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# [Python/Data Analysis] Numpay - Universal Array Function - Day 7import numpy as np arr =np.arange(11)arr array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]) np.sqrt(arr) array([ 0. , 1. , 1.41421356, 1.73205081, 2. , 2.23606798, 2.44948974, 2.64575131, 2.82842712, 3. , 3.16227766]) A = np.random.randn(10)A array([-0.66405485, 0.28749254, 0.27305696, 0.22232217, 0.8804781 , 1.01018702, -0.15188718, -0.7..

# [Python/Data Analysis] Numpay - Array Tranposition 사용하기 - Day 6import numpy as np arr = np.arange(50).reshape((10,5)) arr array([[ 0, 1, 2, 3, 4], [ 5, 6, 7, 8, 9], [10, 11, 12, 13, 14], [15, 16, 17, 18, 19], [20, 21, 22, 23, 24], [25, 26, 27, 28, 29], [30, 31, 32, 33, 34], [35, 36, 37, 38, 39], [40, 41, 42, 43, 44], [45, 46, 47, 48, 49]]) arr.T array([[ 0, 5, 10, 15, 20, 25, 30, 35, 40, 45], ..