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| import random | |
| computer = random.randint(1,3) | |
| player = int(input("가위, 바위, 보 중 하나를 선택하시오. (가위=1, 바위=2, 보=3): ")) | |
| if computer == player: | |
| print("비겼습니다.") | |
| elif player == 1: | |
| if computer == 2: | |
| print("졌습니다 (가위<바위)") |
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| import matplotlib.pyplot as plt | |
| class Neuron: | |
| def __init__(self, package): | |
| self.schwannCells = 0 | |
| self.Ranviers = -1 | |
| self.neurotransmitter = package | |
| self.Potential = -70 | |
| self.i = 0 |
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| import numpy as np | |
| import pandas as pd | |
| import matplotlib.pyplot as plt | |
| from sklearn.datasets import load_iris | |
| def andrews_curve(data, weights=None): | |
| num_variables = data.shape[1] | |
| t = np.linspace(0, 2*np.pi, 100) | |
| curve = np.zeros((len(t), 2)) |
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| import random | |
| sn1 = ['It', 'is', 'a fundraising event', 'which', 'is held', 'on', 'a Friday', 'in March', 'every', 'other', 'year'] | |
| sn2 = ['Foodbank', 'also supports', 'food drives', 'for', 'individuals', 'who', 'want', 'to', 'share', 'their', 'food', 'with', 'the', 'poor', 'in the', 'country'] | |
| sn3 = ['When', 'I', 'called', "Foodbank's office", 'people', 'there', 'let', 'me', 'know', 'in detail', 'how', 'I', 'could', 'donate', 'food', 'to', 'the', 'hungry'] | |
| sn4 = ['These thousands', 'of', 'Santas', 'spread', 'the spirit', 'of', 'Christmas', 'to', 'Australian kids', 'who are', 'sick', 'or', 'disadvantaged'] | |
| sn5 = ['He', 'led', 'a', 'mostly', 'unremarkable', 'life', ', working', 'as', 'a', 'Paris customs service officer', 'until', 'his', 'late', 'forties'] | |
| sn6 = ['The', 'public', 'and', 'critics', 'laughed at', "Rousseau's", 'flat,', 'seemingly', 'childish', 'style', 'of', 'portraying', 'human', 'figures'] | |
| sn7 = ['In', 'this', 'way,', 'he', 'created', 'his', 'own', 'mysterious', 'jungle', 'paintings', 'where', |
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| import matplotlib.pyplot as plt | |
| from mpl_toolkits.mplot3d import Axes3D | |
| import numpy as np | |
| fig = plt.figure() | |
| ax = fig.add_subplot(111, projection='3d') | |
| # 첫 번째 구 | |
| u, v = np.mgrid[0:2*np.pi:20j, 0:np.pi:10j] | |
| x = 1.5 * np.cos(u) * np.sin(v) |
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| import random | |
| def r(): | |
| nums = list(range(1, 26)) | |
| random.shuffle(nums) | |
| return nums | |
| table = [] | |
| for i in range(9): | |
| table += r() |
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| import requests | |
| import urllib | |
| #OpenAPI 금융위원회 파생상품시세정보 | |
| key = "" | |
| #numOfRows : 1 | |
| #pageNo : 1 | |
| #beginBasDt : ex) 20230215. 2023년 2월 15일~... 현재-1 까지. | |
| #resultType : json / xml | |
| #serviceKey : key |
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| import pandas as pd | |
| code_df = pd.read_csv('2021licode.csv') | |
| stat_df = pd.read_csv('2021listat.csv') | |
| code_df = code_df.drop(code_df.columns[[3,4,5]], axis=1) | |
| code_df = code_df.iloc[3:-1] | |
| def counted_tag(tag): | |
| l = [x for x in stat_df[tag].tolist() if str(x) != 'nan'] |
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| let ids = new Set(arr1.map(d => d.id)); | |
| let merged = [...arr1, ...arr2.filter(d => !ids.has(d.id))]; |
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| let sqlite3 = require('sqlite3').verbose(); | |
| let db = new sqlite3.Database('a.sqlite'); | |
| const user_table = { | |
| "id": "INTEGER primary key autoincrement", | |
| "email": "TEXT unique", | |
| "pw": "TEXT", | |
| "name": "TEXT", | |
| "teacher": "INTEGER" | |
| } |