sons dataStory

이변량 분포의 시각화 그래프를 작성하기 위해 kospi 지수의 일일자료를 호출하여 사용합니다. import numpy as np from sklearn.datasets import make_blobs import pandas as pd from sklearn.preprocessing import StandardScaler import matplotlib.pyplot as plt plt.rcParams['font.family'] ='NanumGothic' plt.rcParams['axes.unicode_minus'] =False import seaborn as sns import yfinance as yf from scipy import stats st=pd.Timestamp(2023, 10, 17) et=pd.Timestamp(2024, 10, 17) kos=yf.download("^KS11",st, et) kos=kos.drop('Adj Close', axis=1) kos.columns=kos.columns.levels[0][1:] scaler=StandardScaler().fit(kos) kos1=scaler.transform(kos) kos1df=pd.DataFrame(kos1) kos1df.columns=kos.columns kos1df['coChg']=pd.qcut(np.ravel((kos1df.Close-kos1df.Open)/kos1df.Open*100), 10, range(10)) kos1df['volChg']=pd.qcut(np.ravel(kos1df.Volume.pct_change()), 5, range(5)) kos1df=kos1df.dropna() kos1df.head(3) Price Close High Low Open Volume ...