updates based on code review

Author: michaelgrund

examples/gallery/3d_plots/scatter3d.py

@@ -17,13 +17,8 @@
 import pandas as pd
 import pygmt
 
-# Load sample iris data
+# Load sample iris data and convert 'species' column to categorical dtype
 df = pd.read_csv("https://github.com/mwaskom/seaborn-data/raw/master/iris.csv")
-
-# Extract species names for colorbar legend
-species = ",".join(df.species.unique())
-
-# Convert 'species' column to categorical dtype
 df.species = df.species.astype(dtype="category")
 
 # Use pygmt.info to get region bounds (xmin, xmax, ymin, ymax, zmin, zmax)
@@ -41,9 +36,11 @@
 
 # Define a colormap to be used for three categories, define the range of the
 # new discrete CPT using series=(lowest_value, highest_value, interval),
-# use color_model="+c" + species to write the discrete color palette "cubhelix" in
-# categorical format and add the species names extracted above as annotations
-pygmt.makecpt(cmap="cubhelix", color_model="+c" + species, series=(0, 2, 1))
+# use color_model="+csetosa,versicolor,virginica" to write the discrete color palette
+# "cubhelix" in categorical format and add the species names as annotations
+pygmt.makecpt(
+    cmap="cubhelix", color_model="+csetosa,versicolor,virginica", series=(0, 2, 1)
+)
 
 fig.plot3d(
     # Use petal width, sepal length and petal length as x, y and z data input,
@@ -75,6 +72,6 @@
 )
 
 # Add colorbar legend
-fig.colorbar()
+fig.colorbar(xshift=3.1)
 
 fig.show()