multivariate time series anomaly detection
This is an example of time series data, you can try these steps (in this order):
- plot the data to gain intuitive understanding
- use simple z-score anomaly detection
- use rolling mean and rolling std anomaly detection
- ARMA based models
- STL (seasonal decomposition loess)
- LTSM based deep learning model
I assume this TS data is univariate, since it's not clear that the events are related (you did not provide names or context). If they are related you can see how much they are related (correlation and conintegraton) and do some anomaly detection on the correlation.