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print('hello, world')
from collections import Counterdef find_parity_outliers(nums):return [x for x in numsif x % 2 != Counter([n % 2 for n in nums]).most_common()[0][0]]find_parity_outliers([1, 2, 3, 4, 6]) # [1, 3]
from statistics import median, mean, modedef print_stats(array):print(array)print("median =", median(array))print("mean =", mean(array))print("mode =", mode(array))print()print_stats([1, 2, 3, 3, 4])print_stats([1, 2, 3, 3])
def print_x_pattern(size):i,j = 0,size - 1while j >= 0 and i < size:initial_spaces = ' '*min(i,j)middle_spaces = ' '*(abs(i - j) - 1)final_spaces = ' '*(size - 1 - max(i,j))if j == i:print(initial_spaces + '*' + final_spaces)else:print(initial_spaces + '*' + middle_spaces + '*' + final_spaces)i += 1j -= 1print_x_pattern(7)
# Function to multiply two matricesdef multiply_matrices(matrix1, matrix2):# Check if the matrices can be multipliedif len(matrix1[0]) != len(matrix2):print("Error: The number of columns in the first matrix must be equal to the number of rows in the second matrix.")return None# Create the result matrix filled with zerosresult = [[0 for _ in range(len(matrix2[0]))] for _ in range(len(matrix1))]# Perform matrix multiplicationfor i in range(len(matrix1)):for j in range(len(matrix2[0])):for k in range(len(matrix2)):result[i][j] += matrix1[i][k] * matrix2[k][j]return result# Example matricesmatrix1 = [[1, 2, 3],[4, 5, 6],[7, 8, 9]]matrix2 = [[10, 11],[12, 13],[14, 15]]# Multiply the matricesresult_matrix = multiply_matrices(matrix1, matrix2)# Display the resultif result_matrix is not None:print("Result:")for row in result_matrix:print(row)
def clamp_number(num, a, b):return max(min(num, max(a, b)), min(a, b))clamp_number(2, 3, 5) # 3clamp_number(1, -1, -5) # -1