Exploratory Data Analysis
#create df from data in X_train
#label columns using str in iris_dataset.feature_names
iris_dataframe = pd.DataFrame(X_train, columns=iris_dataset.feature_names)
#create scatter matrix from df, color by y_train
grr = pd.plotting.scatter_matrix(iris_dataframe, c=y_train, figsize = (15,15),
marker = 'o', hist_kwds={'bins':20}, s=60,
alpha=0.8, cmap=mglearn.cm3)
In the above code, I can't understand 's' and 'cmap' use. I know this API has been updated, but I want to learn about the use of 's' and 'cmap=mglearn.cm3' in general use.
In plotting.scatter_matrix, 's' and 'cmap' are keyword arguments for matplotlib.pyplot.scatter.
They are optional parameters which can be used with pandas.plotting.scatter_matrix.
's' is used to specify the marker size.
'cmap' defines the colormap.
Here's a link.