Get certified for free when you join Fabric Data Days 2026 and dive into Fabric, Power BI, SQL, AI, and other essential data skills.
Join nowJuly 7 - July 17 | Round 2 of the Power BI Dataviz World Championships. Don't miss your chance! Learn more
I'm sure i'm missing something obvious, but here goes
I have a sharepoint folder with 3 csv files in it, i bring them all into a single table via the folder import.
One of the columns in the table is the filename, e.g. June.csv, July.csv, etc.
The table is formatted something like this
ID, Name, Score, Filename
So in most cases each ID will appear 3 times, once for each of the csv files, e.g
1,A,12,May.csv
1,A,15,June.csv
1,A,15,July.csv
The scores may change from file to file.
For each row of data in the file i would like to create a column that shows the score value for a particular month, i.e. adding a column something like
ID, Name, Score, Filename,May,June,July
So the data in the table would end up as
1,A,12,May.csv,12,15,15
1,A,15,June.csv,12,15,15
1,A,15,July.csv,12,15,15
How would i syntax the column dax to do this ?
@MasonMA has provided the easiest solution.
If you want to maintain your original table format and you do not want to use table joins, here is a solution. It is likely overkill for your solution but it explores table grouping, nested lists, dynamic column renaming, and dynamic column type setting. Cheers.
let
//example data
Source =
Table.FromRows(
Json.Document(
Binary.Decompress(
Binary.FromText(
"i45WMlTSUXIEYkMjIOGbWKmXXFymFKuDJGEKJLxK81JxyeQg9BjBZEzQDINLmKNoiQUA",
BinaryEncoding.Base64
),
Compression.Deflate
)
),
let _t = ((type nullable text) meta [Serialized.Text = true]) in type table [ID = _t, Name = _t, Score = _t, Filename = _t]
),
//type setting of initial data
initial_type_set =
Table.TransformColumnTypes(
Source,
{
{"ID", Int64.Type}, {"Name", type text}, {"Score", Int64.Type}, {"Filename", type text}
}
),
//get distinct list of filenames
fileList =
List.Distinct(initial_type_set[Filename]),
//create a type setting list that sets month columns to Int64 and the filename column to text
typeList =
List.Combine(
{
List.Zip(
{
List.Transform(fileList, each Text.BeforeDelimiter(_, ".csv")),
List.Repeat({Int64.Type}, List.Count(fileList))
}
),
{{"Filename", Text.Type}}
}
),
//group table by ID and Name using all rows as the aggregate
group_rows =
Table.Group(
initial_type_set,
{"ID", "Name"},
{
{"AllRows", each _, type table [ID=nullable number, Name=nullable text, Score=nullable number, Filename=nullable text]}
}
),
//add a column to the nested table that contains list of distinct filenames for the ID Name table
add_filenames =
Table.TransformColumns(
group_rows,
{
{"AllRows", each let names = [Filename] in Table.AddColumn(Table.Pivot(_, List.Distinct(_[Filename]), "Filename", "Score"), "Filename", each names, type list), type table}
}
),
//expand the nested table, dropping the '.csv' from the filename columns
expand_nested =
Table.ExpandTableColumn(
add_filenames,
"AllRows",
List.Combine({fileList, {"Filename"}}),
List.Combine({List.Transform(fileList, each Text.BeforeDelimiter(_, ".csv")), {"Filename"}})
),
//expand the filename list column to new rows
expand_filenames =
Table.ExpandListColumn(
expand_nested,
"Filename"
),
//set the column data types
final_type_set =
Table.TransformColumnTypes(
expand_filenames,
typeList
)
in
final_type_set
Proud to be a Super User! | |
In the power query,
Since the data already contains the filename, you can do this in Power Query instead by Pivot Column.
Use Score as the Values column. (Under Advanced options, choose Don't Aggregate)
Thanks Pivot works perfectly, one question, if i pivot on the date, so in effect my table visual is
Name,Date1,Date2,Date3
Is there an easy was to add a column or measure after date3 that shows if the value in date 1 and 2 has increased, decreased or stayed the same ?
Join us in Barcelona for FabCon and SQLCon, the Fabric, Power BI, SQL, and AI community event. Save €200 with code FABCMTY200.
Check out the July 2026 Power BI update to learn about new features.
Join Data Days 2026: 60 days of free live/on-demand sessions, challenges, study groups, and certification opportunities.