In [23]: df.head()
Out[23]: 
         date  price
0  1349720105  12.08
1  1349806505  12.35
2  1349892905  12.15
3  1349979305  12.19
4  1350065705  12.15
In [25]: df['date'] = pd.to_datetime(df['date'],unit='s')

In [26]: df.head()
Out[26]: 
                 date  price
0 2012-10-08 18:15:05  12.08
1 2012-10-09 18:15:05  12.35
2 2012-10-10 18:15:05  12.15
3 2012-10-11 18:15:05  12.19
4 2012-10-12 18:15:05  12.15

In [27]: df.dtypes
Out[27]: 
date     datetime64[ns]
price           float64
dtype: object

dates = pd.to_datetime(['2019-01-15 13:30:00'])
(dates - pd.Timestamp("1970-01-01")) // pd.Timedelta('1s')  
# Int64Index([1547559000], dtype='int64')

# convert unix timestamp to datetime UTC
df['datetime'] = df['_ts'].map(lambda x: pendulum.from_timestamp(x)) 
df = df.set_index('datetime')
# convert timezone from UTC to GMT+7
df.index = df.index.tz_convert('Asia/Bangkok')