As a data modeler, sometimes you might need to write a DAX expression that counts table rows. The table could be a model table or an expression that returns a table.<\/p>\n\n\n\n
Your requirement can be achieved in two ways. You can use the COUNT<\/a> function to count column values, or you can use the COUNTROWS<\/a> function to count table rows. Both functions will achieve the same result, providing that the counted column contains no BLANKs.<\/p>\n\n\n\n The COUNT <\/strong>function counts the number of records that contain a number in a single-column table.<\/p>\n\n\n\n The COUNTA<\/strong> function counts the number of records that aren’t blank<\/em> in a single-column table. This function includes empty<\/a> text (“”) in the count.<\/p>\n\n\n\n The following measure definition presents an example. It calculates the number of OrderDate<\/strong> column values.DAXCopy<\/p>\n\n\n\n Providing that the granularity of the Sales<\/strong> table is one row per sales order, and the OrderDate<\/strong> column does not contain BLANKs, then the measure will return a correct result.<\/p>\n\n\n\n However, the following measure definition is a better solution.DAXCopy<\/p>\n\n\n\n There are three reasons why the second measure definition is better:<\/p>\n\n\n\n As a data modeler, sometimes you might need to write a DAX expression that counts table rows. The table could be a model table or an expression that returns a table. Your requirement can be achieved in two ways. You can use the COUNT function to count column values, or you can use the COUNTROWS function to count table 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":[10,621,625],"tags":[1109,1107,1108],"class_list":["post-4000","post","type-post","status-publish","format-standard","hentry","category-microsoft","category-power-bi","category-sql","tag-count-vs-counta","tag-countrows-vs-count","tag-countrows-vs-count-vs-counta"],"aioseo_notices":[],"aioseo_head":"\n\t\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\tSales Orders =\nCOUNT(Sales[OrderDate])\n<\/code><\/pre>\n\n\n\nSales Orders =\nCOUNTROWS(Sales)\n<\/code><\/pre>\n\n\n\n