Options

Pivot log data by dates

leviavihayleviavihay Member Posts: 5 Learner I
edited March 2019 in Help
Hi all,
I'm trying to use RM in a certain task in which I have (kind of) log data in the following (abstract) schema:
  • ID | Date | Result
I wish to transform this table to vectors from the following structure:
  • id1: [date1: result1, date2: result2, ... ]
  • id2: [date11: result11, date22: result22, ... ]
[notice that the dates don't necessarily repeat between different ID's] 

Thanks in advanced

Best Answer

  • Options
    lionelderkrikorlionelderkrikor Moderator, RapidMiner Certified Analyst, Member Posts: 1,195 Unicorn
    Solution Accepted
    HI @leviavihay,

    I propose the following "approximative" solution with the association Generate Concatenation, Pivot, Generate Aggregation operators : 

    The process : 

    <?xml version="1.0" encoding="UTF-8"?><process version="9.2.000">
      <context>
        <input/>
        <output/>
        <macros/>
      </context>
      <operator activated="true" class="process" compatibility="9.2.000" 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" breakpoints="after" class="utility:create_exampleset" compatibility="9.2.000" expanded="true" height="68" name="Create ExampleSet" width="90" x="112" y="85">
            <parameter key="generator_type" value="comma separated text"/>
            <parameter key="number_of_examples" value="100"/>
            <parameter key="use_stepsize" value="false"/>
            <list key="function_descriptions"/>
            <parameter key="add_id_attribute" value="false"/>
            <list key="numeric_series_configuration"/>
            <list key="date_series_configuration"/>
            <list key="date_series_configuration (interval)"/>
            <parameter key="date_format" value="yyyy-MM-dd HH:mm:ss"/>
            <parameter key="time_zone" value="SYSTEM"/>
            <parameter key="input_csv_text" value="ID,Date,Result&#10;1,date1,result1&#10;1,date2,result2&#10;2,date11,result11&#10;2,date22,result22&#10;"/>
            <parameter key="column_separator" value=","/>
            <parameter key="parse_all_as_nominal" value="false"/>
            <parameter key="decimal_point_character" value="."/>
            <parameter key="trim_attribute_names" value="true"/>
          </operator>
          <operator activated="true" class="generate_concatenation" compatibility="9.2.000" expanded="true" height="82" name="Generate Concatenation" width="90" x="246" y="85">
            <parameter key="first_attribute" value="Date"/>
            <parameter key="second_attribute" value="Result"/>
            <parameter key="separator" value=":"/>
            <parameter key="trim_values" value="false"/>
          </operator>
          <operator activated="true" class="blending:pivot" compatibility="9.2.000" expanded="true" height="82" name="Pivot" width="90" x="380" y="85">
            <parameter key="group_by_attributes" value="ID"/>
            <parameter key="column_grouping_attribute" value="Date:Result"/>
            <list key="aggregation_attributes">
              <parameter key="Date:Result" value="concatenation"/>
            </list>
            <parameter key="use_default_aggregation" value="false"/>
            <parameter key="default_aggregation_function" value="first"/>
          </operator>
          <operator activated="true" class="generate_aggregation" compatibility="9.2.000" expanded="true" height="82" name="Generate Aggregation" width="90" x="514" y="85">
            <parameter key="attribute_name" value="vector"/>
            <parameter key="attribute_filter_type" value="subset"/>
            <parameter key="attribute" value=""/>
            <parameter key="attributes" value="ID"/>
            <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="true"/>
            <parameter key="include_special_attributes" value="false"/>
            <parameter key="aggregation_function" value="concatenation"/>
            <parameter key="concatenation_separator" value=","/>
            <parameter key="keep_all" value="true"/>
            <parameter key="ignore_missings" value="true"/>
            <parameter key="ignore_missing_attributes" value="false"/>
          </operator>
          <operator activated="true" class="select_attributes" compatibility="9.2.000" expanded="true" height="82" name="Select Attributes" width="90" x="648" y="85">
            <parameter key="attribute_filter_type" value="subset"/>
            <parameter key="attribute" value=""/>
            <parameter key="attributes" value="ID|vector"/>
            <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="Create ExampleSet" from_port="output" to_op="Generate Concatenation" to_port="example set input"/>
          <connect from_op="Generate Concatenation" from_port="example set output" to_op="Pivot" to_port="input"/>
          <connect from_op="Pivot" from_port="output" to_op="Generate Aggregation" to_port="example set input"/>
          <connect from_op="Generate Aggregation" 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>
    
    Hope this helps,

    Regards,

    Lionel





     





Answers

  • Options
    Telcontar120Telcontar120 Moderator, RapidMiner Certified Analyst, RapidMiner Certified Expert, Member Posts: 1,635 Unicorn
    Can you provide actual example datasets that corrspond to your input and desired output?  Simply based on your description, I don't think it is feasible because the attribute either has to be generic (like "Date") or you are going to get a set of attributes for each possible value of Date.  But it is hard to say for sure without a concrete example.
    You should also think about whether you actually need it in the form you are describing.  The original ID/Date/Result format is a pretty standard structure that should be suitable for many ML and data science needs.
    Brian T.
    Lindon Ventures 
    Data Science Consulting from Certified RapidMiner Experts
  • Options
    sgenzersgenzer Administrator, Moderator, Employee, RapidMiner Certified Analyst, Community Manager, Member, University Professor, PM Moderator Posts: 2,959 Community Manager
    yes tricky ETL problem...would want to know more context.

    Scott

  • Options
    sgenzersgenzer Administrator, Moderator, Employee, RapidMiner Certified Analyst, Community Manager, Member, University Professor, PM Moderator Posts: 2,959 Community Manager
    nicely done @lionelderkrikor. I played with this for a few min and could not get the desired result. Your solution works well. :smile:
  • Options
    lionelderkrikorlionelderkrikor Moderator, RapidMiner Certified Analyst, Member Posts: 1,195 Unicorn
    thanks you @sgenzer,

    I started to search a solution with a Python script....before I realized that it was feasible with RapidMiner native operator.... ;)

    Regards,

    Lionel
  • Options
    leviavihayleviavihay Member Posts: 5 Learner I
    Hi @lionelderkrikor
    First - Thank you and sorry for the late reply. Your solution was helpful.
    Second - This solution has one problem (from my task perspective) : it concatenated events based on all seen dates.
    For example, this toy case: 
    • id1, date1, result1
    • id1, date2, result2
    • id2, date3, result3
    will result in:
    • id1: [date1: result1, date2: result2, ?]
    • id2: [?, ?, date3: result3]
    In simple words - the resulted vector's entries will be ALL dates seen in the data set.
    But, it's not a big problem, it's a string so I removed all "?," using regex.

    Thanks!
    Avihay



  • Options
    leviavihayleviavihay Member Posts: 5 Learner I
    Hi all

    I just posted a question regarding the next step of my problem. I posted it in a new thread for easier future search.
    https://community.rapidminer.com/discussion/55259
Sign In or Register to comment.