This is my goal: Plot the frequency of `y`

according to `x`

in the `z`

axis.

These are my problems: I have a two columns array (`x`

and `y`

) and need to divide `x`

into classes (p.ex. 0.2 ou 0.5) and calculate the frequency of `y`

for each class of `x`

. The plot should appear like a `x-y`

plot in the "ground" plan and the frequency in the `z`

axis. It could be like a surface or a 3D histogram. I tried to make it using the `hist3D`

function of `plot3D`

package but I don't know what I am doing wrong.

This is an example of what I am trying to do:

https://www.safaribooksonline.com/library/view/r-data-visualization/9781783989508/ch06s05.html

Thanks!!

Answer:

Using some simulated data this should get you what you want. The key is that you have to create your bivariate bins, accomplished using the `cuts()`

function. Then treating the binned factors as levels we can then count the combinations of each factor level using the `table()`

function:

```
library(plot3D)
## Simulate data:
set.seed(2002)
x <- rnorm(1000)
y <- rnorm(1000)
## Create cuts:
x_c <- cut(x, 20)
y_c <- cut(y, 20)
## Calculate joint counts at cut levels:
z <- table(x_c, y_c)
## Plot as a 3D histogram:
hist3D(z=z, border="black")
## Plot as a 2D heatmap:
image2D(z=z, border="black")
```

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