[FIXED] Map the first five observations of the Iris dataset from numbers to strings

Issue

As an introduction to machine learning I have to find the first five names corresponding to the flowers of the Iris dataset from the scikit-learn library.

I'm not quite sure how to approach this, as I'm completely new in the field. I was told I can do some numpy indexing to retrieve these.

I know that the integers in iris.target correspond to 0 = 'setosa', 1 = 'versicolor', 2 = 'virginica'.

EDIT: To clarify, what I actually want to achieve is to map the integers to names for the first 5 flowers from iris.data (assign setosa, veriscolor or virginica to each of the first five observations).

Solution

Do you want to convert the numbers to their corresponding categories? If so, try:

# Load first five flowers and store them in `y`
y = load_iris()['target'][:5]

# Declare dictionary to map each number to its corresponding text
dictionary = {0:'setosa',1:'versicolor',2:'virginica'}

# Translate each number to text using the dictionary
[dictionary[i] for i in y]

You can do the same with numpy.where:

# Import numpy
import numpy as np

# Case-like structure
np.where(y == 0, 'setosa',
         np.where(y == 1, 'versicolor',
                  'virginica'))

Answered By - Arturo Sbr