일 | 월 | 화 | 수 | 목 | 금 | 토 |
---|---|---|---|---|---|---|
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 |
- vscode
- java역사
- 웹 용어
- postorder
- 결합전문기관
- bccard
- KNeighborsClassifier
- classification
- inorder
- web 사진
- CES 2O21 참여
- 데이터전문기관
- cudnn
- mglearn
- web 용어
- web
- html
- paragraph
- pycharm
- discrete_scatter
- tensorflow
- 대이터
- 재귀함수
- Keras
- CES 2O21 참가
- 자료구조
- broscoding
- 머신러닝
- C언어
- web 개발
- Today
- Total
목록[IT]/python.matplotlib (18)
bro's coding

import numpy as np import matplotlib.pyplot as plt x=np.arange(-1,1,0.1) y=np.arange(-1,1,0.1) X,Y=np.meshgrid(x,y) Z=np.exp(-(X**2+Y**2)) CS=plt.contourf(X,Y,Z,levels=np.arange(-1,1,0.05),alpha=0.5,cmap='seismic') plt.colorbar() CS=plt.contour(X,Y,Z,levels=np.arange(-1,1,0.05)) plt.clabel(CS,inline=2,fontsize=10) https://broscoding.tistory.com/81 matplotlib.contour(등고선 그리기 1) import numpy as np..

import numpy as np import matplotlib.pyplot as plt # x,y의 구간 설정 x=np.arange(-1,1,0.1) y=np.arange(-1,1,0.1) # x,y에 대한 관계좌표 설정 X,Y=np.meshgrid(x,y) # X,Y에 관한 Z값 설정 Z=np.sin(X*Y) #var = plt.contour(X, Y, Z, 레벨 설정) CS=plt.contour(X,Y,Z,levels=np.arange(-1,1,0.2)) #주석 달아주기 plt.clabel(CS,inline=2,fontsize=10) # 컬러바 생성 plt.colorbar() https://broscoding.tistory.com/82 matplotlib.contourf(등고선 그리기 2) imp..

import matplotlib.pyplot as plt img=plt.imread('제목 없음.png') plt.imshow(img*[2.,1.,1.],vmax=1)

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()

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')

주피터 노트북에서! plt.plot([1,2,3,4,5]) plt.legend(['SI'],['SW'],['PI'],[PW]]) 프롬프트에서! import matplotlib.pyplot as plt plt.plot([1,2,3,4,5]) [] plt.show() https://datascienceschool.net/view-notebook/d0b1637803754bb083b5722c9f2209d0/ Data Science School Data Science School is an open space! datascienceschool.net