# Transpose Rows and Columns

**URL:** <https://forum.inductiveautomation.com/t/transpose-rows-and-columns/14308>\
**Category:** Ignition\
**Tags:** ignition79\
**Created:** [May 16, 2017, 11:07am UTC](https://forum.inductiveautomation.com/t/transpose-rows-and-columns/14308 "2017-05-16T11:07:58Z")\
**Posts on this page:** 1\
**Showing post:** 2

<div class="post-metadata">

**Author:** ![pturmel](https://sea1.discourse-cdn.com/inductiveautomation/user_avatar/forum.inductiveautomation.com/pturmel/32/3295_2.png) [@pturmel](https://forum.inductiveautomation.com/u/pturmel)\
**Post date:** [May 16, 2017, 12:13pm UTC](https://forum.inductiveautomation.com/t/transpose-rows-and-columns/14308/2 "2017-05-16T12:13:20Z")

</div>

I have something that could be massaged into what you need. The follow code is designed to take one or more datasets, each with a just a few rows, and flip all the rows into columns. Should be close to what you need:

```auto

#----------
# Construct a dataset with columns from supplied datasets rows. The column
# names from the first dataset become the string values in the first column
# of the result. The first argument to the function is a sequence of names
# for the dataset arguments. The name string is used verbatim if the
# dataset has one row. Otherwise it is concatenated with the row number.
def flipData(names, *args):
	from com.inductiveautomation.ignition.common.util import DatasetBuilder
	from java.lang import String as jString, Object as jObject, Long as jLong
	ds1 = args[0]
	firstcolumn = [x for x in ds1.columnNames]
	types = [jString]
	heads = ['_']
	columns = [firstcolumn]
	for dsn, ds in enumerate(args):
		collist = range(ds.columnCount)
		if ds.rowCount==0:
			heads.append(names[dsn])
			types.append(jObject)
			columns.append([None for x in firstcolumn])
		for rn in range(ds.rowCount):
			if rn==0:
				heads.append(names[dsn])
			else:
				heads.append("%s %d" % (names[dsn], 1+rn))
			types.append(jObject)
			row = [ds.getValueAt(rn, cn) for cn in collist]
			for i, x in enumerate(row):
				if isinstance(x, long):
					row[i] = jLong(x)
			columns.append(row)
	rows = zip(*tuple(columns))
	builder = DatasetBuilder.newBuilder().colNames(heads).colTypes(types)
	for row in rows:
		t = tuple(row)
		builder.addRow(*t)
	return builder.build()

```

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