bro's coding

# 3 X 1080 X 1920 -> 1080 X 1920 X 3(moveaxis) X_train=np.moveaxis(X_train.reshape(-1,3,32,32),1,-1)

# score (np.argmax(pred_y,axis=1)==iris.target).mean()

# 구 twitter_tag.phrases('겨울이 가고 어느덧 봄이 오는지 어제는 봄비가 많이 내렸습니다') # ['겨울', '어제', '봄비']​ from konlpy.tag import Twitter, Okt # 분석 twitter_tag.morphs('홍길동은 조선시대 사람이죠?') # ['홍길동', '은', '조선시대', '사람', '이', '죠', '?'] # 명사 twitter_tag.nouns('겨울이 가고 어느덧 봄이 오는지 어제는 봄비가 많이 내렸습니다') # ['겨울', '봄', '어제', '봄비'] # type twitter_tag.pos('겨울이 가고 어느덧 봄이 오는지 어제는 봄비가 많이 내렸습니다') '''[('겨울', 'Noun'), ('이', 'Josa'), ('가고', '..

https://konlpy.org/ko/latest/install/ 설치하기 — KoNLPy 0.5.2 documentation 우분투 Supported: Xenial(16.04.3 LTS), Bionic(18.04.3 LTS), Disco(19.04), Eoan(19.10) Install dependencies # Install Java 1.8 or up $ sudo apt-get install g++ openjdk-8-jdk python3-dev python3-pip curl Install KoNLPy $ python3 -m pip install --upgrade pip $ p konlpy.org # test code from konlpy.tag import Kkma Kkma_pos = Kkma() ..

imdb_tarin.data[6] b"This movie has a special way of telling the story, at first i found it rather odd as it jumped through time and I had no idea whats happening. Anyway the story line was although simple, but still very real and touching. You met someone the first time, you fell in love completely, but broke up at last and promoted a deadly agony. Who hasn't go through this? but we will never ..

import numpy as np import matplotlib.pyplot as plt from sklearn.datasets import load_breast_cancer cancer = load_breast_cancer() X=cancer.data y=cancer.target plt.scatter(X[:,0],X[:,2]) plt.axis('equal') np.corrcoef(X[:,0],X[:,2]) array([[1. , 0.99785528], [0.99785528, 1. ]]) mat=np.corrcoef(X.T) mat plt.imshow(mat,vmin=-1,vmax=1,cmap='bwr') plt.colorbar() idx = [0, 2, 3, 12, 13, 20, 22, 23, 1, ..

import pandas as pd 'data=pd.read_csv('CARD_SUBWAY_MONTH_201905.csv') # 역명 별 승차총승객수의 합을 오름차순으로 정렬 ser=data.groupby('역명').승차총승객수.sum().sort_values() ser.head()

#data_time을 이용해 요일 알아내기 data2.일자.dt.dayofweek data2['년']=data2.일자.dt.year data2['월']=data2.일자.dt.month data2['일']=data2.일자.dt.day data2['wday']=data2.일자.dt.weekday data2['wname']=data2.일자.dt.weekday_name # 0 : 월요일 data2.head() data2['요일']=data2.일자.dt.weekday.map({0:'월',1:'화',2:'수',3:'목',4:'금',5:'토',6:'일'}) data2.head()

import pandas as pd data=pd.read_csv('CARD_SUBWAY_MONTH_201905.csv') data data.pivot_table(values='승차총승객수',index='사용일자',columns='노선명',aggfunc='sum') # [사용일자:노선명] 에 따른 승차총승객수(sum)