There are some cases that we want to add a leading zero to a digit, such as showing 01 instead of 1, 02 instead of 2 and so on. We have two options to do this in Power BI, doing it in Power Query or doing it with DAX.
Adding a Leading Zero in Power Query
The first method is doing it in Power Query using the Text.PadStart() function.
Here is how the syntax of the function:
Text.PadStart(text as nullable text, count as number, optional character as nullable text)
And here is how the function works:
Text.PadStart(input string, the length of the string, an optional character to be added to the beginning of the string util we reach to the string length)
For example, Text.PadStart("12345", 10 , "a") returns aaaaa12345 and Text.PadStart("1", 2 , "0") returns 01.
Let’s create a list of integer values between 1 to 20 with the following expression:
{1..20}
Creating a List of Integer Values Between 1 to 20 In Power Query
Now we convert the list to a table by clicking the To Table button from the Transform tab:
Converting a List to a Table in Power Query
Now we add a new column by clicking the Custom Column from the Add Column tab from the ribbon bar:
Adding a New Custom Column to a Table in Power Query
Now we use the following expression in the Custom Column window to pad the numbers with a leading zero:
In 2020, the world celebrated the new year with many uncertainties. Well, life is full of uncertainties, but, this one was very different. The world was facing a new pandemic that never experienced before. The first COVID19 case in New Zealand was confirmed in February 2020. In March 2020 the entire country went to lockdown for the first time. The world was experiencing a massive threat changing everyone’s lives. I was no different. Every day was starting with bad news. A relative passed away; a friend got the virus; the customers put the projects on hold etc. Nothing was looking normal anymore. You can’t even go to get a proper haircut, because everyone is in lockdown. This is me trying to smile after getting a homemade haircut. I bet many of you have done the same thing.
Soheil’s Homemade Haircut
One day, I checked my email and saw a message from Packt Publishing. They wanted to see if I am interested in writing a book about Power BI. That was a piece of good news after a long time. I always wanted to write a book about Power BI. Indeed, I attempted for the first time in 2016, but I couldn’t manage to get my ducks in a row to grasp the publishers’ attention.
I was not unfamiliar with writing books; indeed, I wrote my first book back in 2006 about Multimedia Applications in Persian. One of my passions in life is listening to music. And CDs were the most accessible music source with high-quality sound. I recall I saved money for some months, and I bought a Discman to listen to the music on the go. But CDs are rather bulky, and you could not have many of them in your pocket. So the next project was to save even more money to buy an MP3 player. But, converting Audio CDs to MP3 without compromising a lot on the sound quality was a real challenge for many people. And, that was my motive to write my first book in Persian to share my little knowledge with everyone.
I wrote some other posts on this topic in the past, you can find them here and here. In the first post I explain how to create “Time” dimension with time bands at minutes granularity. Then one of my customers required the “Time” dimension at seconds granularity which encouraged me to write the second blogpost. In the second blogpost though I didn’t do time bands, so here I am, writing the third post which is a variation of the second post supporting time bands of 5 min, 15 min, 30 min, 45 min and 60 min while the grain of the “Time” dimension is down to second. in this quick post I jump directly to the point and show you how to generate the “Time” dimension in three different ways, using T-SQL in SQL Server, using Power Query (M) and DAX. Here it is then:
Time Dimension at Second Grain with Power Query (M) Supporting Time Bands:
Copy/paste the code below in Query Editor’s Advanced Editor to generate Time dimension in Power Query:
let
Source = Table.FromList({1..86400}, Splitter.SplitByNothing()),
#"Renamed Columns" = Table.RenameColumns(Source,{{"Column1", "ID"}}),
#"Time Column Added" = Table.AddColumn(#"Renamed Columns", "Time", each Time.From(#datetime(1970,1,1,0,0,0) + #duration(0,0,0,[ID])), Time.Type),
#"Hour Added" = Table.AddColumn(#"Time Column Added", "Hour", each Time.Hour([Time]), Int64.Type),
#"Minute Added" = Table.AddColumn(#"Hour Added", "Minute", each Time.Minute([Time]), Int64.Type),
#"5 Min Band Added" = Table.AddColumn(#"Minute Added", "5 Min Band", each Time.From(#datetime(1970,1,1,Time.Hour([Time]),0,0) + #duration(0, 0, (Number.RoundDown(Time.Minute([Time])/5) * 5) + 5, 0)), Time.Type),
#"15 Min Band Added" = Table.AddColumn(#"5 Min Band Added", "15 Min Band", each Time.From(#datetime(1970,1,1,Time.Hour([Time]),0,0) + #duration(0, 0, (Number.RoundDown(Time.Minute([Time])/15) * 15) + 15, 0)), Time.Type),
#"30 Min Band Added" = Table.AddColumn(#"15 Min Band Added", "30 Min Band", each Time.From(#datetime(1970,1,1,Time.Hour([Time]),0,0) + #duration(0, 0, (Number.RoundDown(Time.Minute([Time])/30) * 30) + 30, 0)), Time.Type),
#"45 Min Band Added" = Table.AddColumn(#"30 Min Band Added", "45 Min Band", each Time.From(#datetime(1970,1,1,Time.Hour([Time]),0,0) + #duration(0, 0, (Number.RoundDown(Time.Minute([Time])/45) * 45) + 45, 0)), Time.Type),
#"60 Min Band Added" = Table.AddColumn(#"45 Min Band Added", "60 Min Band", each Time.From(#datetime(1970,1,1,Time.Hour([Time]),0,0) + #duration(0, 0, (Number.RoundDown(Time.Minute([Time])/60) * 60) + 60, 0)), Time.Type),
#"Removed Other Columns" = Table.SelectColumns(#"60 Min Band Added",{"Time", "Hour", "Minute", "5 Min Band", "15 Min Band", "30 Min Band", "45 Min Band", "60 Min Band"})
in
#"Removed Other Columns"
You can now export the data direct from Power BI Desktop using my tool, Power BI Exporter. Read more here.
In some of my old posts, which are the most popular ones, I explained how to Export data Power BI Desktop or Power BI Service data to different destinations like CSV, Excel and SQL Server. In this quick tip I explain a very easy way to export the model data as a whole to either CSV or SQL Server with DAX Studio.
Daniil from XXL BI well explained this method, but I’d rather quickly explain how it works and add some more information.
After release 2.8 of DAX Studio, you can now quickly export the whole model to CSV and SQL Server in one shot.
