Is probability of occurrence of a binary event simply the proportion of its occurrence? I have a data frame with binary features Weekday and Weekend like this with occurrences of a specific event:
| ID | Weekday | Weekend
| ---| --------|--------
| 01 | 1       | 0
| 02 | 0       | 1
| 03 | 0       | 1
| 04 | 0       | 1

Now I'm expected to give "probabilities of event in weekdays and weekends respectively". Are these respective probabilities simply the proportions of events happening on weekdays/weekends? So probability of event happening on weekday is 1/4 (25%), while on weekend is 3/4 (75%)? So simple?

It can be understood by the definition of Probability, but there are a lot of definitions for probability, which are Classical, Empirical, Axiomatic, Subjective...
Here we need to understand Classical and Empirical Probability
Classical Probability
This is the Probability that is used most by non-statisticians and used in an introductory course: it simply implies the probability is a fraction whose numerator is the number  of events we are interested in and the denominator is the number of possible outcomes. For example, suppose we have a coin with two sides Head(H) and Tail(T) then the probability of obtaining Head
$$
P(H) = \frac{Number \ of \ Heads}{Total \ Number \ of \ Sides} = \frac{1}{2}
$$
It looks good and can be applied in your problem and we will get $\frac{1}{2}$, but it fails when the coin we are observing is biased.  suppose we have a coin that always turns into Head, there it fails and hence comes the Empirical Probability
Empirical Probability
It is also known as the frequentist approach. We define
$$
f_n = \frac{M_n}{n}
$$
where $M_n$ number of favorable outcomes in n random experiments in an identical condition, and the probability is given by
$$
P(M) = lim_{n \to \infty}f_n
$$
So in your case, your approximation of Empirical Probability is correct, that is 1/4 and 3/4.
