bro's coding

import matplotlib.pyplot as plt img=plt.imread('제목 없음.png') plt.imshow(img.mean(axis=2),cmap='gray',vmin=0,vmax=1) plt.colorbar()

a = np.ones([4,3]) a ''' array([[1., 1., 1.], [1., 1., 1.], [1., 1., 1.], [1., 1., 1.]]) ''' a+[1,2,3] ''' [2,3,4] [2,3,4] [2,3,4] [2,3,4] ''' https://docs.scipy.org/doc/numpy/user/basics.broadcasting.html Broadcasting — NumPy v1.17 Manual Broadcasting Note See this article for illustrations of broadcasting concepts. The term broadcasting describes how numpy treats arrays with different shapes d..

a = np.arange(12).reshape(4,3) a ''' array([[ 0, 1, 2], [ 3, 4, 5], [ 6, 7, 8], [ 9, 10, 11]]) ''' 1/a ''' array([[ inf, 1. , 0.5 ], [0.33333333, 0.25 , 0.2 ], [0.16666667, 0.14285714, 0.125 ], [0.11111111, 0.1 , 0.09090909]]) '''

import numpy as np a = np.array([1,2,3,4,5]) a+1 [2,3,4,5,6] a*4 [4,8,12,16,20]

import numpy as np iris_labels = ['Iris-setosa', 'Iris-versicolor', 'Iris-virginica'] iris = np.loadtxt('iris.csv', skiprows=1, delimiter=',', converters={4: lambda s: iris_labels.index(s.decode())}) # iris = np.loadtxt('iris.csv', skiprows=1, delimiter=',', # converters={4: lambda s: labels.index(s)}, encoding='utf-8') # latin1, ascii, utf-8, cp949

plt.subplot(2,2,1) plt.title('SepalLength') plt.hist(iris[:,0],bins=30) plt.subplot(2,2,2) plt.title('SepalWidth') plt.hist(iris[:,1], bins=30) plt.subplot(2,2,3) plt.title('PetalLength') plt.hist(iris[:,2],bins=30) plt.subplot(2,2,4) plt.title('PetalWidth') plt.hist(iris[:,3],bins=30)

plt.plot(iris[:50,:4].T,'r-',alpha=0.1) plt.plot(iris[50:100,:4].T,'g-',alpha=0.1) plt.plot(iris[100:150,:4].T,'b-',alpha=0.1) pass​ plt.plot(iris) plt.legend(iris_pd.columns)

import matplotlib.pyplot as plt plt.scatter(iris[:,2],iris[:,3],c=iris[:,4],s=iris[:,1]+100,alpha=0.2) #우측에 bar표시 plt.colorbar() plt.title('SepalLength Vs SepalWidth') plt.xlabel('SepalLength') plt.ylabel('SepalWidth')

NUMPY MATPLOTLIB PANDAS 수치데이터 분석 정방형 데이터 고차원 데이터 머신러닝 작업 시각화 다양한 그래프 문자/숫자 데이터 2차원 표형태 데이터 데이터베이스 작업 통게 분석 import numpy as np import matplotlib.pyplot as plt import pandas as pd