Join us at FabCon Atlanta from March 16 - 20, 2026, for the ultimate Fabric, Power BI, AI and SQL community-led event. Save $200 with code FABCOMM.
Register now!The Power BI Data Visualization World Championships is back! Get ahead of the game and start preparing now! Learn more
I has a table like
| DATE | CAR | COLOR |
| 01/01/2023 | TESLA | BLACK |
| 01/02/2023 | MUSTANG | BLUE |
I need replicate the rows for all the days of the month.
i want a table like:
| DATE | CAR | COLOR |
| 01/01/2023 | TESLA | BLACK |
| 02/01/2023 | TESLA | BLACK |
| 03/01/2023 | TESLA | BLACK |
| 04/01/2023 | TESLA | BLACK |
...
| DATE | CAR | COLOR |
| 31/01/2023 | TESLA | BLACK |
| 01/02/2023 | MUSTANG | BLUE |
| 02/02/2023 | MUSTANG | BLUE |
| 03/02/2023 | MUSTANG | BLUE |
...
| DATE | CAR | COLOR |
| 26/02/2023 | MUSTANG | BLUE |
| 27/02/2023 | MUSTANG | BLUE |
| 28/02/2023 | MUSTANG | BLUE |
Solved! Go to Solution.
If you do not have duplicate rows with the same DATE then you can skip the Table.Group step. The Grouping is to avoid generating the same list multiple times which can slow down the query due to unnecessary repetition.
let
Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText("i45WMjDUByIjAyNjJR2lENdgH0cg7eTj6OytFKsDkTaCSfuGBoc4+rmDFYS6KsXGAgA=", BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type nullable text) meta [Serialized.Text = true]) in type table [DATE = _t, CAR = _t, COLOR = _t]),
#"Changed Type" = Table.TransformColumnTypes(Source,{{"DATE", type date}, {"CAR", type text}, {"COLOR", type text}}),
#"Grouped Rows" = Table.Group(#"Changed Type", {"DATE"}, {{"Count", each _, type table [DATE=nullable date, CAR=nullable text, COLOR=nullable text]}}),
generate_dates =
Table.TransformColumns(
#"Grouped Rows",
{
"DATE",
each List.Dates(
_,
Duration.TotalDays(Date.EndOfMonth(_) - _) + 1,
#duration(1,0,0,0)
)
}),
#"Expanded DATE" = Table.ExpandListColumn(generate_dates, "DATE"),
#"Expanded Count" = Table.ExpandTableColumn(#"Expanded DATE", "Count", {"CAR", "COLOR"}, {"CAR", "COLOR"})
in
#"Expanded Count"
If you do not have duplicate rows with the same DATE then you can skip the Table.Group step. The Grouping is to avoid generating the same list multiple times which can slow down the query due to unnecessary repetition.
let
Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText("i45WMjDUByIjAyNjJR2lENdgH0cg7eTj6OytFKsDkTaCSfuGBoc4+rmDFYS6KsXGAgA=", BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type nullable text) meta [Serialized.Text = true]) in type table [DATE = _t, CAR = _t, COLOR = _t]),
#"Changed Type" = Table.TransformColumnTypes(Source,{{"DATE", type date}, {"CAR", type text}, {"COLOR", type text}}),
#"Grouped Rows" = Table.Group(#"Changed Type", {"DATE"}, {{"Count", each _, type table [DATE=nullable date, CAR=nullable text, COLOR=nullable text]}}),
generate_dates =
Table.TransformColumns(
#"Grouped Rows",
{
"DATE",
each List.Dates(
_,
Duration.TotalDays(Date.EndOfMonth(_) - _) + 1,
#duration(1,0,0,0)
)
}),
#"Expanded DATE" = Table.ExpandListColumn(generate_dates, "DATE"),
#"Expanded Count" = Table.ExpandTableColumn(#"Expanded DATE", "Count", {"CAR", "COLOR"}, {"CAR", "COLOR"})
in
#"Expanded Count"
Check out the November 2025 Power BI update to learn about new features.
Advance your Data & AI career with 50 days of live learning, contests, hands-on challenges, study groups & certifications and more!
| User | Count |
|---|---|
| 11 | |
| 7 | |
| 5 | |
| 5 | |
| 3 |