Reza Rad is a Microsoft Regional Director, an Author, Trainer, Speaker and Consultant. You need to choose the right transformation for the given requirement. Each of the transformations above can be useful in a specific scenario. There is no right or wrong transformation in the lists above. Here are some of those transformations Īnd there are some transformations that depend on the context, can apply to a column or the whole table. Or we can call them Column-independent transformations. There are also some transformations, which for them, the selected column doesn’t matter. Some of the examples of these transformations are We can call them column-dependent transformations. For this operation, it doesn’t matter what column you have selected, the output will be like this: How the Remove Blank rows works in Power Query and Power BI Column-dependent transformationsĪs you realized, for some of the transformations in Power Query, the selected column is important. This option, will check the value in every single cell of that row, and will remove the row if all of those values are blank. If you want to remove the row only if all values (across all columns) are empty, then Remove Blank Rows is a better option. Remove Empty only considers the value in the selected column to be empty Remove Blank Rows In the example above, the last rows, which was entirely blank, and also the first row, which was not blank in the Column1, but it was blank in the Column2 (which was the column we used the Remove Empty on it), both removed. How Remove Empty works in Power Query and Power BI This means values in other columns is not considered at all, they might have a value or they might be blank. This option, removes the entire row if the value of that row in the selected column is blank.
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Remove Empty is a transformation that you can choose by clicking on the drop down on the column header Remove Empty in Power Query
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To remove the rows with blank values, you can click on the Transform Data and get the Power Query Editor window opened. the very first and the very last row of the table. There are two rows in the data table above that include blank values. Let’s assume that we have a table with the sample data below Sample data table