![\"Excel](\"https:\/\/docs.microsoft.com\/en-us\/learn\/modules\/clean-data-power-bi\/media\/02-excel-data-multiple-columns-ss.png#lightbox\")
<\/a><\/figure>\n\n\n\nThough the data might initially make sense, it would be difficult to create a total of all sales combined from 2018 and 2019. Your goal would then be to use this data in Power BI with three columns: Month<\/strong>, Year<\/strong>, and SalesAmount<\/strong>.<\/p>\n\n\n\n When you import the data into Power Query, it will look like the following image.<\/p>\n\n\n\n Next, rename the first column to Month<\/strong>. This column was mislabeled because that header in Excel was labeling the 2018 and 2019 columns. Highlight the 2018 and 2019 columns, select the Transform<\/strong> tab in Power Query, and then select Unpivot<\/strong>.<\/p>\n\n\n\n You can rename the Attribute<\/strong> column to Year<\/strong> and the Value<\/strong> column to SalesAmount<\/strong>.<\/p>\n\n\n\n Unpivoting streamlines the process of creating DAX measures on the data later. By completing this process, you have now created a simpler way of slicing the data with the Year<\/strong> and Month<\/strong> columns.<\/p>\n\n\n\n If the data that you are shaping is flat (in other words, it has lot of detail but is not organized or grouped in any way), the lack of structure can complicate your ability to identify patterns in the data.<\/p>\n\n\n\n You can use the Pivot Column<\/strong> feature to convert your flat data into a table that contains an aggregate value for each unique value in a column. For example, you might want to use this feature to summarize data by using different math functions such as Count<\/strong>, Minimum<\/strong>, Maximum<\/strong>, Median<\/strong>, Average<\/strong>, or Sum<\/strong>. <\/p>\n\n\n\n In the SalesTarget example, you can pivot the columns to get the quantity of product subcategories in each product category.<\/p>\n\n\n\n On the Transform<\/strong> tab, select\u202fTransform\u202f>\u202fPivot Columns<\/strong>.<\/p>\n\n\n\n On the Pivot Column<\/strong> window that displays, select a column from the Values Column<\/strong> list, such as Subcategory name<\/strong>. Expand\u202fthe advanced options and select an option from the\u202fAggregate Value Function<\/strong> list, such as Count (All)<\/strong>, and then select OK<\/strong>. <\/p>\n\n\n\n The following image illustrates how the Pivot Column<\/strong> feature changes the way that the data is organized.<\/p>\n\n\n\n Power Query Editor records all steps that you take to shape your data, and the list of steps are shown in the Query Settings<\/strong> pane. If you have made all the required changes, select Close & Apply<\/strong> to close Power Query Editor and apply your changes to your data model. However, before you select Close & Apply<\/strong>, you can take further steps to clean up and transform your data in Power Query Editor. These additional steps are covered later in this module. <\/p>\n\n\n\n Ref: Shape the initial data – Learn | Microsoft Docs<\/a><\/p>\n","protected":false},"excerpt":{"rendered":" Unpivot columns Unpivoting is a useful feature of Power BI. You can use this feature with data from any data source, but you would most often use it when importing data from Excel. The following example shows a sample Excel document with sales data. Though the data might initially make sense, it would be difficult to Read More<\/a><\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_bbp_topic_count":0,"_bbp_reply_count":0,"_bbp_total_topic_count":0,"_bbp_total_reply_count":0,"_bbp_voice_count":0,"_bbp_anonymous_reply_count":0,"_bbp_topic_count_hidden":0,"_bbp_reply_count_hidden":0,"_bbp_forum_subforum_count":0,"om_disable_all_campaigns":false,"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"categories":[10,621],"tags":[999,998,996,997],"class_list":["post-3846","post","type-post","status-publish","format-standard","hentry","category-microsoft","category-power-bi","tag-pivot-columns","tag-unpivot-columns","tag-unpivot-columns-and-pivot-columns","tag-unpivot-columns-and-pivot-columns-power-bi"],"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/SUMMALAI.COM\/index.php?rest_route=\/wp\/v2\/posts\/3846","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/SUMMALAI.COM\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/SUMMALAI.COM\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/SUMMALAI.COM\/index.php?rest_route=\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/SUMMALAI.COM\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=3846"}],"version-history":[{"count":2,"href":"https:\/\/SUMMALAI.COM\/index.php?rest_route=\/wp\/v2\/posts\/3846\/revisions"}],"predecessor-version":[{"id":3854,"href":"https:\/\/SUMMALAI.COM\/index.php?rest_route=\/wp\/v2\/posts\/3846\/revisions\/3854"}],"wp:attachment":[{"href":"https:\/\/SUMMALAI.COM\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=3846"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/SUMMALAI.COM\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=3846"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/SUMMALAI.COM\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=3846"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}<\/a><\/figure>\n\n\n\n<\/a><\/figure>\n\n\n\nPivot columns <\/h2>\n\n\n\n
<\/a><\/figure>\n\n\n\n<\/a><\/figure>\n\n\n\n<\/a><\/figure>\n\n\n\n