Map of All Bigfoot Sightings in the Dataset with Mouseover

Write-Up

This map visualizes every sighting of bigfoot in the dataset plotted by latitude and longitude. You can mouse-over each sighting to reveal the title of the sighting as entered in the dataset. I encoded the latitude and longitude data using altair’s latitude and longitude encoding type and made their data-type quantitative. I did not transform the data in anyway nor did I filter it. However, I did add an interactive element to the visualization. I think this map could function as the driver of a dashboard where each point could include an href linking out to another page of the website on the sighting. In this way, this visualization could work as a landing page for a bigfoot sighting database.

Dashboard of All Bigfoot Sightings in Latitude and Longitude Ranges Over Time

Write-Up

This dashboard links the latitude and longitude range of bigfoot sightings on a scatter plot to a bar chart counting the number of bigfoot sightings within the latitude and longitude range per year. I encoded the latitude and longitude as x and y encoding types and quantitative data types. This is because I wanted to use a scatter plot. Moreover, I colored point on the scatter plot based on the season in which the sighting occurred. I encoded the the year data in the second chart as temporal. The count of records per year in the y field of the second chart is quantitative by default. In this plot, I used altair’s time unit transformations to extract just the year from the date information in the dataset. This visualization is most similar to those I created in starboard for homework 9. For Homework 9, I created 2 visualizations: one visualized the number of bigfoot sightings per state and another visualized bigfoot sightings over time. This visualization enables a user to see the temporal patterns of bigfoot sightings in a latitude and longitude range of their choosing.

Search The Data & Methods

Both plots 1 and 2 were created using the same dataset within the same jupyter notebook. View both below.