Aggregate operator applied to each subset

SylvainM · May 2019

Hello everyone,

I apologize if this question has already been asked elsewhere, or if it is an obvious one. I'm still learning how to use Rapidminer

This is my problem. Let's suppose that I have a dataset looking like that (but much more different values):

Year Region Item
01 QC CCD
01 QC CCD
01 QC CS

01 ON CCD
01 ON CS

01 NB CCD
01 NB CS
--------------------------
02 QC CCD
02 QC CS
02 QC CS

02 ON CS
02 ON CS

02 NB CCD
02 NB CCD

I would like to get the relative percentage of each Item related to the Region and to the Year:

Year Region Item Proportion
01 QC CCD 66.6%
01 QC CS 33.3%

01 ON CCD 50%
01 ON CS 50%

01 NB CCD 50%
01 NB CCS 50%
-------------------------------------
02 QC CCD 33.3%
02 QC CS 66.6%

02 ON CS 100%

02 NB CCD 100%

I tried many combinations with the operators Aggregate, Loop values, Branch, etc. but I seem to constantly fail...

Do you have any suggestion?

Thanks a lot!
Sylvain

SGolbert · May 2019

Hi @SylvainM

I think I managed to do what you wanted with 2 aggregations and one Join, check it out:

Image: https://us.v-cdn.net/6030995/uploads/editor/xa/x6gv4qleezhj.png

<?xml version="1.0" encoding="UTF-8"?><process version="9.2.001">
<context>
    <input/>
    <output/>
    <macros/>
</context>
<operator activated="true" class="process" compatibility="9.2.001" expanded="true" name="Process">
    <parameter key="logverbosity" value="init"/>
    <parameter key="random_seed" value="2001"/>
    <parameter key="send_mail" value="never"/>
    <parameter key="notification_email" value=""/>
    <parameter key="process_duration_for_mail" value="30"/>
    <parameter key="encoding" value="SYSTEM"/>
    <process expanded="true">
      <operator activated="true" class="python_scripting:execute_python" compatibility="9.2.000" expanded="true" height="82" name="Execute Python" width="90" x="112" y="34">
        <parameter key="script" value="import pandas

# rm_main is a mandatory function, 
# the number of arguments has to be the number of input ports (can be none)
def rm_main():
	import pandas as pd
	import random

	dt = []
	
	for i in range(100):
	    region = random.choice(['America', 'Europe', 'Asia'])
	    quartile = random.choice(range(1,5))
	    item = random.choice(['A', 'B', 'C'])
	    dt.append([region, quartile, item])
	    
