This code worked for me using Python 3.5.2:

import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline

from sklearn import datasets

iris_dataset = datasets.load_iris()
X = iris_dataset.data
Y = iris_dataset.target

iris_dataframe = pd.DataFrame(X, columns=iris_dataset.feature_names)

# Create a scatter matrix from the dataframe, color by y_train
grr = pd.plotting.scatter_matrix(iris_dataframe, c=Y, figsize=(15, 15), marker='o',
                                 hist_kwds={'bins': 20}, s=60, alpha=.8)

For pandas version < v0.20.0.

Thanks to michael-szczepaniak for pointing out that this API had been deprecated.

grr = pd.scatter_matrix(iris_dataframe, c=Y, figsize=(15, 15), marker='o',
                        hist_kwds={'bins': 20}, s=60, alpha=.8)

I just had to remove the cmap=mglearn.cm3 piece, because I was not able to make mglearn work. There is a version mismatch issue with sklearn.

To not display the image and save it directly to file you can use this method:

plt.savefig('foo.png')

Also remove

# %matplotlib inline

Just an update to Vikash's excellent answer. The last two lines should now be:

grr = pd.plotting.scatter_matrix(iris_dataframe, c=Y, figsize=(15, 15), marker='o',
                                 hist_kwds={'bins': 20}, s=60, alpha=.8)

The scatter_matrix function has been moved to the plotting package, so the original answer, while correct is now deprecated.

So the complete code would now be:

import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline

from sklearn import datasets

iris_dataset = datasets.load_iris()
X = iris_dataset.data
Y = iris_dataset.target

iris_dataframe = pd.DataFrame(X, columns=iris_dataset.feature_names)
# create a scatter matrix from the dataframe, color by y_train
grr = pd.plotting.scatter_matrix(iris_dataframe, c=Y, figsize=(15, 15), marker='o',
                                 hist_kwds={'bins': 20}, s=60, alpha=.8)

This is also possible using seaborn:

import seaborn as sns

df = sns.load_dataset("iris")
sns.pairplot(df, hue="species")