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# [Python/Data Analysis] Numpy 및 Matplotlib 사용하기 - Day 5 import numpy as np import matplotlib.pyplot as plt # 1 - Pyplot example x = np.arange(0,6,0.1) y = np.sin(x) plt.plot(x,y) plt.show() # 2 - Pyplot example a = np.arange(0, 6, 0.1) b1 = np.sin(a) b2 = np.cos(a) plt.plot(a, b1, label="sin") plt.plot(a, b2, linestyle="--", label="cos") # a axis name plt.xlabel("a") plt.ylabel("b") plt.title("..

# [Python/Data Analysis] Numpy 및 Matplotlib 사용하기 - Day 3import numpy as np arr = np.arange(0,11) arr2 = np.arange(0,11) arr array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10])arr[8] 8# Slice arr[1:5] array([1, 2, 3, 4]) arr[0:5] array([0, 1, 2, 3, 4]) arr[0:5] = 100 arr array([100, 100, 100, 100, 100, 5, 6, 7, 8, 9, 10])arr2[3:7] = 100 arr2 array([ 0, 1, 2, 100, 100, 100, 100, 7, 8, 9, 10])arr = np.arang..

# [Python/Data Analysis] Numpy 및 Matplotlib 사용하기 - Day 2 import numpy as np from __future__ import division 5/2 2.5 arr1 = np.array([[1,2,3,4], [8,9,10,11]]) arr1 array([[ 1, 2, 3, 4], [ 8, 9, 10, 11]]) arr1 * arr1 array([[ 1, 4, 9, 16], [ 64, 81, 100, 121]]) arr1 - arr1 array([[0, 0, 0, 0], [0, 0, 0, 0]]) 1 / arr1 array([[ 1. , 0.5 , 0.33333333, 0.25 ], [ 0.125 , 0.11111111, 0.1 , 0.09090909]])..