Example of Logistic Regression using a proportion as the dependent variable? I am trying to run a logistic regression on a data set where my dependent variable is a proportion of a binary variable, rather than the binary variable itself.  I have seen a ton of documentation that says this is possible, but I am having trouble finding an example of how to actually do it.  I am open to using scikit learn, statsmodels, or any other library that will do it.

I have added a photo showing a simplified version of my data.

successes here is just a count of a binary (1/0) outcome.  instead of having the individual observations, I only have them rolled up, but my understanding is that it is still a logistic regression problem.  I want to predict the dependent variable 'proportion' based on the features.  I understand this conceptually, but am just trying to find an example of this in python.  all of the examples I have seen assume a binary dependent variable.

your help is appreciated!
As the link by @Spacedman shows, binomial regression works well. If you don't have the attempts and successes but, instead, have just the proportion, then you'll want to use beta-regression. After a little digging, it doesn't seem like this is available in Python. Here's a blog post demoing it in R.