Reference no: EM132715172

Discussion 1:

Data viz follows a particular chart type, determined by the data and story you are giving. Temporal graph type is much suited in trends and activities that are shown over time for cross-comparison purposes. This level of data chart has numerous kinds of visualization that include hours, days, months, and years. This type of representation is depicted in a cyclic design because of the nature of the time-day and night.

The primary concern of temporal viz is understanding time-based regular intervals and variances, or prediction query. The time-series data and sequential trends can be visualized using multiple temporal charts like line graphs. The study of mankind's activities usually follows a sequential event (Ren et al., 2018).

Another type is the Spatial chart type that focuses on understanding data physically using a form of map visualization as a core chart type. The data are represented in various maps serving different functions in improving the visualization (Kirk, et al., 2016). Color encoding in choropleth maps is important in showing data attributes.

The characteristic values are encoded with the area scopes through a distortion of physical space by cartograms. And tile grid maps make the spatial scopes' shape and size uniform for the encoded color data to be observed with ease and compare. Again, the grid maps select any size of scope and this makes it easier for the smaller ones.

The categorical chart compares the numerical values' categories and dissemination (Kirk, et al., 2016). It handles multivariate data represented either categorically or numerically. The visualization of these data objects in understanding the patterns of the data attributes. The data can be visualized in more than one form of graphs. Box-plot graph viz in a one-dimension graph and represent data quartiles ranges if the data is numerical. Bar-graphs type is abundant in representing numerical data more effectively e.g. student grade. Another characteristic is color visualization of values in heatmaps.

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