import pandas as pd import numpy as np from sklearn.model_selection import train_test_split import datetime as dt from sklearn.linear_model import LogisticRegression df = pd.read_csv('https://raw.githubusercontent.com/sahdan96/covid19/main/owid-covid-data.csv') my_case = df[df['location']=='Malaysia'].reset_index() my_case['date'] = pd.to_datetime(my_case['date'], format="%Y-%m-%d") my_case['date'] = my_case['date'].map(dt.datetime.toordinal) x_train, x_test, y_train, y_test = train_test_split(my_case['date'], my_case['total_cases'], test_size=0.2) model = LogisticRegression() newX =np.array(x_train).reshape(-1,1) newY =np.array(y_train).reshape(-1,1) newX_test = np.array(x_test).reshape(-1,1) newY_test =np.array(y_test).reshape(-1,1) model.fit(newX, newY) pred =model.predict(newX_test) from sklearn.metrics import accuracy_score acc = accuracy_score(newY_test,pred) print(acc)
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