There might be a simple solution for simple cases (where non-numeric columns are of no concern and simply ALL columns can be aggregated). I created a more sophisticated and flexible approach, using a custom function:
all_attributes_min(attributes(), make_list('field_to_exclude1', 'field2_to_exclude'))
where attributes() passes on a map for each feature {'Field1':value1, ..., 'FieldX':valueX} and make_list('') can be used to exclude fields (= attributes) that should be excluded from the aggregate.
The function has some checks implemented (exclude NULL, None, 0 and non-numerical values) that you can adjust by removing the corresponding lines of code. Also you can adjust it to use max, mean, ... instead of min.
To use the function, create the following two functions in the function editor (Tab next to 'Expression' within the Expression Editor).
The code comes with it's documentation for usage, therefore it's a bit long. The actual logic is quite short, making use of list comprehension.
You can view the "compiled" documentation when clicking on the respective custom function in the box next to the expression editor:
Function 1: Helper function
from qgis.core import *
from qgis.gui import *
@qgsfunction(args=-1, group='Custom')
def make_list(list_of_args, feature, parent):
"""
Creates a python list from a number of arguments.
<h2>Example usage:</h2>
<ul>
<li>make_list(1, 2 ,3) -> [1, 2, 3]</li>
</ul>
"""
return list_of_args
Function 2: Aggregate function
from qgis.core import *
from qgis.gui import *
@qgsfunction(args='auto', group='Custom')
def all_attributes_min(attrmap, exclude, feature, parent):
"""
Calculates the min of an attrmap.
The argument exclude is a list of attributes (identified by column name)
that should be ignored.
Currently this function also removes 0 values.
<h2>Example usage 1</h2>
<ul>
<li>all_attributes_min({'A':72, 'B':7, 'C':42}, []) -> 7</li>
<li>all_attributes_min({'A':72, 'B':7, 'C':42}, ['B']) -> 42</li>
<li>all_attributes_min(attributes(), ["field2"]) -> 42</li>
</ul>
<h2>Example usage 2</h2>
<p>With a table resulting from the tool Distance Matrix,
containing a field "ID" and several number fields:</p>
<p>
<code>{'ID':'node-42', 'node-1':4, 'node-2':4, ..., 'node-42':0, 'node-43':999}</code>
</p>
<p>The exclude argument can be used to filter non-numeric attributes, e.g.
<code>all_attributes_min(attributes(), make_list('ID', 'fid'))</code>
</p>
<p>Or in case of the distance matrix, also, the use the ID field to remove the
attribute of the node itself, which would have distance 0 (in the example 42):
<code>all_attributes_min(attributes(), make_list("ID", 'ID', 'fid'))</code>
</p>
<p>
For this example the helper function make_list() needs to be present, too:
</p>
<p>
<code>
@qgsfunction(args=-1, group='Custom')<br/>
def make_list(list_of_args, feature, parent):<br/>
return list_of_args<br/>
</code>
</p>
"""
# exclude not needed fields
attrmap_filtered = {key: attrmap[key] for key in attrmap.keys() if key not in exclude}
# remove non-numeric entries to prevent errors
my_vals = [i for i in attrmap_filtered.values() if isinstance( i, ( int, float ) )]
# remove None entries to prevent errors
my_vals = [i for i in my_vals if i is not None]
# remove 0 entries to prevent 0-minimas
my_vals = [i for i in my_vals if i != 0]
# check for empty list
if my_vals:
my_min = min(my_vals)
return my_min
else:
return -1
