time. Users can interactively explore vaccination trends and identify variations in vaccine coverage among various regions. Data Loading and Preparation:
Link: https://drive.google.com/file/d/1_e2ajrY4bYcqBZMLw2KiCmzxDLPVzDZQ/view?usp=drive_link
Dashboard Summary: Temporal Patterns of Covid-19 Crude Rate and Vaccinated Rate in US Counties This interactive dashboard utilizes the Adaptive Choropleth Mapper (ACM) library to visualize and analyze temporal patterns of Covid-19 crude rate and vaccinated rate at the zip code level in US counties for the year 2020. The data for visualization is sourced from the "Covid_Rate_daily_counties_mainland.csv" dataset, which includes essential variables such as geo IDs, confirmed rate, death rate, and cumulative rates. Additionally, the geographical coordinates of US counties are loaded from the "counties.shp" shapefile using the geospatial library, Geopandas.
Dashboard Objective: The main objective of this dashboard is to provide a comprehensive understanding of temporal patterns in Covid-19 crude rate and vaccinated rate across US counties at the zip code level throughout the year 2020. By visualizing and analyzing these temporal patterns, users can identify trends and variations in Covid-19 metrics.
Link: https://drive.google.com/file/d/1VT4-uqxQztjQ0QlHoT04__C7AcWFX1Uv/view?usp=drive_link
Dashboard Summary: Comparison of Temporal Patterns of Covid-19 Crude Rate Between US Counties This interactive dashboard employs the Adaptive Choropleth Mapper (ACM) library to visualize and compare temporal patterns of Covid-19 crude rate among various US counties. The dataset used for visualization is "Covid_Rate_daily_counties_mainland.csv," which contains crucial variables such as geo IDs and Covid-19 confirmed rates. Geographical coordinates of US counties are loaded from the "counties.shp" shapefile using the geospatial library, Geopandas.
Dashboard Objective: The primary objective of this dashboard is to facilitate a comprehensive comparison of temporal patterns in Covid-19 crude rate across different US counties. By visualizing these patterns over time, users can gain insights into the variations and trends in Covid-19 metrics among different regions.