At a glance, data visualization is about drawing a picture with your data rather than providing numbers and facts. Going by this definition, anything put forth to represent the data counts. But not every way of representation is apt for every situation. Different situations(depending on the data and audience) call for specific ways of representing data. With that in mind, I am listing out five different ways of data representation and their optimal usage.
1) Bar Graphs
Bar graphs could be horizontal, vertical or stacked. While horizontal graphs are used mainly for comparative ranking, vertical graphs(column) are used for showing chronological data. Stacked charts are a bit more complicated in that they usually show the part to whole relationship. The problem for bar graphs, in general, is that it gets cluttered if there is a huge amount of data to be represented. Moreover, labeling would be difficult with a cluttered graph.
2) Maps
Maps form one of the most complete ways of representing data when various geographical areas have to be compared/contrasted. Maps can do more than just displaying data. They can direct action as well. Despite all this, maps have their disadvantages as well. Simply put, if the data that needs to be visualized does not involve a geographical area, it doesn’t need a map. Moreover, as with bar graphs, too much data can clutter the map and filling the map with data points doesn’t make for a pleasant viewing, not to mention inundating the viewer.
3) Line charts
Trends. Dynamism. Volatility. Line charts portray these aspects with an unerring efficiency. They display relationships in how data changes over a period of time. A cursory glance at the line chart given below lets the viewer know that the amount of sales by means of credit cards were the highest(this is just a minute part of what the whole chart says).
As with most other ways of representations, line charts become confusing if the number of variables to be represented shoot up. Besides, a legend is imperative to decipher the meaning of the chart and the viewer may be forced to constantly refer to the same for interpretation.
4) Area charts
Like its close relative, area charts too are most effective when used to represent time series relationships and for facilitating trend analyses. Area charts are of two types, unstacked(which is basically a line chart with enclosed colored areas) and stacked area charts. Stacked area charts and more informative and consequently, is used more. They portray a part to the whole relationship.
As long as one sticks to stacked charts for representing a part to the whole relationship of not more than 6-7 values, an area chart seems to be a perfect choice. Unstacked charts clutter quickly and can be used only for 3 or fewer values.
5) Scatter plots
If correlation in a large data set is what one needs out of a representation, scatter plots are the way to go. The data set needs to be in pairs with a dependent and an independent variable. Upon distribution of data, the result would show a positive/negative/neutral correlation. The addition of a trend line would make it more informative by highlighting the correlation and shows how statistically significant it is.
Contrary to most other forms of data representation, scatter plots need a large amount of data to appear meaningful. A scatter plot with only a few variables would appear empty, with little to no information provided for the viewer.
Source : http://www.datapine.com/blog/how-to-choose-the-right-data-visualization-types/