# Is there a specific name for this plot?

This plot represents the popularity of technologies in two "tools", vue and react. In left-top corner are specific technologies for vue but not for react, right-top technologies popular in both tools - you get the idea.

For example vue-loader (left-top) is in 51% of projects with vue but only in 0.08% projects with react.

Is there any specific name for this kind of data representation?

EDIT

This plot is quite similar to Correspondence Analysis but axis are made of two variables from my data:

            technology          vue        react

acorn 0.0006145023 0.0003786922
animate.css 0.0143383859 0.0191870740
apache-server-configs 0.0006145023 0.0001262307
archiver 0.0012290045 0.0005049230
assert 0.0020483408 0.0012623075


EDIT 2

This kind of plot can be explained by converting

slope plot

to scatter plot

Since I will not find any ready to use guides how to read this kind of plot I made my own explanation:

• What specific features, in your view, distinguish this scatter plot from other scatter plots? – Ruben van Bergen Feb 22 '18 at 11:32
• @RubenvanBergen Squared size, characteristic diagonal (identity function), this idea about corners I was trying to describe. Fact that data on either side of diagonal is more specific to one of vue or react in my example. – Everettss Feb 22 '18 at 11:38
• @RubenvanBergen And each point is not from on paired observation - this can suggest that this is not a scatter plot? stats.stackexchange.com/a/187773/196312 – Everettss Feb 22 '18 at 13:07
• I would say these are paired observations, because each dot represents two measurements for the same technology: its popularity in vue and its popularity in react. Unless I've misunderstood something? – Ruben van Bergen Feb 22 '18 at 14:40
• These are paired in that each dot represents two values for the same technology, as @RubenvanBergen notes. Those 2 pieces of information are estimated separately, & in this case you can say something about their uncertainty, whereas in a more typical case (w/ 1 measure on each) you couldn't. If you wanted, you could put little horizontal & vertical error bars around the observed %ages based on the possibly differing $M$'s. You may not want to, b/c that would make the plot even busier, but you could. At any rate, these data are paired. – gung - Reinstate Monica Feb 23 '18 at 21:23

Second, there is a subtle distinction in statistics between correlation and agreement (cf., Does Spearman's $r=0.38$ indicate agreement?). Most commonly people look at scatterplots from a correlation-ish frame of mind; your scatterplot seems to connote an agreement-ish perspective. For example, your two variables are naturally on the same scale and you have a prominent diagonal line marking perfect agreement. Your "slope plot", which you think of as analogous, is also presenting a kind of agreement-ish information (i.e., the stability of the rankings over time, coupled with the consistency of the increase).