Generating class name list based on class index list

Question

I'm playing with iris_dataset from sklearn.datasets I want to generate list similiar to iris_dataset['target'] but to have name of class instead of index. The way I did it:

from sklearn.datasets import load_iris
iris_dataset=load_iris()
y=iris_dataset.target
print("Iris target: \n {}".format(iris_dataset.target))
unique_y = np.unique(y)
class_seq=['']
class_seq=class_seq*y.shape[0]

for i in range(y.shape[0]):
    for (yy,tn) in zip(unique_y,iris_dataset.target_names):
        if y[i]==yy:
            class_seq[i]=tn          

print("Class sequence: \n {}".format(class_seq))

but I would like to do it not looping through all of the elements of y, how to do it better way?

The outcome is that I need this list for pandas.radviz plot to have a proper legend:

pd.plotting.radviz(iris_DataFrame,'class_seq',color=['blue','red','green'])

And further to have it for any other dataset.

Actually it's probably better to use mask as given in second answer cause it's easier to work with np.arrays not lists, my mistake in formulating a question — Kostia, Dec 10 '18 at 20:29

score 1 · Answer 1 · answered Dec 07 '18 at 13:39

You can do it by looping over iris_dataset.target_names.size. This is only size 3 so it should be alot faster for large y arrays.

class_seq = np.empty(y.shape, dtype=iris_dataset.target_names.dtype)

for i in range(iris_dataset.target_names.size):
    mask = y == i
    class_seq[mask] = iris_dataset.target_names[i]

If you want to have class_seq as a list: class_seq = list(class_seq)

score 0 · Accepted Answer · answered Dec 07 '18 at 13:42

0

Yo can do it by list comprehension.

class_seq = [ iris_dataset.target_names[i] for i in iris_dataset.target]

or by using map

class_seq = list(map(lambda x : iris_dataset.target_names[x], iris_dataset.target))

answered Dec 07 '18 at 13:42

Sach

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Generating class name list based on class index list

2 Answers2