I don’t think you would have to take the time to calculate the mean and median for this. Mean is more influenced by skewed data, this graph has a positive skew meaning that the mean will be greater than the median. More on reddit.com

I always say it "mean, median, mode." (Alphabetical order) Mean is the average Median is the one(s) in the middle (just like it's in the middle of the phrase "mean, median, mode") MOde - the one you see the MOst More on reddit.com

From a data engineer's perspective, average is much easier to compute than median for large datasets. To calculate an average for a long list of values, all you need is a sum and a total. The database can read each value once, add it to the sum, then release it from memory and move on. For a median however, you need to sort all the values and find the value in the middle, which requires more compute time and memory. There are a few algorithms that improve this but none of them scale very well. None of this matters if you only have 100 or 1,000 values, or if you're doing one-time calculations. But for us, our data analysts ask us to produce reports from tables with millions of records, with live dashboards that constantly get updated. So unless there's a really good reason to use a median instead of a mean, we'll go with the mean. More on reddit.com

Select the data you need and run your descriptives? You can put your selection in a new dataframe or vector if you want? Or like this http://www.cookbook-r.com/Manipulating_data/Summarizing_data/ https://www.statmethods.net/stats/descriptives.html More on reddit.com