Here's a picture of the plot I get for a bivariate density. However the numbers next to the colorbar are really not of much use here, and I would like either to delete them or replace by 'LOW' and 'HIGH'. I didn't find any way of doing this so if any of you has info, it would be great. Here's the code i used for creation of this plot :
df = self.dfuinsights
ax = sns.kdeplot(data = df, x = key1, y = key2, fill = True, alpha = 0.7, tresh = tsh, levels = lvls, cmap = "viridis")
xlabel = self.colnamesMapper_uinsights[key1]
ylabel = self.colnamesMapper_uinsights[key2]
title = "Bivariate Densities : " + xlabel + " - " + ylabel
self.__convert_capitals(ax, title, xlabel, ylabel) #just modifying titles and xlabel, ignore this)
plt.show()
plt.close()
kdeplot
can take arguments to be passed to the colorbar in cbar_kws=
. To remove the ticks+labels, you can request an empty list of ticks:
geyser = sns.load_dataset("geyser")
sns.kdeplot(
data=geyser, x="waiting", y="duration",
fill=True, thresh=0, levels=100, cmap="viridis",
cbar=True, cbar_kws=dict(ticks=[])
)
Alternatively, if you capture the return value from kdeplot()
, you should be able to get a reference to the colorbar axes, and then you can use any of the functions provided by Axes
to modify ticks and ticklabels
ax = sns.kdeplot(
data=geyser, x="waiting", y="duration",
fill=True, thresh=0, levels=100, cmap="viridis",
cbar=True
)
cax = ax.figure.axes[-1] # This assume there are no other axes in the figure
cax.set_yticklabels([])