text_plain_output_1.png
import numpy as np

import pandas as pd

train_csv = pd.read_csv('../input/recursion-cellular-image-classification/train.csv')
test_csv = pd.read_csv('../input/recursion-cellular-image-classification/test.csv')
sub = pd.read_csv('../input/recursion-cellular-keras-densenet/submission.csv')

np.stack([train_csv.plate.values[train_csv.sirna == i] for i in range(10)]).transpose()

plate_groups = np.zeros((1108, 4), int)
for sirna in range(1108):
    grp = train_csv.loc[train_csv.sirna == sirna, :].plate.value_counts().index.values
    assert len(grp) == 3
    plate_groups[sirna, 0:3] = grp
    plate_groups[sirna, 3] = 10 - grp.sum()
plate_groups[:10, :]