I'm running through a tutorial to understand the histogram plotting. Given the seaborn tips dataset, by running the sns.distplot(tips.tip);
function the following plot is rendered.
Looking at the plot, I don't understand the sense of the KDE (or density curve). The middle column (the one with the lower value) between 2 and 4 doesn't seem to support the shape of the curve.
I have to say that I have little if no understanding on the principle used to plot it, so I would love to hear from somebody more experienced on
- What's the added value of the KDE?
- What's the process behind the calculation
Also, why using the same dataset with the standard matplotlib I get a slightly different representation (in which the density line above probably fit better)?
bins=10
whereas seaborn seems to use the Freedman-Diaconis rule to determine the number of bins. $\endgroup$ – Oxbowerce Jan 15 '20 at 19:52