![]() We will use the Remove Top Rows function to remove the first two rows of the query, which contain information that is not part of the data set. Power Query Editor will now remove all blank rows from the query. Choose Remove Blank Rows from the drop-down menu.Click the Remove Rows button located on the Home tab.We will use the Remove Blank Rows function to get rid of all the blank rows in the query. Power Query Editor will now launch with the query imported. In this case, Power Query Editor correctly determined that the individual units of data within a row are delimited, or separated, by tabs.Įnsure that the dialog box on your screen is formatted as shown above and click Transform Data. Power Query Editor will try to determine the best options for a given data source. This dialog box, often called the data preview, provides a preview of the data set as it will appear in Power Query Editor. A dialog box with the file name in the title bar will appear. Choose Text/CSV from the drop-down menu.Click the drop-down arrow on the Get Data button, located on the Home tab.If you were to import this report into Power BI in this state, these issues would interfere with your ability to use the data set to create reports.Īt the end of this exercise, we will have cleaned the report and will have a report that looks like the one shown below. There is an incorrect value in the salary column.There is a duplicate row within the data set.The top two rows and the bottom row contain values that are not a part of the data set.The image below shows the base file that we use for this exercise.Īs you can see there are several issues with the report: You can save them where ever works for you, you will just have to use the navigation path to that location rather than the ones included in the blog.ĭownload the following files to complete exercise one and two:Ĭomprehensive Download Let’s Look at the Report To use the navigation paths included in this blog, create a folder called Remove Rows directly in your C: Drive. The report we are using is a sample salary report that has been exported from a source as a text file. In this exercise we will be using five of the row removal types listed above to clean a data set. Remove Alternate Rows: removes and keeps rows within a query using a specified pattern. Remove Duplicates: removes rows that contain identical values within a specified column or column(s) Remove Errors: removes rows that contain errors within a specified column or column(s) Remove Bottom Rows: removes a specified number of rows from the bottom of a report Remove Top Rows: removes a specified number of rows from the top of a report Remove Blank Rows:removes every blank row within a query The Remove Rows function can be used to complete these six different types of row removals: (If you are unfamiliar with Power Query Editor, it may be beneficial to take a moment to learn a bit about it, but it’s not necessary to complete the tutorial we will be covering here.) ![]() We can do that in Power Query Editor using a function called Remove Rows. One of the easiest ways to correct these issues is simply to remove the rows that contain them. It can also occur when the original data contains an incorrect entry. This can happen when reports are exported from the data source in formats that are more difficult to interpret, such as a text file, or when they include elements that aren’t part of the data set, like page numbers or report dates. However, this process isn’t typically sufficient, and there will often be cases where we will have to make manual adjustments to a report after it has been exported from the source. Power BI is a useful tool that can do some automated processing on reports when we import them. Why do we want to remove rows from our reports?
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