SnowyPainter

import mojito
import websockets
import json
import requests
import os
import asyncio
import time

from Crypto.Cipher import AES
from Crypto.Util.Padding import unpad

SnowyPainter

import mojito
import pprint

key = "발급받은 API KEY"
secret = "발급받은 API SECRET"
acc_no = "12345678-01"

broker = mojito.KoreaInvestment(
    api_key=key,
    api_secret=secret,

SnowyPainter

from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense, Dropout
from tensorflow.keras.optimizers import RMSprop
import numpy as np
import random

class QLearningAgent:
    def __init__(self, env, learning_rate=0.1, discount_factor=0.99, epsilon=0.1):
        self.env = env
        self.step_size = learning_rate

SnowyPainter

import pandas as pd
import numpy as np

files = ["nvda.csv", "vix.csv", "eur.csv"]

def open_df(fn):
    df = pd.read_csv(fn)
    df.drop(["Vol.","Change %","Open","Low","High"], axis=1, inplace=True)
    df["Price"] = df["Price"].astype(float)
    df['Date'] = pd.to_datetime(df['Date'], format='%m/%d/%Y')

SnowyPainter

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)")

SnowyPainter

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

SnowyPainter

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))

SnowyPainter

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',

SnowyPainter

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)

SnowyPainter

import random

def r():
    nums = list(range(1, 26))
    random.shuffle(nums)
    return nums

table = []
for i in range(9):
    table += r()