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Calculate Price Elasticity

Member Posts: 10 Contributor I
edited June 2019 in Help
Dear Rapidminer Community

I have a large data set with weekly sales data (price and quantity) of 100+ products over a few months. Is there an efficient way on how to calculate the price elasticity (= %price change/%quantity change) of each individual product?

GL

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Moderator, RapidMiner Certified Analyst, Member Posts: 1,195 Unicorn
Hi @gianluca_scheid,

To better understand , can you provide a sample of your dataset and from this sample give an example
of what you want to obtain ?

Regards,

Lionel
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Member Posts: 10 Contributor I
Hi Lionel,

I attached a sample data file. The real data set just contains more products and observations.

I would like to calculate a linear demand function for every product, in order to see how price changes of a certain product influence the demand for this product.

In this example the results would be
for product 1: -16.308*price+38.251
for product 2: 0.072x*price+5.527

Regards,
GL
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Moderator, RapidMiner Certified Analyst, Member Posts: 1,195 Unicorn
Hi @gianluca_scheid,

Can you give me the relationship between the values for product 1 / product 2 in your file sampledata
and the equations of product 1 and product 2 you give in your last post.

Regards,

Lionel

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Moderator, RapidMiner Certified Analyst, Member Posts: 1,195 Unicorn
Hi again @gianluca_scheid,

