I have imported an excel data of ship operations into a Pandas data frame. The data frame has latitude and longitude and time stamps with an interval of 20 min. The data is for a voyage of one month. I also have the true wind speed and wind angle probability distribution.

Is it possible to generate a random time series of wind speed and wind angles to fit into my already existing Pandas data frame? The condition is that:

1. The time series should be approximately be same as my given probability of occurance.
2. Even though its random the wind speeds and angles should not change drastically. At one time stamp we have 10 knots wind speed and another one its 50 knots. That is not realistic.

The distribution of wind speeds is like this.

Finally, the idea is to able to carry out a simulation performing the same random generation mentioned above for n number of times to calculate the shaft power. This would be something like a monte carlo simulation. Need some guidance for this too.

Can you please give me some ideas and modules or functions in Python using Pandas that I would be able to do this? I can then dig deeper into those to study and complete this. I have added the .csv file with the time stamps and ship speeds.

.csv file with time stamps, latitude and longitude and ship speed