Greetings everyone.

It is about the code in the link below.

https://app.dataquest.io/m/152/conditional-plots/9/adding-a-legend

Could somebody please tell me what those Y-axis values stand for?

Greetings everyone.

It is about the code in the link below.

https://app.dataquest.io/m/152/conditional-plots/9/adding-a-legend

Could somebody please tell me what those Y-axis values stand for?

The **vertical or y-axis** of a KDE plot represents the **Kernel Density Estimate** of the **Probability Density Function** of a random variable.

AND

The **horizontal or x-axis** of a KDE plot is the range of values in the data set.

hello,

…I was wonder about it too. This answer is great, but It doesn’t mean much without information: what we can do about it. I mean: how to read it?

Suppose that we have survivals that have **x:20** years and **y: 0,035**. What does it mean? is it 3,5 % of chances that 20 years old survive? or is it 3,5 % of total people that survive? something else? I don’t understand that at all

Another thing is: what’s the reason that the same data for kernel density plot and the histogram shows totally different hight of Y-axis. We can see it on example in this exercise when we place this code:

```
# Condition on unique values of the "Survived" column.
g = sns.FacetGrid(titanic, col="Pclass", size=6)
# For each subset of values, generate a kernel density plot of the "Age" columns.
g.map(sns.kdeplot, "Age", shade=True)
sns.despine(bottom=True, left=True)
g = sns.FacetGrid(titanic, col="Pclass", size=6)
g.map(plt.hist, "Age")
```

output is:

As we can see: the first and third column seems to look similar on both plots types, but the second column is totally different when we compare the hight of histogram and kernel density plot.