Search Missing Timestamp and display in python?

Question

Here is my some Dataset which having Time,Temperature1,Temperature2

Timestamp.             Temperature1.        Temperature2
09/01/2016 00:00:08          53.         


        

Answer 1

Assuming that the timestamps have been converted to datetime, if you set the index to the timestamp column and then reindex with a date range then the missing values will show up:

In [94]:
df['Timestamp'] = pd.to_datetime(df['Timestamp'])
df = df.set_index('Timestamp')
df

Out[94]:
                     Temperature1  Temperature2
Timestamp                                      
2016-09-01 00:00:08          53.4          45.5
2016-09-01 00:00:38          53.5          45.2
2016-09-01 00:01:08          54.6          43.2
2016-09-01 00:01:38          55.2          46.3
2016-09-01 00:02:08          54.5          45.5
2016-09-01 00:04:08          54.2          35.5
2016-09-01 00:05:08          52.4          45.7
2016-09-01 00:05:38          53.4          45.2

In [96]:    
df.reindex(pd.date_range(start=df.index[0], end=df.index[-1], freq='30s'))

Out[96]:
                     Temperature1  Temperature2
2016-09-01 00:00:08          53.4          45.5
2016-09-01 00:00:38          53.5          45.2
2016-09-01 00:01:08          54.6          43.2
2016-09-01 00:01:38          55.2          46.3
2016-09-01 00:02:08          54.5          45.5
2016-09-01 00:02:38           NaN           NaN
2016-09-01 00:03:08           NaN           NaN
2016-09-01 00:03:38           NaN           NaN
2016-09-01 00:04:08          54.2          35.5
2016-09-01 00:04:38           NaN           NaN
2016-09-01 00:05:08          52.4          45.7
2016-09-01 00:05:38          53.4          45.2

This assumes that the timestamps are regular, here we construct a date range using the timestamp first and last values with a frequency of 30 seconds:

In [97]:
pd.date_range(start=df.index[0], end=df.index[-1], freq='30s')

Out[97]:
DatetimeIndex(['2016-09-01 00:00:08', '2016-09-01 00:00:38',
               '2016-09-01 00:01:08', '2016-09-01 00:01:38',
               '2016-09-01 00:02:08', '2016-09-01 00:02:38',
               '2016-09-01 00:03:08', '2016-09-01 00:03:38',
               '2016-09-01 00:04:08', '2016-09-01 00:04:38',
               '2016-09-01 00:05:08', '2016-09-01 00:05:38'],
              dtype='datetime64[ns]', freq='30S')

When you reindex with this, any missing index labels become NaN values