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import numpy as np

import numpy as np # linear algebra

import os

import os

import pandas as pd

import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)

import numpy as np
import pandas as pd
import pandas as pd
import os
import numpy as np
from sklearn.neighbors import KNeighborsClassifier
from sklearn.model_selection import GridSearchCV
import os
data = pd.read_csv('/kaggle/input/otto-group-product-classification-challenge/train.csv')
data.sample(10)

X = np.asarray(data.iloc[:, 1:-1].dropna(), dtype=np.float32)
Y = np.asarray(data.iloc[:, -1])

np.sum(data.iloc[:, 1:94] > 40)

data.isnull().sum()