md `Show Multiple Dimensions: The geospatial data under Rape Crimes in India By State is commuting the population + literacy levels of India by State. This data is limited to 2011 because that’s when the census was last conducted for these 2 pieces of information. However, there are more graphs below that are communicating via colour gradience, the number of rape cases reported by State. The bar charts show the case status and people status by State with the added funtionality of filtering by the Population Type. Use Data From More Than One Source: 3 datasets -- crime_data, india_pop, india_literacy Filtering: The user can filter by the population they are interested in via the dropdown option; they can choose between General Population, Scheduled Castes, Scheduled Tribes. General Population is referring to the overall population, Scheduled Castes is a sub-set of the population at a disadvantage and Scheduled Tribes are small groups of people that live in the forests. Brushing and Linking: For the type of data I had available, brushing didn’t quite align so instead the user can click on a State of this choropleth map and see the linked bar graphs below with the updated stats. Details on Demand: There is a tooltip available for the geo-visualization when the user hovers of a State, it reveals the state population, literacy rate and other information. Multiple Views: All the 4 maps are interactive. Visualization Idiom: Colour gradience/saturation is used to communicate area density in maps. The reason for using geo-vis is to communicate the spatial data as this dataset and the scope of my product is heavily reliant on where the rapes are happening and looking at the temporal trends. Additionally a choropleth map seems like the best for as all the data I am working with contains information by state. The bar charts are colour coded with a legend to help communicate the difference in each item. The height (horizontal) is used to communicate the magnitude of how high the numbers are. Bar graphs are great for communicating a nominal data type combined with a quantitative data type to show the relationship. They allow the user to quickly pick up on the differences between the 2 charts. `