# Combine two datasets

**URL:** <https://forum.inductiveautomation.com/t/combine-two-datasets/45855>\
**Category:** Ignition\
**Created:** [April 21, 2021, 10:24am UTC](https://forum.inductiveautomation.com/t/combine-two-datasets/45855 "2021-04-21T10:24:03Z")\
**Posts on this page:** 1\
**Showing post:** 11

<div class="post-metadata">

**Author:** ![JordanCClark](https://sea1.discourse-cdn.com/inductiveautomation/user_avatar/forum.inductiveautomation.com/jordancclark/32/83362_2.png) [@JordanCClark](https://forum.inductiveautomation.com/u/JordanCClark)\
**Post date:** [April 21, 2021, 12:50pm UTC](https://forum.inductiveautomation.com/t/combine-two-datasets/45855/11 "2021-04-21T12:50:27Z")

</div>

You will need to iterate through each dataset. I find dictionaries useful for this.

```python
# Set up sample datasets
data1 = [['t_stamp', 'val1'],
         [1, 123],
		 [3, 456],
		 [4, 789],
		 [9, 345],
		 [10, 678],
		 [11, 901],
		 [15, 234],
		 [17, 567],
		 [20, 890],
		]
data2 = [['t_stamp', 'val2'],
         [2, 987],
		 [3, 654],
		 [7, 321],
		 [9, 876],
		 [12, 543],
		 [14, 210],
		 [17, 765],
		 [20, 432],
		 [22, 109],
		]

dataset1 = system.dataset.toDataSet(data1[0], data1[1:])
dataset2 = system.dataset.toDataSet(data2[0], data2[1:])

########################################################

def combineDatasets(dataList, commonCol = 't_stamp'):
	''' Combine multiple datasets based on a common column
		dataList: list of datasets
		commonCol: column name common to all datasets	    
	'''
	# Convert all datsets to BasicDataset, if needed
	for i, data in enumerate(dataList):
		if 'com.inductiveautomation.ignition.common.BasicDataset' not in str(type(data)):
			dataList[i] = system.dataset.toDataSet(data)
	
	# Create default value dictionary containing all column names
	# with None values
	blankValueDict = {}
	for data in dataList:
		colNames = list(data.getColumnNames())
		for col in colNames:
			if col != commonCol and col not in blankValueDict.keys():
				blankValueDict[col] = None

	# Process the data
	dataDict = {}
	for data in dataList:
		colNames = list(data.getColumnNames())
		for i in xrange(data.rowCount):
			commonColValue = data.getValueAt(i, commonCol)
			if commonColValue not in dataDict.keys():
				dataDict[commonColValue] = blankValueDict.copy()
			for col in colNames:
				if col != commonCol:
					dataDict[commonColValue][col] = data.getValueAt(i, col)

	# Create combined dataset
	headers = [commonCol] + sorted(blankValueDict.keys())
	data = []
	for key in sorted(dataDict.keys()):
		newRow=[]
		newRow.append(key)
		for col in headers[1:]:
			newRow.append(dataDict[key][col])
		data.append(newRow)
	
	return system.dataset.toDataSet(headers, data)

combinedData = combineDatasets([dataset1, dataset2])

```

Output:

```nohighlight
row | t_stamp | val1 | val2
---------------------------
0 | 1 | 123 | None
1 | 2 | None | 987 
2 | 3 | 456 | 654 
3 | 4 | 789 | None
4 | 7 | None | 321 
5 | 9 | 345 | 876 
6 | 10 | 678 | None
7 | 11 | 901 | None
8 | 12 | None | 543 
9 | 14 | None | 210 
10 | 15 | 234 | None
11 | 17 | 567 | 765 
12 | 20 | 890 | 432 
13 | 22 | None | 109 

```

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