Hello,

So let me first describe what I am working with and the steps I took.

One dataset has for every company every year stated like, 1992, 1993, 1994, 1995.. and so on. with financial information about companies.

the next dataset is about CEO financials, and there it's 1992, 1992, 1992, 1993, 1993, 1993, 1993.. and so on. Because some companies have more or less CEO's per year.

I have used 1:m merge, and it looks like its merged. I then looked at the CEO GENDER, which is main part of my study, and deleted the rows which did not match.

I checked whether it removed rows of information, but it kept the information of Dataset 1 and moved/multiplied the information from the 'company financials years' to CEO financials. Like this: [merged]

Year....CEO FIN....Company FIN

X1......X1-Male............X1

X1......X1-Male............X1

X1......X1-Female............X1

Now it's of course counting all the years multiple times and therefore the sample size looks deceitful, it's giving something like 293,123 as sample size only because the years are counted more than once.

Is there a way to shorten the rows when using it in calculations? And secondly, I thought to only keep 1 row per year of the information when there is a Female CEO that year (if more, I summarize) I'll use only X1-Female, and otherwise I'll use Male (X1-Male). So that per company year there will be one row. But am kinda clueless how to perform such task.
Does anyone know how to do this, or even if this is possible. Thanks.