Unnormalized y-axis when using KDE

When I do

sns.distplot(my_data, rug=True, norm_hist=False)

I get:

and when I do:

sns.distplot(my_data, rug=True, norm_hist=False)

I get:

Is there any way to have the Y-axis show raw counts (as in the 1st example above), when adding a kde plot? (2nd example above)?

[mbernste]

It would be more informative than decorative. KDE and histogram summarize the data in slightly different ways. In general, when plotting a KDE, I don’t really care about what the actual values of the density function are at each point in the domain. Rather, I care about the shape of the curve. This contrasts with the histogram in which the values of each bar are something much more interpretable (number of samples in each bin).

Thus, it would be great to set the normalization of the KDE so that the density function integrates to a custom value thereby allowing the curve to be overlaid on the histogram.

[dmitriibeliakov]

Here’s my solution:

# Plotting hist without kde
ax = sns.distplot(filtered_bookings.booking_window, kde=False)

# Creating another Y axis
second_ax = ax.twinx()

#Plotting kde without hist on the second Y axis
sns.distplot(filtered_bookings.booking_window, ax=second_ax, kde=True, hist=False)

#Removing Y ticks from the second axis
second_ax.set_yticks([])

Hope this helps.