Weird Behavior in Group_By

[patrickw]

I have a custom R visualization within Power BI. The visualization works fine in my own Power BI Desktop but I am noticing some weird behavior when uploading the dashboard to Power BI Services.

When I group by a column the data such as:

dataset = dataset %>%
group_by(month, year, groupname) %>%
summarize(y = cumsum(y))

it is not grouping correctly. The groupname column will start with two different values to group, lets say "A" and "B" but when I group the data the output will be the "B" column and a bunch of different numbers like "0", "12", "2" , etc... with NA values. The whole dataset seems to be messed up. Other columns like the month and year now reading as NA instead of their original values.

There are other columns I use this same behavior on within the data.frame and these seem to group correctly except for this one. I am not sure what is causing this behavior.

[patrickw]

Does anyone know a different approach I can use to do a group_by than with dplyr and see if it makes a difference?

[siddharthprabhu]

I think you will need to post a reproducible example in order for us to be able to help you effectively. Maybe you could just sample a few rows from your actual data set since it's very likely that the problem is with your data.

FAQ: How to do a minimal reproducible example ( reprex ) for beginners

A minimal reproducible example consists of the following items: A minimal dataset, necessary to reproduce the issue The minimal runnable code necessary to reproduce the issue, which can be run on the given dataset, and including the necessary information on the used packages. Let's quickly go over each one of these with examples: Minimal Dataset (Sample Data) You need to provide a data frame that is small enough to be (reasonably) pasted on a post, but big enough to reproduce your issue. Let's say, as an example, that you are working with the iris data frame head(iris) #> Sepal.Length Sepal.Width Petal.Length Petal.Width Species #> 1 5.1 3.5 1.4 0.2…