From this dataframe that represent the position of a fish according to different months:
X Y Month
2040 2760 1
2041 2580 1
2045 2762 1
2047 2763 2
2053 2774 3
and through this seaborn script:
fig,ax=plt.subplots()
kde = sns.kdeplot(data=HR25, x='X', y='Y', shade=True, ax=ax, levels=levels_, cmap="Reds",
alpha=0.9)
ax.set_xlim([x_min-10, x_max+10])
ax.set_ylim([y_min-10, y_max+10])
ax.scatter(X, Y, c=months, edgecolors='black', picker=True, s=17)
ax.set_aspect('equal')
plt.show()
i have been able to create this figure which represent the positions of a fish over one year according to months (the red area in the background is the home range of the animal calculated with kernel seaborn method):
Actually, I would like to change the colours of the points related to the months, so I create a distinct palette specifing colours for each month:
palette = {1:"tab:blue", 2:"tab:orange", 3:"tab:purple", 4:"tab:green", 5:"tab:red", 6:"tab:pink", 7:"tab:brown", 8:"tab:yellow", 9:"tab:olive", 10:"tab:black", 11:"tab:cyan", 12:"tab:gray"}
However, when i add the palette to ax.scatter like this:
fig,ax=plt.subplots()
kde = sns.kdeplot(data=HR25, x='X', y='Y', shade=True, ax=ax, levels=levels_, cmap="Reds",
alpha=0.9)
ax.set_xlim([x_min-10, x_max+10])
ax.set_ylim([y_min-10, y_max+10])
ax.scatter(X, Y, c=months, edgecolors='black', picker=True, s=17, palette=palette)
ax.set_aspect('equal')
plt.show()
all points disappear!
In your case, when you call ax.scatter
you're not actually using the Seaborn scatterplot
function. Instead, you're using the Matplotlib scatter
function, which does not have a palette
or picker
keyword argument. Rather than:
ax.scatter(X, Y, c=months, edgecolors='black', picker=True, s=17, palette=palette)
try:
sns.scatterplot(X, Y, c=months, edgecolors='black', picker=True, s=17, palette=palette, ax=ax)
Note: tab:yellow
and tab:black
are not in Matplotlib's tableau palette, so you should remove the tab:
in the strings for those values.
If you did want to use Matplotlib's scatter
, you could set the colours by setting 'axes.prop_cycle'
in the rcParams, e.g.,:
import matplotlib as mpl
from cycler import cycler
mpl.rcParams['axes.prop_cycle'] = cycler(
color=list(palette.values())
)