gistfile1.py

from sklearn.decomposition.pca import PCA

pca = PCA(n_components=2)

# Note, data.shape = (6, 26440)
pca.fit(data)

Yd = dict()
Yd["400"] = pca.transform(data.ix[:,"400"])
Yd["5000"] = pca.transform(data.ix[:,"5000"])

plt.scatter(*zip(*Yd["400"]), c='#348ABD', s=100, label="400");
plt.scatter(*zip(*Yd["500"]), c='#A60628', s=100, label="5000");
plt.legend();
plt.title("Score plot");
plt.xlabel("PC1");
plt.ylabel("PC2");
plt.grid();

Please validate it with example output.