Module # 2 Google Table, Tableau and Geographic map - LIS 4317


 Module # 2 Google Table, Tableau and Geographic map





In order to improve the way a Tableau map communicates, I would consider adding different visual elements and features. A couple of examples could involve the use of a color gradient for measurements like population density or temperature fluctuations, and use of color coding to indicate different categories or values. To highlight greater values or relevance, you could resize data points, such as circles, according to the relevant variable. To provide readers with more context, add labels to important data points and include legends explaining color coding and size variance. 

You can effectively arrange and structure visual elements by utilizing Gestalt Laws, such as closeness, resemblance, and continuity. In order to communicate spatial patterns and interdependence, highlight the connections between neighboring data points. For geographical context, it's important to think about including a background map with elements like rivers, highways, or topography. To make a visually appealing and educational map, explore and match these decisions with your unique ideas.

Comments

Post a Comment

Popular posts from this blog

LIS 4370: Module # 10 Building your own R package

Module # 10 Building your own R package  GitHub Link:  https://github.com/agremer/LIS4370/blob/main/DESCRIPTION%20File DECRIPTION File : Package : DataVisTools Title : Alec Gremer's Data Visualization Test Implementation Version : 0.1.0.9000 Authors@R : "Alec Gremer, agremer@usf.edu [aut, cre]" Description : DataVisTools is an R package designed to streamline data visualization tasks by offering a versatile set of functions. It will include interactive visualization features, customizable plot aesthetics, statistical visualization tools, geospatial mapping capabilities, and time series analysis functions. Comprehensive documentation and an MIT License will ensure ease of use and widespread adoption. Implementation will prioritize S3 classes and methods for flexibility.  Depends : R (>= 3.1.2) License : CC0 LazyData : true For the final project, I proposed an R package named DataVisTools, which will serve as a comprehensive toolkit for data visualization tasks. Thi...
Read more

LIS 4317 Final Project: Fuel Economy Data from the U.S Dept. of Energy

Image
  LIS 4317 Final Project: Fuel Economy Data from the U.S Dept. of Energy Investigating the association between vehicle features and CO2 emissions in a dataset comprising fuel efficiency data is the issue statement for my final project. The objective is to ascertain the extent to which CO2 emissions differ among various vehicle classes. In order to evaluate the effects of automobiles on the environment and pinpoint possible areas where fuel efficiency regulations could be strengthened, further investigation is essential. The idea suggests that specific vehicle classes, like larger cars or ones with bigger engines, might have more CO2 emissions than other car classes. This issue is set within the larger framework of transportation research and environmental sustainability. The relationship between vehicle characteristics and emissions, particularly CO2 emissions, has been well studied in the past. Numerous techniques, such as statistical evaluations and graphics, have been used to in...
Read more

LIS 4317: Module # 10 assignment

Image
  Module # 10 assignment Time series data is important in many fields, such as finance, economics, and weather forecasting. It is defined as observations taken at repeated time intervals. Finding patterns, drawing conclusions, and coming to wise decisions all depend on the visualization of such data. First, we take a look at the 'economics' dataset that is integrated into ggplot2, which includes economic indicators for a number of years. This dataset contains variables like population, unemployment rate, and median length of unemployed. Using a time series graphic of the unemployment rate, we first investigate patterns and variations in the dataset.  By charting the median length of unemployment across time, we can see possible long-term trends or seasonal patterns. Furthermore, we explore combination visualization methods, comparing and contrasting several time series plots for investigation of correlation or comparability. The flexible framework of ggplot2 allows analysts an...
Read more