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Showing posts from September, 2024

Mod 5 plot.ly

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Daniel Tafmizi Dr. Friedman September 30, 2024 Lis 4317 Module 5 Plot.ly:  Online Graph Maker · Plotly Chart Studio Part to whole analysis is a graphical technique that breaks down data into separate parts for further analysis. Bar charts and pie charts are commonly used to represent the data aggregated by this technique. Sometimes the scales are too wide; to combat this the scales should be re-expressed through the square root, the log, or the inverse. These should be attempted in order until the data is properly scaled.

Module 4

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Daniel Tafmizi Dr. Friedman September 23, 2024 Lis 4317 Module 4 Tableau:  Book6 | Tableau Public Tableau is nice. Earlier today, I took some time to clean the data. I grouped the dataset by year and summed the riders, vehicle collisions, and person collisions. This left me with a small data frame that tableau would be able to handle. At some point of inserting the above image, it clicked for me that tableau does the necessary data cleaning for you. Earlier, I was concerned that tableau would not be able to handle the dataset without some simplification. I was wrong, and without further cleaning of the data the following line chart took about 45 seconds to make. Thats pretty cool. 

Module 3 adobe

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 Daniel Tafmizi Dr. Friedman September 16, 2024 Lis 4317 I used vector elements in adobe illustrator to style and implement tableau's legend, create a colorful title, and create a text box for my data source information. I cannot say I enjoyed using the adobe platform, but it was fairly straightforward. 

Module 2 tableau

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 Daniel Tafmizi Dr. Friedman September 5, 2024 Lis 4317 Module 2: Mapping Florida's Trails by County Sources:  US County Boundaries — Opendatasoft  ,  Florida Existing Trails | Koordinates I used the County Boundaries data set to get Florida's counties names and geo coordinates. I used Florida existing trails (FET) dataset for trail data. I had to clean some of the data in R. The FET data was outdated and required new county names. After I standardized the county names across the two datasets, I was able to create my own data frame of countyName, latitude, longitude, trailCount, and mileage. I pushed the data into Tableau and applied them to a symbol map. Mileage is represented through a size scale on each point. Trail count is represented through a color scale on each point.  For my next geographic map, I would like to add county borders. I would put a heat map effect to represent mileage. I think this will make the data easier to understand and quickly show th...