{"title":"Moving Aggregator","nodeType":"Manipulator","id":"*JKPnK49gCJ_6tVwe","factoryName":"org.knime.timeseries.node.movagg.MovingAggregationNodeFactory","factoryId":"org.knime.timeseries.node.movagg.MovingAggregationNodeFactory","path":["Other Data Types","Time Series","Smoothing"],"owner":"knime","ownerAccountId":"account:team:b5f0848f-496d-4e6a-b869-fa3532248db7","description":"<p>This node calculates aggregation values for a moving window. The aggregation values are displayed in new columns appended at the end of the table.</p>\n                 \n            <p>The columns to aggregate can be either defined by selecting the columns directly, by name based on a search pattern or based on the data type. Input columns are handled in this order and only considered once e.g. columns that are added directly in the &#34;Aggregation&#34; section are ignored even if their name matches a search pattern in the &#34;Pattern Based Aggregation&#34; section or their type matches a defined type in the &#34;Type Based Aggregation&#34; section. The same holds for columns that are added based on a search pattern. They are ignored even if they match a criterion that has been defined in the &#34;Type Based Aggregation&#34; section.</p>\n                \n            <p>In the &#34;Pattern Based Aggregation&#34; section you can assign aggregation methods to columns based on a search pattern. The pattern can be either a string with wildcards or a <a href=\"https://docs.oracle.com/en/java/javase/17/docs/api/java.base/java/util/regex/Pattern.html\" rel=\"ugc nofollow noopener noreferrer\">regular expression</a> . Columns where the name matches the pattern but where the data type is not compatible with the selected aggregation method are ignored. Only columns that have not been selected as aggregation column on the &#34;Aggregation&#34; section are considered.</p>\n                \n            <p>The &#34;Type Based Aggregation&#34; section allows to select an aggregation method for all columns of a certain data type e.g. to compute the mean for all decimal columns (Number (Float)). Only columns that have not been handled by the other tabs e.g. column based and pattern based are considered. The data type list to choose from contains basic types e.g String, Number (Float), etc. and all data types the current input table contains.</p>\n            \n        \n        ","shortDescription":"Adds a column with moving average values.","keywords":[],"deprecated":false,"streamable":false,"tags":["Other Data Types","Time Series","Smoothing"],"icon":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAAAGXRFWHRTb2Z0d2FyZQBBZG9iZSBJbWFnZVJlYWR5ccllPAAAA3BpVFh0WE1MOmNvbS5hZG9iZS54bXAAAAAAADw/eHBhY2tldCBiZWdpbj0i77u/IiBpZD0iVzVNME1wQ2VoaUh6cmVTek5UY3prYzlkIj8+IDx4OnhtcG1ldGEgeG1sbnM6eD0iYWRvYmU6bnM6bWV0YS8iIHg6eG1wdGs9IkFkb2JlIFhNUCBDb3JlIDUuNi1jMDY3IDc5LjE1Nzc0NywgMjAxNS8wMy8zMC0yMzo0MDo0MiAgICAgICAgIj4gPHJkZjpSREYgeG1sbnM6cmRmPSJodHRwOi8vd3d3LnczLm9yZy8xOTk5LzAyLzIyLXJkZi1zeW50YXgtbnMjIj4gPHJkZjpEZXNjcmlwdGlvbiByZGY6YWJvdXQ9IiIgeG1sbnM6eG1wTU09Imh0dHA6Ly9ucy5hZG9iZS5jb20veGFwLzEuMC9tbS8iIHhtbG5zOnN0UmVmPSJodHRwOi8vbnMuYWRvYmUuY29tL3hhcC8xLjAvc1R5cGUvUmVzb3VyY2VSZWYjIiB4bWxuczp4bXA9Imh0dHA6Ly9ucy5hZG9iZS5jb20veGFwLzEuMC8iIHhtcE1NOk9yaWdpbmFsRG9jdW1lbnRJRD0ieG1wLmRpZDowYjM2YWM5Ny01ZWJhLTQwZTctOTE4OS1iYmU4ZDdkMGYyNGUiIHhtcE1NOkRvY3VtZW50SUQ9InhtcC5kaWQ6REIyM0U4OEI4RkEwMTFFNTg1NzhENEEzQzA5OUQ0MUMiIHhtcE1NOkluc3RhbmNlSUQ9InhtcC5paWQ6REIyM0U4OEE4RkEwMTFFNTg1NzhENEEzQzA5OUQ0MUMiIHhtcDpDcmVhdG9yVG9vbD0iQWRvYmUgUGhvdG9zaG9wIENDIDIwMTUgKE1hY2ludG9zaCkiPiA8eG1wTU06RGVyaXZlZEZyb20gc3RSZWY6aW5zdGFuY2VJRD0ieG1wLmlpZDpERTIxNzg1RTQ1QzYxMUU1QUM2QkE3NzQyQjhFM0EyRCIgc3RSZWY6ZG9jdW1lbnRJRD0ieG1wLmRpZDpERTIxNzg1RjQ1QzYxMUU1QUM2QkE3NzQyQjhFM0EyRCIvPiA8L3JkZjpEZXNjcmlwdGlvbj4gPC9yZGY6UkRGPiA8L3g6eG1wbWV0YT4gPD94cGFja2V0IGVuZD0iciI/PticdVYAAAFySURBVHjaYmFAA8/8/BmB1BMGLEBq00ZpdDEmBgoBxQaw4JIAOlcKzWvPiHbB979/QeHAYCUi8rNaS+sjDjuSgDgF3QBZmc2b0jiYmRnmmJq9O/bmDXusvMI3NNvZgHgBEM8F4hnIBgQC8cX////PeP/rl7CHhMQvBzGxH903b/AiqRED4n1AHA/lN4IM4ADiqUC8DogFQaK///1je/vrl2i9ts7Xuffu8bz6+ZMJKMYKlDoFxNZA/AOIo4C4GRSI+4HYAmpiJwsT0xomRsYT//7/Z9787KmQvoDAH14WFrZ3v36BDAeFzQsg9ocaBo4FUGi/BuIYIN710MeXEaj59d2vX4T7bt5kXWRuzvLp928hqAXngdgPOaGBDNCGsr/Ao4aR8R9Q8x9PSUkmXX4B5km3bzHwsbL+AUrZAPE39Gj8gqwZBjY+fcopzs7xfeXjR9/n37/PUK6h+QpdM96EBAILHtznITsl4kp5gy8zAQQYAP3ofUilh2cvAAAAAElFTkSuQmCC","views":[],"inPorts":[{"objectClass":"org.knime.core.node.BufferedDataTable","color":"000000","dataType":"Table","optional":false,"name":"Input column","description":"Table containing time series."