	dt = pd.DataFrame(dt, columns=['region', 'quarter', 'item'])
	return dt"/>
        <parameter key="use_default_python" value="true"/>
        <parameter key="package_manager" value="conda (anaconda)"/>
      </operator>
      <operator activated="true" class="numerical_to_polynominal" compatibility="9.2.001" expanded="true" height="82" name="Numerical to Polynominal" width="90" x="246" y="34">
        <parameter key="attribute_filter_type" value="single"/>
        <parameter key="attribute" value="quarter"/>
        <parameter key="attributes" value=""/>
        <parameter key="use_except_expression" value="false"/>
        <parameter key="value_type" value="numeric"/>
        <parameter key="use_value_type_exception" value="false"/>
        <parameter key="except_value_type" value="real"/>
        <parameter key="block_type" value="value_series"/>
        <parameter key="use_block_type_exception" value="false"/>
        <parameter key="except_block_type" value="value_series_end"/>
        <parameter key="invert_selection" value="false"/>
        <parameter key="include_special_attributes" value="false"/>
      </operator>
      <operator activated="true" class="order_attributes" compatibility="9.2.001" expanded="true" height="82" name="Reorder Attributes" width="90" x="380" y="34">
        <parameter key="sort_mode" value="user specified"/>
        <parameter key="attribute_ordering" value="region|quarter|item"/>
        <parameter key="use_regular_expressions" value="false"/>
        <parameter key="handle_unmatched" value="append"/>
        <parameter key="sort_direction" value="ascending"/>
      </operator>
      <operator activated="true" class="multiply" compatibility="9.2.001" expanded="true" height="103" name="Multiply" width="90" x="514" y="34"/>
      <operator activated="true" class="aggregate" compatibility="9.2.001" expanded="true" height="82" name="Aggregate" width="90" x="648" y="34">
        <parameter key="use_default_aggregation" value="false"/>
        <parameter key="attribute_filter_type" value="all"/>
        <parameter key="attribute" value=""/>
        <parameter key="attributes" value=""/>
        <parameter key="use_except_expression" value="false"/>
        <parameter key="value_type" value="attribute_value"/>
        <parameter key="use_value_type_exception" value="false"/>
        <parameter key="except_value_type" value="time"/>
        <parameter key="block_type" value="attribute_block"/>
        <parameter key="use_block_type_exception" value="false"/>
        <parameter key="except_block_type" value="value_matrix_row_start"/>
        <parameter key="invert_selection" value="false"/>
        <parameter key="include_special_attributes" value="false"/>
        <parameter key="default_aggregation_function" value="average"/>
        <list key="aggregation_attributes">
          <parameter key="item" value="count"/>
        </list>
        <parameter key="group_by_attributes" value="quarter|region|item"/>
        <parameter key="count_all_combinations" value="false"/>
        <parameter key="only_distinct" value="false"/>
        <parameter key="ignore_missings" value="true"/>
      </operator>
      <operator activated="true" class="aggregate" compatibility="9.2.001" expanded="true" height="82" name="Aggregate (2)" width="90" x="648" y="187">
        <parameter key="use_default_aggregation" value="false"/>
        <parameter key="attribute_filter_type" value="all"/>
        <parameter key="attribute" value=""/>
        <parameter key="attributes" value=""/>
        <parameter key="use_except_expression" value="false"/>
        <parameter key="value_type" value="attribute_value"/>
        <parameter key="use_value_type_exception" value="false"/>
        <parameter key="except_value_type" value="time"/>
        <parameter key="block_type" value="attribute_block"/>
        <parameter key="use_block_type_exception" value="false"/>
        <parameter key="except_block_type" value="value_matrix_row_start"/>
        <parameter key="invert_selection" value="false"/>
        <parameter key="include_special_attributes" value="false"/>
        <parameter key="default_aggregation_function" value="average"/>
        <list key="aggregation_attributes">
          <parameter key="item" value="count"/>
        </list>
        <parameter key="group_by_attributes" value="quarter|region"/>
        <parameter key="count_all_combinations" value="false"/>
        <parameter key="only_distinct" value="false"/>
        <parameter key="ignore_missings" value="true"/>
      </operator>
      <operator activated="true" class="rename" compatibility="9.2.001" expanded="true" height="82" name="Rename" width="90" x="782" y="187">
        <parameter key="old_name" value="count(item)"/>
        <parameter key="new_name" value="region_quarter_total"/>
        <list key="rename_additional_attributes"/>
      </operator>
      <operator activated="true" class="concurrency:join" compatibility="9.2.001" expanded="true" height="82" name="Join" width="90" x="916" y="34">
        <parameter key="remove_double_attributes" value="true"/>
        <parameter key="join_type" value="inner"/>
        <parameter key="use_id_attribute_as_key" value="false"/>
        <list key="key_attributes">
          <parameter key="region" value="region"/>
          <parameter key="quarter" value="quarter"/>
        </list>
        <parameter key="keep_both_join_attributes" value="false"/>
      </operator>
      <operator activated="true" class="generate_attributes" compatibility="9.2.001" expanded="true" height="82" name="Generate Attributes" width="90" x="1050" y="34">
        <list key="function_descriptions">
          <parameter key="proportion" value="[count(item)]/region_quarter_total"/>
        </list>
        <parameter key="keep_all" value="true"/>
      </operator>
      <operator activated="true" class="select_attributes" compatibility="9.2.001" expanded="true" height="82" name="Select Attributes" width="90" x="1184" y="34">
        <parameter key="attribute_filter_type" value="subset"/>
        <parameter key="attribute" value=""/>
        <parameter key="attributes" value="region|quarter|item|proportion"/>
        <parameter key="use_except_expression" value="false"/>
        <parameter key="value_type" value="attribute_value"/>
        <parameter key="use_value_type_exception" value="false"/>
        <parameter key="except_value_type" value="time"/>
        <parameter key="block_type" value="attribute_block"/>
        <parameter key="use_block_type_exception" value="false"/>
        <parameter key="except_block_type" value="value_matrix_row_start"/>
        <parameter key="invert_selection" value="false"/>
        <parameter key="include_special_attributes" value="false"/>
      </operator>
      <connect from_op="Execute Python" from_port="output 1" to_op="Numerical to Polynominal" to_port="example set input"/>
      <connect from_op="Numerical to Polynominal" from_port="example set output" to_op="Reorder Attributes" to_port="example set input"/>
      <connect from_op="Reorder Attributes" from_port="example set output" to_op="Multiply" to_port="input"/>
      <connect from_op="Multiply" from_port="output 1" to_op="Aggregate" to_port="example set input"/>
      <connect from_op="Multiply" from_port="output 2" to_op="Aggregate (2)" to_port="example set input"/>
      <connect from_op="Aggregate" from_port="example set output" to_op="Join" to_port="left"/>
      <connect from_op="Aggregate (2)" from_port="example set output" to_op="Rename" to_port="example set input"/>
      <connect from_op="Rename" from_port="example set output" to_op="Join" to_port="right"/>
      <connect from_op="Join" from_port="join" to_op="Generate Attributes" to_port="example set input"/>
      <connect from_op="Generate Attributes" from_port="example set output" to_op="Select Attributes" to_port="example set input"/>
      <connect from_op="Select Attributes" from_port="example set output" to_port="result 1"/>
      <portSpacing port="source_input 1" spacing="0"/>
      <portSpacing port="sink_result 1" spacing="0"/>
      <portSpacing port="sink_result 2" spacing="0"/>
    </process>
</operator>
</process>

I generated some random data with Python.

Best regards,

Sebastian

BalazsBarany · May 2019

Hi,

what you're trying to achieve is called "window functions" in SQL.

You should check out this project, it's an implementation of window functions in RapidMiner.
https://github.com/bbarany/rapidminer-windowfunctions

You can calculate groupwise sums or counts, generate the ratios, and then aggregate according to your needs.

Regards,

Balazs

SylvainM · May 2019

Thanks BalazsBarany and SGolbert for your help,

Your solution, Sebastian, is perfect! Thank you so much!

Best regards to both of you,
Sylvain

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Aggregate operator applied to each subset

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