I have a bubble chart with the legend showing two categories differentiated by color and size, the markers on the scatter have black edge color and I like the markers shown in the legend to have it too, anyone know how can I do it?
I'm using seaborn scatterplot to generate the graph
Summary = pd.read_csv("Summary.csv")
####################################################################################
# Plot the scatterplot
####################################################################################
f, (ax1, ax2) = plt.subplots(ncols=2, nrows=1, sharey=True, figsize=(8.27,5.8))
#----------------------------------------------------------------------------------------
# add a big axes, hide frame, common axis labels
#----------------------------------------------------------------------------------------
f.add_subplot(111, frameon=False)
# hide tick and tick label of the big axes
plt.tick_params(labelcolor='none', top=False, bottom=False, left=False, right=False)
plt.grid(False)
plt.xlabel('T$_{s}$ - T$_{sat}$ [$^{\circ}$C]', fontsize=14)
plt.ylabel('Heat Flux [W$\cdot$cm$^{-2}$]', fontsize=14)
#----------------------------------------------------------------------------------------
# Change the minimum and maximum point size
ax=sns.scatterplot(x='T_surf - T_sat [C]', y='Heat Flux [W/cm2]', data=Summary, # Choose the x and y values and the dataframe
size='Mass flux [kg$\cdot$m$^{-2}$$\cdot$s$^{-1}$]', # Size of markers
hue='Enhanced Surface', # Color by surface type
#color='Greys',
alpha=1.0,
#style='Enhanced Surface', # Marker by surface type
sizes=(20, 700), # minimum and maximum marker size
palette = 'Blues',
#markers=["X","d", "*","s"], # Change the markers' style
markers='o',
edgecolor= "Black", # Change the edge color of the markers
linewidth=0.5, # Change the edge linewidth of the markers
legend=False,
ax=ax1
)
ax=sns.scatterplot(x='T_surf - T_sat [C]', y='Heat Flux [W/cm2]', data=Summary, # Choose the x and y values and the dataframe
size='Mass flux [kg$\cdot$m$^{-2}$$\cdot$s$^{-1}$]', # Size of markers by population
hue='Enhanced Surface', # Color by surface type
#cmap='Greys',
alpha=1.0,
#style='Enhanced Surface', # Marker by surface type
sizes=(20, 700), # minimum and maximum marker size
palette = 'Blues',
#markers=["X","d", "*","s"], # Change the markers' style
markers='o',
edgecolor= "Black", # Change the edge color of the markers
linewidth=0.5, # Change the edge linewidth of the markers
legend='auto',
ax=ax2
)
ax1.set_xlim(-60, 120)
ax2.set_xlim(790, 810)
# labels = ax1.get_legend_handles_labels()
####################################################################################
# Use the matplotlib library to edit the plot
####################################################################################
#Legend
lgd = ax2.legend(loc="upper right", frameon = 0.5, framealpha=0.8, # Create a legend and define its location, frame and frame alpha
edgecolor='white', facecolor='white', ncol=2, # Edgecolor, facecolor and the number of columns
title='', fontsize=10, # the title and the font size
handlelength=1, handleheight=2, columnspacing = 1.0, labelspacing=1.5,
markerscale=1.0, markerfirst = False)
You can create your plot as you would with seaborn
and then tweak the legend style directly.
Each ha
handle is a matplotlib.collections.PathCollection
, I've set the edge colour to red
here so you can see the difference.
import seaborn as sns
tips = sns.load_dataset("tips")
fig, ax = plt.subplots(figsize=(4,4))
sns.scatterplot(data=tips, x="total_bill", y="tip", style="day", ax=ax)
# Get the legend handles
handles, labels = ax.get_legend_handles_labels()
# Iterate through the handles and call `set_edgecolor` on each
for ha in handles:
ha.set_edgecolor("red")
# Use `ax.legend` to set the modified handles and labels
lgd = ax.legend(
handles,
labels,
loc="upper left",
ncol=2,
)
Which produces:
Or, as mwaskom suggested, modify the artists in place to avoid redrawing the legend:
tips = sns.load_dataset("tips")
fig, ax = plt.subplots(figsize=(4,4))
sns.scatterplot(data=tips, x="total_bill", y="tip", style="day", ax=ax)
# Place the legend
lgd = ax.legend(
loc="upper left",
ncol=2,
)
# Modify the point edge colour
for ha in ax.legend_.legendHandles:
ha.set_edgecolor("red")
which produces the same plot.