jupyter notebook - matplotlib scatter plot add legend without loop and without using seaborn

Question

I receive the error No handles with labels found to put in legend. when running the code below. How can I add a legend to this scatter plot that shows the color definitions (a red dot for A, blue dot for B, green dot for C)?

### Dummy Dataset
x = [0,1,-1,4,0,2,2,4,2]
y = [1,5,9,2,4,2,5,6,1]
cat = ['A','B','B','B','A','C','A','B','B']
df = pd.DataFrame(list(zip(x,y,cat)), columns =['x', 'y', 'cat'])

### Build color definitions
df.loc[:, 'color'] = df.cat
df.color.replace(['A', 'B', 'C'], ['red', 'blue', 'green'], inplace=True)
display(df)

### Plotting
fig = plt.figure(figsize=(5,5), constrained_layout=True)
gs = fig.add_gridspec(2, 1)
ax1 = fig.add_subplot(gs[0, 0])
ax1.scatter(df.x, df.y, edgecolors = 'none', c = df.color)
ax1.legend(loc='upper left', facecolor='white', frameon=1, 
           framealpha=1, labelspacing=0.2, borderpad=0.25)

question from:https://stackoverflow.com/questions/65874934/matplotlib-scatter-plot-add-legend-without-loop-and-without-using-seaborn

Answer 1

It seems like there might not be a way to do this without a simple loop. Based on the procedure here, the following code works.

x = [0,1,-1,4,0,2,2,4,2]
y = [1,5,9,2,4,2,5,6,1]
cat = ['A','B','B','B','A','C','A','B','B']
df = pd.DataFrame(list(zip(x,y,cat)), columns =['x', 'y', 'cat'])

mycolorsdict = {'A':'red', 'B':'blue', 'C':'green'}

fig = plt.figure(figsize=(5,5), constrained_layout=True)
gs = fig.add_gridspec(2, 1)
ax1 = fig.add_subplot(gs[0, 0])
grouped = df.groupby('cat')
for key, group in grouped:
    group.plot(ax=ax1, kind='scatter', 
               x='x', y='y', 
               label=key, color=mycolorsdict[key])
ax1.legend(loc='upper left', facecolor='white', frameon=1, 
           framealpha=1, labelspacing=0.2, borderpad=0.25)