使用matplotlib绘制图例：错误

Question

I am trying to add a legend to my graph in matplotlib. instead of creating a legend it puts the full list of all mylabels in the legend.

My graph looks like this:

The legend is cut off and i cant see more than that, i assume due to its size.

This is my code:

features2 = ["Number of Sides"]
features3 = ["Largest Angle"]
header2 = ["Label"]

data_df = pd.DataFrame.from_csv("AllMixedShapes2.csv")
X1 = np.array(data_df[features2].values)
y1 = np.array(data_df[features3].values)
l = np.array(data_df[header2].values)

plt.scatter(X1[:, 0],y1, c=y, cmap=plt.cm.Paired, label=l)
plt.axis([0, 17, 0, 200])
plt.ylabel("Maximum Angle (Degrees)")
plt.xlabel("Number Of Sides")
plt.title('Original 450 Test Shapes')

plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)
plt.show()

And AllMixedShapes2.csv looks like this:

I'm quite new to python and machine learning and ive tried other examples but i cant get anything to work.

Answer 1

Matplotlib's label argument is meant to be a single string that labels the entire dataset, rather than an array of individual labels for the points within the dataset. If you wish to pass an array of point-by-point labels that will be aggregated into a legend, the best option is probably the Seaborn library. Seaborn provides a wrapper around matplotlib for more convenient statistical visualization.

This should do approximately what you wish to do with your data:

import seaborn
seaborn.lmplot('Number of Sides', 'Largest Angle', hue='Label',
               data=data_df, fit_reg=False)

I'd suggest checking out the seaborn example gallery for more ideas.