How to annotated labels to a 3D matplotlib scatter plot? - python-3.x

Question

I have run a sklearn - Principal Component Analysis on my data with 3 principal components (PC1, PC2, PC3). The data looks like this (it's a pandas DataFrame):
Here is the code for plotting the principle components:
from mpl_toolkits.mplot3d import axes3d
import matplotlib.pyplot as plt
%matplotlib
fig = plt.figure()
ax = fig.gca(projection='3d')
ax.set_title('3D Scatter Plot')
ax.set_xlabel('PC1')
ax.set_ylabel('PC2')
ax.set_zlabel('PC3')
ax.view_init(elev=12, azim=40) # elevation and angle
ax.dist=10 # distance
ax.scatter(
data_df_3dx['PC1'], data_df_3dx['PC2'], data_df_3dx['PC3'], # data
#color='purple', # marker colour
#marker='o', # marker shape
s=60 # marker size
)
plt.show()
My problem, how do I add labels (like 'GER, medium') to the points? Hope someone can help me :)

Answer 1

In the following posts [1], [2] the plotting of 3D arrows in matplotlib is discussed.
Similarly Annotation3D class (inherited from Annotation) can be created:
from mpl_toolkits.mplot3d.proj3d import proj_transform
from matplotlib.text import Annotation
class Annotation3D(Annotation):
'''Annotate the point xyz with text s'''
def __init__(self, s, xyz, *args, **kwargs):
Annotation.__init__(self,s, xy=(0,0), *args, **kwargs)
self._verts3d = xyz
def draw(self, renderer):
xs3d, ys3d, zs3d = self._verts3d
xs, ys, zs = proj_transform(xs3d, ys3d, zs3d, renderer.M)
self.xy=(xs,ys)
Annotation.draw(self, renderer)
Further, we can define the annotate3D() function:
def annotate3D(ax, s, *args, **kwargs):
'''add anotation text s to to Axes3d ax'''
tag = Annotation3D(s, *args, **kwargs)
ax.add_artist(tag)
Using this function annotation tags can be added to Axes3d as in example bellow:
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import axes3d
from mpl_toolkits.mplot3d.art3d import Line3DCollection
# data: coordinates of nodes and links
xn = [1.1, 1.9, 0.1, 0.3, 1.6, 0.8, 2.3, 1.2, 1.7, 1.0, -0.7, 0.1, 0.1, -0.9, 0.1, -0.1, 2.1, 2.7, 2.6, 2.0]
yn = [-1.2, -2.0, -1.2, -0.7, -0.4, -2.2, -1.0, -1.3, -1.5, -2.1, -0.7, -0.3, 0.7, -0.0, -0.3, 0.7, 0.7, 0.3, 0.8, 1.2]
zn = [-1.6, -1.5, -1.3, -2.0, -2.4, -2.1, -1.8, -2.8, -0.5, -0.8, -0.4, -1.1, -1.8, -1.5, 0.1, -0.6, 0.2, -0.1, -0.8, -0.4]
group = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 3, 2, 2, 2, 3, 3, 3, 3]
edges = [(1, 0), (2, 0), (3, 0), (3, 2), (4, 0), (5, 0), (6, 0), (7, 0), (8, 0), (9, 0), (11, 10), (11, 3), (11, 2), (11, 0), (12, 11), (13, 11), (14, 11), (15, 11), (17, 16), (18, 16), (18, 17), (19, 16), (19, 17), (19, 18)]
xyzn = zip(xn, yn, zn)
segments = [(xyzn[s], xyzn[t]) for s, t in edges]
# create figure
fig = plt.figure(dpi=60)
ax = fig.gca(projection='3d')
ax.set_axis_off()
# plot vertices
ax.scatter(xn,yn,zn, marker='o', c = group, s = 64)
# plot edges
edge_col = Line3DCollection(segments, lw=0.2)
ax.add_collection3d(edge_col)
# add vertices annotation.
for j, xyz_ in enumerate(xyzn):
annotate3D(ax, s=str(j), xyz=xyz_, fontsize=10, xytext=(-3,3),
textcoords='offset points', ha='right',va='bottom')
plt.show()

Answer 2

One way would be to plot each point individually inside of a for loop, that way you know the coordinates of each point and can add text to it.
for i in range(len(data_df_3dx)):
x, y, z = data_df_3dx.iloc[i]['PC1'], data_df_3dx.iloc[i]['PC2'], data_df_3dx.iloc[i]['PC3']
ax.scatter(x, y, z)
#now that you have the coordinates you can apply whatever text you need. I'm
#assuming you want the index, but you could also pass a column name if needed
ax.text(x, y, z, '{0}'.format(data_df_3dx.index[i]), size=5)