How to append a new row to a DataFrame?

Question

I have a folder of 800 .csv files, each with 3 columns and 2048 rows. I'm trying to use ML.NET to retrieve the first column of each .csv file, transpose it into a row, and append each into a Dataframe. So in the end I expect a dataframe of shape (200 x 2048).

I can do everything except transpose the columns and append rows to a dataframe. Can't find anything of use in the documentation either, unless I missed something vital.

var dataFrame1 = new DataFrame();
for (int i = 0; i < files.Length; i++)
            {
                IDataView data = mlContext.Data.LoadFromTextFile<CsvData>(files[i], separatorChar: ',', hasHeader: true);

                data = mlContext.Data.SkipRows(data, minrange);
                data = mlContext.Data.TakeRows(data, maxrange - minrange);

                var pipeline = mlContext.Transforms.SelectColumns(new string[] { "PE" , "FPos"})
                               .Append(mlContext.Transforms.NormalizeMinMax("PE", fixZero:false));
                var preview = pipeline.Fit(data).Transform(data);
                var peColumn = preview.GetColumn<float>("PE");

                var fPosColumn = preview.GetColumn<float>("FPos");
                var testDfPE = new SingleDataFrameColumn("PE", peColumn);
                var testDfFPOS = new SingleDataFrameColumn("FPos", fPosColumn);
                ...
            }

I tried extracting each column into testDfPE, testDfFPOS, and maybe appending them to dataFrame1, but that just appends them column-wise, not row-wise. I can't figure out an efficient way of solving this, especially considering I'm working with a large number of .csv files. For additional context, I'm eventually going to use this dataframe with a pretrained model in .onnx format