A more general process (with this process, you don't have to set the number of products in your dataset) :

```<?xml version="1.0" encoding="UTF-8"?><process version="9.3.001">
<context>
<input/>
<output/>
<macros/>
</context>
<operator activated="true" class="process" compatibility="9.3.001" expanded="true" name="Process">
<parameter key="logverbosity" value="init"/>
<parameter key="random_seed" value="2001"/>
<parameter key="send_mail" value="never"/>
<parameter key="process_duration_for_mail" value="30"/>
<parameter key="encoding" value="SYSTEM"/>
<process expanded="true">
<parameter key="excel_file" value="D:\Lionel\Formations_DataScience\Rapidminer\Tests_Rapidminer\LinearRegression_Elasticity\sampledata.xlsx"/>
<parameter key="sheet_selection" value="sheet number"/>
<parameter key="sheet_number" value="1"/>
<parameter key="imported_cell_range" value="A1"/>
<parameter key="encoding" value="SYSTEM"/>
<parameter key="first_row_as_names" value="true"/>
<list key="annotations"/>
<parameter key="date_format" value=""/>
<parameter key="time_zone" value="SYSTEM"/>
<parameter key="locale" value="English (United States)"/>
<list key="data_set_meta_data_information">
<parameter key="0" value="Product NR.true.integer.attribute"/>
<parameter key="1" value="Calendar Week.true.integer.attribute"/>
<parameter key="2" value="Year.true.integer.attribute"/>
<parameter key="3" value="Price Per Product.true.real.attribute"/>
<parameter key="4" value="Quantity Sold.true.integer.attribute"/>
<parameter key="5" value="Turnover.true.real.attribute"/>
<parameter key="6" value="G.true.polynominal.attribute"/>
<parameter key="7" value="H.true.polynominal.attribute"/>
<parameter key="8" value="I.true.polynominal.attribute"/>
</list>
<parameter key="datamanagement" value="double_array"/>
<parameter key="data_management" value="auto"/>
</operator>
<operator activated="true" class="select_attributes" compatibility="9.3.001" expanded="true" height="82" name="Select Attributes" width="90" x="246" y="34">
<parameter key="attribute_filter_type" value="subset"/>
<parameter key="attribute" value=""/>
<parameter key="attributes" value="Product NR|Price Per Product|Quantity Sold"/>
<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>
<operator activated="true" class="set_role" compatibility="9.3.001" expanded="true" height="82" name="Set Role" width="90" x="380" y="34">
<parameter key="attribute_name" value="Product NR"/>
<parameter key="target_role" value="id"/>
<parameter key="Quantity Sold" value="label"/>
</list>
</operator>
<operator activated="true" class="numerical_to_polynominal" compatibility="9.3.001" expanded="true" height="82" name="Numerical to Polynominal" width="90" x="514" y="34">
<parameter key="attribute_filter_type" value="single"/>
<parameter key="attribute" value="Product NR"/>
<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="true"/>
</operator>
<operator activated="true" class="concurrency:loop_values" compatibility="9.3.001" expanded="true" height="124" name="Loop Values" width="90" x="715" y="34">
<parameter key="attribute" value="Product NR"/>
<parameter key="iteration_macro" value="loop_value"/>
<parameter key="reuse_results" value="false"/>
<parameter key="enable_parallel_execution" value="true"/>
<process expanded="true">
<operator activated="true" class="filter_examples" compatibility="9.3.001" expanded="true" height="103" name="Filter Examples (2)" width="90" x="313" y="34">
<parameter key="parameter_expression" value="[Product NR]==eval(%{loop_value})"/>
<parameter key="condition_class" value="expression"/>
<parameter key="invert_filter" value="false"/>
<list key="filters_list">
<parameter key="filters_entry_key" value="Product NR.equals.eval(%{loop_value})"/>
</list>
<parameter key="filters_logic_and" value="true"/>
</operator>
<operator activated="true" class="concurrency:cross_validation" compatibility="9.3.001" expanded="true" height="145" name="Cross Validation (2)" width="90" x="849" y="34">
<parameter key="split_on_batch_attribute" value="false"/>
<parameter key="leave_one_out" value="false"/>
<parameter key="number_of_folds" value="10"/>
<parameter key="sampling_type" value="automatic"/>
<parameter key="use_local_random_seed" value="false"/>
<parameter key="local_random_seed" value="1992"/>
<parameter key="enable_parallel_execution" value="true"/>
<process expanded="true">
<operator activated="true" class="linear_regression" compatibility="9.3.001" expanded="true" height="103" name="Linear Regression (2)" width="90" x="179" y="34">
<parameter key="feature_selection" value="M5 prime"/>
<parameter key="alpha" value="0.05"/>
<parameter key="max_iterations" value="10"/>