}],"outPorts":[{"objectClass":"org.knime.core.node.BufferedDataTable","color":"000000","dataType":"Table","optional":false,"name":"Moving average values","description":"Table with columns holding aggregation values."}],"dynInPorts":[],"dynOutPorts":[],"additionalSiteInformation":{"url":"https://update.knime.com/analytics-platform/5.12","trusted":true,"enabledByDefault":true,"name":"KNIME Analytics Platform 5.12 Update Site","version":"5.12.0"},"dialog":[{"sectionName":"Options","fields":[{"name":"Cumulative computation","description":"Select this option to compute cumulative values e.g. cumulative sum over the whole table. Each result row is computed by aggregating the values from the first row to the current row.","optional":false},{"name":"Window type","description":"Select the direction of the moving window.\n<ul><li><b>Backward</b> : Looks window length rows back from the current point.</li><li><b>Central</b> : Looks half the window length backward from the current point and half forward.</li><li><b>Forward</b> : Looks window length rows forward from the current point.</li></ul>","optional":false},{"name":"Window length","description":"The number of samples to include in the moving window.\n<br />\nMinimum value: 2 samples.\n<br />\nMaximum Value: Time Series length.","optional":false},{"name":"Resolve missing values for incomplete windows","description":"If selected the aggregation values of incomplete windows are computed based on the data rows available so far.","optional":false},{"name":"Manual","description":"Add one or more columns for aggregation from the available columns list. You can add the same column multiple times.\n<ul><li><b>Column</b> : The column to aggregate</li><li><b>Aggregation</b> : The aggregation method to use</li><li><b>Missing values</b> : Missing values are considered during aggregation if the missing option set to &#34;Included&#34;. Some aggregation methods do not support the changing of the missing option such as &#34;Mean&#34;.</li></ul>","optional":false},{"name":"Pattern","description":"<p>The search pattern can either be a string with wildcards or a <a href=\"https://docs.oracle.com/en/java/javase/17/docs/api/java.base/java/util/regex/Pattern.html#sum\" rel=\"ugc nofollow noopener noreferrer\"> regular expression</a> .</p>\nSupported wildcards are <code>*</code> (matches any number of characters) and <code>?</code> (matches one character) e.g. <code>KNI*</code> would match all strings that start with &#34;KNI&#34; such as &#34;KNIME&#34; whereas <code>KNI?</code> would match only strings that start with &#34;KNI&#34; followed by a fourth character.\n<ul><li><b>Search pattern</b> : Wildcard or regular expression pattern</li><li><b>Pattern type</b> : Specifies whether the search pattern is a regular expression or a string with wildcards ( <code>*</code> and <code>?</code> ).</li><li><b>Aggregation</b> : The aggregation method to use</li><li><b>Missing values</b> : Missing values are considered during aggregation if the missing option set to &#34;Included&#34;. Some aggregation methods do not support the changing of the missing option such as &#34;Mean&#34;.</li></ul>","optional":false},{"name":"Type Based Aggregation","description":"Aggregations are applied to all columns of the selected type.\n<ul><li><b>Data Type</b> : Select the data type to apply the aggregation on. You can add the same data type multiple times. The list contains all registered data types the system knows about.