co_matrix.py

# Co-occurence Matrix
com = np.zeros([len(counts)]*2)
for i, l in enumerate(list(counts.keys())):
    for i2, l2 in enumerate(list(counts.keys())):
        c = 0
        cy = 0
        for row in labels.values:
            if l in row:
                c += 1
                if l2 in row: cy += 1
        com[i, i2] = cy / c

data=[go.Heatmap(z=com, x=list(counts.keys()), y=list(counts.keys()))]
layout=go.Layout(height=800, width=800, title='Co-occurence matrix of training labels')
fig=dict(data=data, layout=layout)
py.iplot(data, filename='train-com')