Downloading and understanding the famous Iris data for unsupervised classification

In this recipe, we download and inspect the well-known Iris dataset in preparation for the upcoming streaming KMeans recipe, which lets you see classification/clustering in real-time.

The data is housed on the UCI machine learning repository, which is a great source of data to prototype algorithms on. You will notice that R bloggers tend to love this dataset.

How to do it...

1. You can start by downloading the dataset using either two of the following commands:

wget https://archive.ics.uci.edu/ml/machine-learning-databases/iris/iris.data

You can also use the following command:

curl https://archive.ics.uci.edu/ml/machine-learning-databases/iris/iris.data -o iris.data

You can also use the following command:

https://archive.ics.uci.edu/ml/machine-learning-databases/iris/iris.data

2. Now we begin our first step of data exploration by examining how the data in iris.data is formatted:

head -5 iris.data
5.1,3.5,1.4,0.2,Iris-setosa...