Append exact Timestamp to new DataFrame after looping (Can`t Find TimeStamp related to coefficient)

Wanted to do a Linear regression of Pressure versus time. Converted Timestamp into values and saved in the 'z' column. The timestamp is per minute for 3 days. I gave 15-minute intervals and created Time1 and Time2 (something like rolling windows) Problem is that I obtain the model. coef_ but cant extract related Timestamps.

minute_summary['z'] = minute_summary['Timestamp'].apply(lambda x: time.mktime(x.timetuple()))
t_s = minute_summary[['Time1','Time2']].copy()
t_s = t_s.dropna()
ks = pd.DataFrame()
ks1 = pd.DataFrame()
for i in range(len(minute_summary)):
    to_work = minute_summary[(minute_summary['Timestamp'] >= t_s.iloc[i][0]) & (minute_summary['Timestamp'] <= t_s.iloc[i][1])]
    # ks = ks.append(pd.DataFrame(to_work['Timestamp']))
    to_work = to_work[['Timestamp', '(DHP)', 'z']].copy().dropna()
    y = np.asarray(to_work['(DHP)'])
    x = np.asarray(to_work[['z']])
    model = LinearRegression() #create linear regression object
    model = LinearRegression().fit(x, y) #train model on train data
    r_sq = model.score(x, y)
    ks = ks.append(pd.DataFrame(model.coef_)).reset_index(drop=True)
    ks1 = ks1.append(pd.DataFrame(minute_summary['Timestamp'])).reset_index(drop=True)
How many English words
do you know?
Test your English vocabulary size, and measure
how many words do you know
Online Test
Powered by Examplum