<parameter key="forward_alpha" value="0.05"/>
<parameter key="backward_alpha" value="0.05"/>
<parameter key="eliminate_colinear_features" value="true"/>
<parameter key="min_tolerance" value="0.05"/>
<parameter key="use_bias" value="true"/>
<parameter key="ridge" value="1.0E-8"/>
</operator>
<connect from_port="training set" to_op="Linear Regression (2)" to_port="training set"/>
<connect from_op="Linear Regression (2)" from_port="model" to_port="model"/>
<portSpacing port="source_training set" spacing="0"/>
<portSpacing port="sink_model" spacing="0"/>
<portSpacing port="sink_through 1" spacing="0"/>
</process>
<process expanded="true">
<operator activated="true" class="apply_model" compatibility="9.3.001" expanded="true" height="82" name="Apply Model (2)" width="90" x="45" y="34">
<list key="application_parameters"/>
<parameter key="create_view" value="false"/>
</operator>
<operator activated="true" class="performance_regression" compatibility="9.3.001" expanded="true" height="82" name="Performance (2)" width="90" x="179" y="34">
<parameter key="main_criterion" value="first"/>
<parameter key="root_mean_squared_error" value="true"/>
<parameter key="absolute_error" value="false"/>
<parameter key="relative_error" value="false"/>
<parameter key="relative_error_lenient" value="false"/>
<parameter key="relative_error_strict" value="false"/>
<parameter key="normalized_absolute_error" value="false"/>
<parameter key="root_relative_squared_error" value="false"/>
<parameter key="squared_error" value="false"/>
<parameter key="correlation" value="false"/>
<parameter key="squared_correlation" value="false"/>
<parameter key="prediction_average" value="false"/>
<parameter key="spearman_rho" value="false"/>
<parameter key="kendall_tau" value="false"/>
<parameter key="skip_undefined_labels" value="true"/>
<parameter key="use_example_weights" value="true"/>
</operator>
<connect from_port="model" to_op="Apply Model (2)" to_port="model"/>
<connect from_port="test set" to_op="Apply Model (2)" to_port="unlabelled data"/>
<connect from_op="Apply Model (2)" from_port="labelled data" to_op="Performance (2)" to_port="labelled data"/>
<connect from_op="Performance (2)" from_port="performance" to_port="performance 1"/>
<portSpacing port="source_model" spacing="0"/>
<portSpacing port="source_test set" spacing="0"/>
<portSpacing port="source_through 1" spacing="0"/>
<portSpacing port="sink_test set results" spacing="0"/>
<portSpacing port="sink_performance 1" spacing="0"/>
<portSpacing port="sink_performance 2" spacing="0"/>
</process>
</operator>
<connect from_port="input 1" to_op="Filter Examples (2)" to_port="example set input"/>
<connect from_op="Filter Examples (2)" from_port="example set output" to_op="Cross Validation (2)" to_port="example set"/>
<connect from_op="Cross Validation (2)" from_port="model" to_port="output 1"/>
<connect from_op="Cross Validation (2)" from_port="example set" to_port="output 2"/>
<connect from_op="Cross Validation (2)" from_port="performance 1" to_port="output 3"/>
<portSpacing port="source_input 1" spacing="0"/>
<portSpacing port="source_input 2" spacing="0"/>
<portSpacing port="sink_output 1" spacing="0"/>
<portSpacing port="sink_output 2" spacing="0"/>
<portSpacing port="sink_output 3" spacing="0"/>
<portSpacing port="sink_output 4" spacing="0"/>
</process>
</operator>
<operator activated="false" class="concurrency:loop" compatibility="9.3.001" expanded="true" height="124" name="Loop" width="90" x="648" y="289">
<parameter key="number_of_iterations" value="2"/>
<parameter key="iteration_macro" value="iteration"/>
<parameter key="reuse_results" value="false"/>
<parameter key="enable_parallel_execution" value="true"/>
<process expanded="true">
<operator activated="true" class="filter_examples" compatibility="9.3.001" expanded="true" height="103" name="Filter Examples" width="90" x="246" y="85">
<parameter key="parameter_expression" value=""/>
<parameter key="condition_class" value="custom_filters"/>
<parameter key="invert_filter" value="false"/>
<list key="filters_list">
<parameter key="filters_entry_key" value="Product NR.eq.%{iteration}"/>
</list>
<parameter key="filters_logic_and" value="true"/>
</operator>
<operator activated="true" class="concurrency:cross_validation" compatibility="9.3.001" expanded="true" height="145" name="Cross Validation" width="90" x="581" y="85">
<parameter key="split_on_batch_attribute" value="false"/>
<parameter key="leave_one_out" value="false"/>
<parameter key="number_of_folds" value="10"/>
<parameter key="sampling_type" value="automatic"/>
<parameter key="use_local_random_seed" value="false"/>
