( Originally appeared on the Ather Blog )
We just added Marimekko charts to the ggTimeSeries library.
What are Marimekko charts? Also know as mosaic plots, they help visualise the co-occurrence of two categorical or ordinal variables and compare the occurrence of that pair to other pairs.
Remember the plot showing the proportions of accelerations from our last blog post?
Here is the same data visualised as a Marimekko plot. The X axis plots the overall occurrence of the starting buckets. The Y axis plots the distribution of the next bucket given the current bucket is the label on the X axis. For instance, the plot for Julian’s decelerations, indicates that about 50% of the decelerations start from the mid bucket, because the column labelled mid occupies about 50% of the space on the X axis. and out of these decelerations, almost 60% end in the mid bucket itself while the remaining 40% end in the low bucket.
Similarly, George’s affinity for high speeds clearly shows up here. The high amount of blue you see in the acceleration plots indicates the proportion of times he accelerates to the high speed bucket. The high amount of blue in the deceleration plot similarly indicates that a large share of George’s decelerations are small ones which let him stay within the high speed bucket. Compare this to Timmy’s plot, which has large swathes of green instead.
We just added Marimekko charts to the ggTimeSeries library.
What are Marimekko charts? Also know as mosaic plots, they help visualise the co-occurrence of two categorical or ordinal variables and compare the occurrence of that pair to other pairs.
Remember the plot showing the proportions of accelerations from our last blog post?
Here is the same data visualised as a Marimekko plot. The X axis plots the overall occurrence of the starting buckets. The Y axis plots the distribution of the next bucket given the current bucket is the label on the X axis. For instance, the plot for Julian’s decelerations, indicates that about 50% of the decelerations start from the mid bucket, because the column labelled mid occupies about 50% of the space on the X axis. and out of these decelerations, almost 60% end in the mid bucket itself while the remaining 40% end in the low bucket.
Similarly, George’s affinity for high speeds clearly shows up here. The high amount of blue you see in the acceleration plots indicates the proportion of times he accelerates to the high speed bucket. The high amount of blue in the deceleration plot similarly indicates that a large share of George’s decelerations are small ones which let him stay within the high speed bucket. Compare this to Timmy’s plot, which has large swathes of green instead.
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