python
import numpy as np
arr = np.array([1, 2, 3, 4, 5])
print(arr)
print(arr.ndim)
print(arr.size)
print(arr.shape)
arr_transposed = np.transpose(arr)
print(arr_transposed)
python
import pandas as pd
data = {'Name': ['Tom', 'Nick', 'John', 'Mike'],
'Age': [25, 30, 18, 40],
'Gender': ['Male', 'Male', 'Female', 'Male']}
df = pd.DataFrame(data)
print(df)
summary = df.describe()
print(summary)
head = df.head(2)
print(head)
age_column = df['Age']
print(age_column)
python
from sklearn.datasets import load_iris
from sklearn.model_selection import train_test_split
from sklearn.neighbors import KNeighborsClassifier
iris = load_iris()
X_train, X_test, y_train, y_test = train_test_split(iris.data, iris.target, test_size=0.2, random_state=42)
knn = KNeighborsClassifier(n_neighbors=3)
knn.fit(X_train, y_train)
y_pred = knn.predict(X_test)