<parameter key="local_random_seed" value="1992"/>
<parameter key="enable_parallel_execution" value="true"/>
<process expanded="true">
<operator activated="true" class="linear_regression" compatibility="9.3.001" expanded="true" height="103" name="Linear Regression" width="90" x="179" y="34">
<parameter key="feature_selection" value="M5 prime"/>
<parameter key="alpha" value="0.05"/>
<parameter key="max_iterations" value="10"/>
<parameter key="forward_alpha" value="0.05"/>
<parameter key="backward_alpha" value="0.05"/>
<parameter key="eliminate_colinear_features" value="true"/>
<parameter key="min_tolerance" value="0.05"/>
<parameter key="use_bias" value="true"/>
<parameter key="ridge" value="1.0E-8"/>
</operator>
<connect from_port="training set" to_op="Linear Regression" to_port="training set"/>
<connect from_op="Linear Regression" from_port="model" to_port="model"/>
<portSpacing port="source_training set" spacing="0"/>
<portSpacing port="sink_model" spacing="0"/>
<portSpacing port="sink_through 1" spacing="0"/>
</process>
<process expanded="true">
<operator activated="true" class="apply_model" compatibility="9.3.001" expanded="true" height="82" name="Apply Model" width="90" x="45" y="34">
<list key="application_parameters"/>
<parameter key="create_view" value="false"/>
</operator>
<operator activated="true" class="performance_regression" compatibility="9.3.001" expanded="true" height="82" name="Performance" width="90" x="179" y="34">
<parameter key="main_criterion" value="first"/>
<parameter key="root_mean_squared_error" value="true"/>
<parameter key="absolute_error" value="false"/>
<parameter key="relative_error" value="false"/>
<parameter key="relative_error_lenient" value="false"/>
<parameter key="relative_error_strict" value="false"/>
<parameter key="normalized_absolute_error" value="false"/>
<parameter key="root_relative_squared_error" value="false"/>
<parameter key="squared_error" value="false"/>
<parameter key="correlation" value="false"/>
<parameter key="squared_correlation" value="false"/>
<parameter key="prediction_average" value="false"/>
<parameter key="spearman_rho" value="false"/>
<parameter key="kendall_tau" value="false"/>
<parameter key="skip_undefined_labels" value="true"/>
<parameter key="use_example_weights" value="true"/>
</operator>
<connect from_port="model" to_op="Apply Model" to_port="model"/>
<connect from_port="test set" to_op="Apply Model" to_port="unlabelled data"/>
<connect from_op="Apply Model" from_port="labelled data" to_op="Performance" to_port="labelled data"/>
<connect from_op="Performance" from_port="performance" to_port="performance 1"/>
<portSpacing port="source_model" spacing="0"/>
<portSpacing port="source_test set" spacing="0"/>
<portSpacing port="source_through 1" spacing="0"/>
<portSpacing port="sink_test set results" spacing="0"/>
<portSpacing port="sink_performance 1" spacing="0"/>
<portSpacing port="sink_performance 2" spacing="0"/>
</process>
</operator>
<connect from_port="input 1" to_op="Filter Examples" to_port="example set input"/>
<connect from_op="Filter Examples" from_port="example set output" to_op="Cross Validation" to_port="example set"/>
<connect from_op="Cross Validation" from_port="model" to_port="output 1"/>
<connect from_op="Cross Validation" from_port="example set" to_port="output 2"/>
<connect from_op="Cross Validation" from_port="performance 1" to_port="output 3"/>
<portSpacing port="source_input 1" spacing="0"/>
<portSpacing port="source_input 2" spacing="0"/>
<portSpacing port="sink_output 1" spacing="0"/>
<portSpacing port="sink_output 2" spacing="0"/>
<portSpacing port="sink_output 3" spacing="0"/>
<portSpacing port="sink_output 4" spacing="0"/>
</process>
</operator>
<connect from_op="Read Excel" from_port="output" to_op="Select Attributes" to_port="example set input"/>
<connect from_op="Select Attributes" from_port="example set output" to_op="Set Role" to_port="example set input"/>
<connect from_op="Set Role" from_port="example set output" to_op="Numerical to Polynominal" to_port="example set input"/>
<connect from_op="Numerical to Polynominal" from_port="example set output" to_op="Loop Values" to_port="input 1"/>
<connect from_op="Loop Values" from_port="output 1" to_port="result 1"/>
<connect from_op="Loop Values" from_port="output 2" to_port="result 2"/>
<connect from_op="Loop Values" from_port="output 3" to_port="result 3"/>
<portSpacing port="source_input 1" spacing="0"/>
<portSpacing port="sink_result 1" spacing="0"/>
<portSpacing port="sink_result 2" spacing="0"/>
<portSpacing port="sink_result 3" spacing="0"/>
<portSpacing port="sink_result 4" spacing="0"/>
</process>
</operator>
</process>
```

Regards,

Lionel