How to approach a regular unevenly-spaced time series?

How do you approach a time series that has a regular pattern of unevenly spaced time between observations?

For example, in the linked picture, I have a time series that only has data for Quarter's 2, 3, and 4 of the financial year in a repeating pattern:

Image of Time Series Data

To graph this data, I thought of three options, either:

a) assume the data is evenly spaced and graph the time series as if there were 3 equal periods (i.e. Qtr 2, 3 and 4 all represent the same period of time)

b) include the missing data, and have gaps in the graph

c) interpoloate the missing data

Visualisation Options

Which option is the most ideal (given that the pattern of missing data is known)?

Option 1 would be the easiest to work with, but would this be bad practice?

For context this data represents the compliance rate of the community following the release of fire inspection notices at 3 different times each year. My intention of using the data is to visualise it and apply a simple moving average to track the data relative to a set target. However if I can get more historical data I would like to apply a forecast.