#chartingtechniques

Data Visualization – Charts, Graphs and Infographic designs - ThinkCell: Expert Q&A Guide

1.How to read 100% stacked area chart?   

A 100% stacked area chart displays the proportional contribution of different categories to a total overtime. Each area represents a category, and the height of each area indicates its percentage of the total. The chart allows you to compare the relative sizes of categories at different points, showing how each category's share changes over time while totaling 100%.

2. What is an advantage of using a 100% stacked area chart instead of an ordinary area chart in Excel?

A 100% stacked area chart emphasizes the relative contributions of each category to the total over time, showing the percentage distribution rather than absolute values. This makes it easier to compare the composition of different series at a glance, highlighting trends and shifts in proportions, which can be more informative for understanding overall patterns in the data.

3. How to show total in stacked area chart?

To show the total in a stacked area chart, you can add a line representing the cumulative total of all stacked areas. This line can be overlaid on the chart, using the same axis, to indicate the overall value. Alternatively, you can display data labels or annotations at key points to highlight the total values.

4. How do you plot a stacked area chart?

To plot a stacked area chart, use a data visualization library like Python. Prepare your data in a suitable format (e.g., a DataFrame). Use the `stackplot()` function, specifying the x-values and the y-values for each category. Customize colors and labels as needed, then display the chart with `plt.show()`.

5. What are the problems with stacked area charts?

Stacked area charts can be difficult to interpret, especially when there are many series, as it can be hard to distinguish between individual components. The overall area can obscure trends in the individual series, and changes in one series can be misleading due to the cumulative effect. Additionally, they can misrepresent data if the baseline is not consistent.