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import pandas as pd 
import numpy as np 
import matplotlib.pyplot as plt
%matplotlib inline

import warnings
warnings.filterwarnings("ignore")
data=pd.read_csv('UNRATE.csv',header=None)
data.columns=['Month', 'UNRATE']
data.head(25)
data['Month']=pd.to_datetime(data['Month'], format='%m-%d-%Y')
data.info()
<class 'pandas.core.frame.DataFrame'> RangeIndex: 867 entries, 0 to 866 Data columns (total 2 columns): # Column Non-Null Count Dtype --- ------ -------------- ----- 0 Month 867 non-null datetime64[ns] 1 UNRATE 867 non-null float64 dtypes: datetime64[ns](1), float64(1) memory usage: 13.7 KB
train_len=612
train=data[:train_len]
test=data[train_len:]