CSV/ Flat file with column names with no. of months and dates E.g. Benchmark Bloomberg 6 months in year 10/30/2018..
Informatica( IICS) fails to load > 65 char field names, so I loaded it as data -first row. Now I need to do unpivot and do logic based on the “original column Names” i.e. if the month was 6 & date was Oct 30 2018 compare with created date and do X. My best approach is as below. Please suggest a better approach.
1) load column names also as data 2) take out row 1 and store it as 1 row table 3) unpivot the table to make 1 column table and re-pivot it to make column names 4) Apply to the original table in SQL( no issues with > 65 char)
If your fields will always be in the same sequence edit the header names in the source transformation. Configure the source so that data starts on second row. There may be an option to ignore header row values. It should be clear from the UI once you edit the transformation.
Related
I have 2 data sources - Source 1 ( SharePoint List ) & Source 2 ( Cloud Source ). I bring both into Power BI. They each have a key to identify a unique instance of a record.
In Power BI I have been asked to identify the New Inserts / Deletes and Updated Records.
So is there an easy way of doing this?
Table 1
Key Column 1 Column 2 Column 3
Table 2
Key Column 1 Column 2 Column 3
You can use Merge queries transformation in Power Query Editor to do that. Left Anti and Right Anti join kinds will give you the rows that exists only in the first or second data source. Inner will give you the rows that exists in both (based on their key value) and later you can compare the other columns to decide are they modified or not.
Lets assume there are two data sources, as follows:
Source 1
Key
Column 1
Column 2
Column 3
1
initial value
initial value
initial value
2
initial value
initial value
initial value
3
initial value
initial value
initial value
Source 2
Key
Column 1
Column 2
Column 3
1
initial value
initial value
initial value
2
modified value
initial value
initial value
4
initial value
initial value
initial value
1 exists in both sources and is not modified;
2 exists in both sources but is modified (Column 1 has different values);
3 exists only in Source 1;
4 exists only in Source 2.
In Power Query Editor, in Home tab of the ribbon, in Combine group, click on Merge Queries -> Merge Queries as New, select Source 1 as the first source, Source 2 as the second source, set the join kind to be Left Anti and make sure Key columns in both sources are selected:
This will give you the rows, that exists only in Source 1, i.e. only 3 (and remove the columns from Source 2 there, because they are not needed):
Do the same merge again, but swap the sources:
to get the rows, that exists only in Source 2, i.e. 4:
And then do it again, but this time set the join kind to be Inner:
Click on the button in the header of Source 2 column and add all the columns except Key and add a conditional column (Add Column -> General -> Conditional Column) as follows (note, that the screenshot is incorrect - the third comparison should be between Column 3 and Source 2.Column 3):
It will tell you is this row modified (2) or not (1):
If you want you can click the button in the header of the custom column and filter the result to show only the rows, where the value is Modified, which will leave only 2 in the result:
I pulled data into Power BI from a SQL query which returns only the order year in one of the columns. In Power BI I formatted the column as "Data type Date" and "Date time format 2001(yyyy)", but when I pull that column into a table in Power BI, it's clearly calculating 2020 and 2021 as the number of days from 1/1/1900 (like excel) because it shows the year as 1905 for both when inserting this column into a visual, instead of years 2020 and 2021.
How can I format this column as the year 2020 and 2021?
Thank you,
You can convert it in the data source, or you can add a custom column in Power Query with M, or a calculated column in the model with DAX. If your data is not too much, it doesn't really matter where you will do that, but the general recommendation is to do that as close to the data source as you can (i.e. if you can, add it to your query, or if you can't add a calculated column).
The data source option needs a column in your query, which can be added with expression like this (this one uses DATEFROMPARTS T-SQL command, if you are using another database, you will have to change it):
DATEFROMPARTS(ExistingYearOnlyColumn, 1, 1)
Or click Transform data to open Power Query Editor and click Add Column -> Custom Column:
and use #date to create the date:
The last option is to create a calculated column in DAX, by right-clicking on your table and selecting New column:
And use DATE DAX function in an expression like this:
DateColumn = DATE([ExistingYearOnlyColumn], 1, 1)
I'm "bugging" to transform my datas to something usable.
For the moment, a datasource provides me a table where a column contains dates, following by 24 columns representing each hours. In this 24 columns, for each date (each row) I've a total of phone calls.
I want to show the hourly repartition. So, my original datasource is not really usable ans need to transform it with something where there is a column "hour" (a simple index from 0 to 23 or 1 to 24) and a column with the total call for each column from the original column. But I'm a lot confused to do it because I don't have a way to create a relationship. Like this :
Someone have any idea to help me? Thanks in advance
I would unpivot the data source and then create two dimensions (Calendar) and (Time).
I have a table visual with a date column and I have a requirement to highlight the top 2 rows. The data on the table visual is sorted desc by the date column.
I need help to conditional format the background color for the top 2 rows.
I tried searching for a way to do this but no luck.
You can calculate the rank of the rows and use conditional formatting to highlight the top 2 rows. But first, we need to define what "top 2 rows" means. You said it is sorted by date descending, so I will assume that "top 2 rows" means the rows with the 2 biggest dates. I will use a measure, which will respond to filters applied on the data. Then we will highlight the rows with rank 1 and 2 (assuming dates are unique in table's rows).
Make new measure like this:
Measure = RANKX(ALLSELECTED('Table'); CALCULATE(SELECTEDVALUE('Table'[Date])))
Where Table is your table name, and Date is the name of the date column. This will give you a number (1, 2, 3...) where 1 is the row with the biggest date, 2 is the second biggest date, and so on.
Then for every field shown in your table, add the following background color condition (right click each item in the list of fields and select Conditional formatting -> Background color):
Set Format by to be Rules, select your measure in Based on field and ad condition > 0 and <= 2 to set the desired background color. Repeat this for all fields shown.
I have the following table:
I'm trying to create a new column using Dax language:
Column = DISTINCT('Edição'[País])
But I gott this error message:
A table of multiple values was supplied where a single value was expected.
The expected result is:
You have a source table with 21 rows. You want to add a column. In the end you'll still have 21 rows.
The "expected" table has 18 rows. So with only adding a column you will never get there, it's just impossible.
To get the expected output though, you can do this easily: just create a table with just Pais as values and PowerBI will automatically group. See here a (more minimal) example:
PS. If you wanted to add a column -say- with the number of years the country appears in the source data, you should:
choose the matrix visualization
add "Pais" (country) for rows
add e.g. "Ano" (year) for values, and summarize by "Count (Distinct)"