Once the step is finished, you should see the following output. Using our derived indices, we can now go ahead with reordering the date components and combining them via Concatenation only when it is the right data as dictated by the earlier If-statement. We then run the function and refer to the component by selecting the index: Index In this example, I decided against using variables to store temporary calculations in M and so we are forced to relate each component to an index number. In some cases, we do not know how many fragments the String will be divided into but since we are familiar with this data we know that it should look like this: Date When the String is split, we need an index to access each section of its division. Should the If statement return true, meaning it found the “/” character in the String, we split the date into its parts (Day/Month/Year). If Text.Contains(,”/”) then … Step 2: Split apart the column components using the function Text.Split(text, delimiter). In this case, we will employ the Text.Contains() function as it is a flexible tool capable of checking the existence of a set of characters in a String without having to know the specifics of its contents.
This works only if the entered data is predictable, and the character consistently appears at that position in the String. To search for this, we can check if a character at a specific index is “/”. It gets terribly busy, if not messy when the process is repeated multiple times on the same table.įor a more manageable solution, we can implement the process using M. Should this solution be implemented using the Power Query Editor drop-down options, the multiple button clicks will clutter the Applied Steps section in the editor. This is the basis of the solution chosen in this blog. One viable alternative is to take multiple steps through the tools available in the Power Query Editor and then split the String (Date) into its components Day/Month/Year based on the presence of the “-“ or “/” delimiters. This is a time-consuming approach that has zero scalability. As such, the solution cannot be automated because it must be custom-tailored to suit each occurrence of the problem. To our collective disappointment, the tool does not pick up any pattern, meaning, we are forced to define every possible representation of each date. Hardcoded transformations based on conditional tests If you have had any experience with data clean-up in Power BI, you might reach for the powerful Columns From Example feature. Sometimes the values in the table are presented as Date values, and other times as Date-Time values, as showcased in Figure 1.įigure 2. In this example, we have a dataset that is based on the last scenario. In all of these scenarios, it is best to use string manipulation in order to create consistency in the data. Or worse still, the data is being entered manually with no way to enforce standards. As a result, the data is inconsistent, and we are unable to figure out the correct values. The data is being aggregated without returning to a generic format first.Īnother example would be a change of format in the interface of your existing data entry program from DD/MM/YYYY to MM/DD/YY and the old data is not updated to match the new. Imagine a situation where you are provided data that is combined from various geographic regions, each with a localized date format. There are many scenarios where you will need to convert data formats. Possible Scenarios: When could we need string manipulation? This tutorial assumes that you have experience cleaning and transforming data using Power Query Editor is Power BI. In this blog, we will look at an example of string manipulation to modify a date format to achieve consistency and learn a few Text Functions in M and a try-otherwise statement.
POWER BI CLEAN TEXT SERIAL
This flexibility makes them the ideal data type for intermediary storage and manipulation of other data types, for example, dates or serial numbers. They differ from other data types as they can represent every other data type.
POWER BI CLEAN TEXT SERIES
Strings are a series of characters used to represent a value or classification of an attribute or label an aspect of an entity.
The terms text and strings would be used interchangeably for the duration of this article. The most dynamic of these will be the Text Data type, which is commonly known as strings in most programming languages. Date, Date/Time, Date/Time/Time-Zone and Time.Here are the different data types in Power BI: When it comes to data types, Power BI provides us with the basics for efficiently storing measurable aspects of our entities and business processes.
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