Linear Regression on Time Series

[buran]

I think there is some confusion in your understanding, but anyway

import pandas as pd
import numpy as np
df = pd.DataFrame([['2017-11-10', 4470.76], ['2017-11-11', 5465.72], ['2017-11-12', 15465.72]], columns=['Date_Time', 'eie'])
y = np.array(df['eie'], dtype=float)
x = np.array(pd.to_datetime(df['Date_Time'], format='%Y-%m-%d'), dtype='datetime64[D]')
print(y)
print(x)

Output:
[ 4470.76  5465.72 15465.72]
['2017-11-10' '2017-11-11' '2017-11-12']

or

import pandas as pd
import numpy as np
df = pd.DataFrame([['2017-11-10', 4470.76], ['2017-11-11', 5465.72], ['2017-11-12', 15465.72]], columns=['Date_Time', 'eie'])
y = np.array(df['eie'], dtype=float)
x = np.array(pd.to_datetime(df['Date_Time'].index.values+1, format='%Y-%m-%d'), dtype=int)
print(y)
print(x)

Output:
[ 4470.76  5465.72 15465.72]
[1 2 3]