</li><li><b>Aggregation</b> : The aggregation method to use</li><li><b>Missing values</b> : Missing values are considered during aggregation if the missing option set to &#34;Included&#34;. Some aggregation methods do not support the changing of the missing option such as &#34;Mean&#34;.</li></ul>","optional":false},{"name":"Type matching","description":"Define how strict the type matching for the aggregations is.\n<ul><li><b>Strict</b> : The type based aggregation method is only applied to columns of the selected type.</li><li><b>Include sub-types</b> : The type based aggregation method is also applied to columns containing sub-types of the selected type. For example <i>Boolean</i> is a sub-type of <i>Number (Integer)</i> , <i>Number (Integer)</i> of <i>Number (Long)</i> , and <i>Number (Long)</i> of <i>Number (Float)</i> .</li></ul>","optional":false},{"name":"Column naming","description":"The name of the resulting aggregation column(s) depends on the selected naming schema.\n<ul><li>Keep original name(s): Keeps the original column names. Note that you can use all aggregation columns only once with this column naming option to prevent duplicate column names.</li><li>Aggregation method (column name): Uses the aggregation method first and appends the column name in brackets</li><li>Column name (aggregation method): Uses the column name first and appends the aggregation method in brackets</li></ul>\nAll aggregation methods get a * appended if the missing value option is not ticked in the aggregation settings in order to distinguish between columns that considered missing values in the aggregation process and columns that do not.","optional":false},{"name":"Remove aggregation columns","description":"If selected the columns used to aggregate are filtered from the output table.","optional":false},{"name":"Remove retained columns","description":"If selected the columns that are not aggregate are filtered from the output table.","optional":false},{"name":"Maximum unique values per group","description":"Defines the maximum number of unique values per group to avoid problems with memory overloading. All groups with more unique values are skipped during the calculation and a missing value is set in the corresponding column, and a warning is displayed.","optional":false},{"name":"Value delimiter","description":"The value delimiter used by aggregation methods such as concatenate.","optional":false}]}],"links":[],"kudos":[],"kudosCount":0,"bundleInformation":{"bundleVersion":"5.12.0.v202604300921","bundleName":"KNIME Time Series Nodes","bundleSymbolicName":"org.knime.timeseries","bundleVendor":"KNIME AG, Zurich, Switzerland","featureSymbolicName":"org.knime.features.timeseries","featureName":"KNIME Timeseries nodes","featureVersion":"5.12.0.v202604300921","featureVendor":"KNIME AG, Zurich, Switzerland","extensionId":"*VOAVcUWXbgClAcQM"},"frequentSuccessors":[{"id":"*AApA5VHd41CVDe7u","factoryName":"org.knime.base.node.meta.looper.LoopEndNodeFactory","probability":0.1200750469043152},{"id":"*2fI5rIsFDCFPHc0R","factoryName":"org.knime.ext.jep.JEPNodeFactory","probability":0.1200750469043152},{"id":"*JKPnK49gCJ_6tVwe","factoryName":"org.knime.timeseries.node.movagg.MovingAggregationNodeFactory","probability":0.0450281425891182},{"id":"*HjhjPWnI5BHBrI1H","factoryName":"org.knime.js.base.node.viz.plotter.line.LinePlotNodeFactory","probability":0.043151969981238276},{"id":"*RurwVi1VODgLDTQP","factoryName":"org.knime.base.node.preproc.columnlag.LagColumnNodeFactory","probability":0.04127579737335835},{"id":"*jd2U-FYTI8jCbQls","factoryName":"org.knime.base.node.preproc.filter.row.RowFilterNodeFactory","probability":0.039399624765478425},{"id":"*PHWv6FsABEjrSc76","factoryName":"org.knime.base.node.preproc.rename.RenameNodeFactory","probability":0.0375234521575985},{"id":"*DOkyMaii62U05xZ1","factoryName":"org.knime.base.node.preproc.filter.column.DataColumnSpecFilterNodeFactory","probability":0.0300187617260788},{"id":"*ZgYyOm1P9VJVBE9e","factoryName":"org.knime.base.node.preproc.joiner.Joiner2NodeFactory","probability":0.028142589118198873},{"id":"*sJQ73svNoG0qOOOP","factoryName":"org.knime.base.node.viz.plotter.line.LinePlotterNodeFactory","probability":0.02626641651031895}]}