Let's say I have a dataframe with contains time series as below:

```
Date                value
2000-01-01 00:00:00  4.6
2000-01-01 01:00:00  N/A
2000-01-01 02:00:00  5.3
2000-01-01 03:00:00  6.0
2000-01-01 04:00:00  N/A
2000-01-01 05:00:00  N/A
2000-01-01 06:00:00  N/A
2000-01-01 07:00:00  6.0

```

I want to find an efficient way to calculate the size of the gap (number of consecutive N/As) and add it to a new column of my dataframe to get the following:

```
Date                value  gap_size
2000-01-01 00:00:00  4.6      0
2000-01-01 01:00:00  N/A      1
2000-01-01 02:00:00  5.3      0
2000-01-01 03:00:00  6.0      0
2000-01-01 04:00:00  N/A      3
2000-01-01 05:00:00  N/A      3
2000-01-01 06:00:00  N/A      3
2000-01-01 07:00:00  6.0      0

```

My dataframe in reality has more than 6 millions row so I am looking for the cheapest way in terms of computation. Note that my time series is equi-spaced over the whole dataset (1 hour).