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Hello Forum!
I have this table in power query:
And I would a conditional table to read last month with data and copy amount value in the new column, see below the answer
Thank you so much in advance.
Solved! Go to Solution.
let
Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText("i45WMtM3MtY3MjAyVtJRMjQwMFCK1YlWstQ3tIAJmsIEzfWNTJFVwpXCBM3BYrEA", BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type nullable text) meta [Serialized.Text = true]) in type table [Date = _t, Amount = _t]),
#"Changed Type" = Table.TransformColumnTypes(Source,{{"Date", type date}, {"Amount", Int64.Type}}),
add_last_month =
let last_month = Date.StartOfMonth(List.Max(#"Changed Type"[Date]))
in Table.AddColumn(#"Changed Type", "Last Month Cost", each if [Date] < last_month then null else [Amount], type number)
in
add_last_month
Hi @rafavillegas ,
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Regards,
Xiaoxin Sheng
let
Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText("i45WMtM3MtY3MjAyVtJRMjQwMFCK1YlWstQ3tIAJmsIEzfWNTJFVwpXCBM3BYrEA", BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type nullable text) meta [Serialized.Text = true]) in type table [Date = _t, Amount = _t]),
#"Changed Type" = Table.TransformColumnTypes(Source,{{"Date", type date}, {"Amount", Int64.Type}}),
add_last_month =
let last_month = Date.StartOfMonth(List.Max(#"Changed Type"[Date]))
in Table.AddColumn(#"Changed Type", "Last Month Cost", each if [Date] < last_month then null else [Amount], type number)
in
add_last_month
Hi,
Why should the answer be 5000 and 7000? Also, why not create a calculated column formula in DAX? Why are you trying to do this in Power Query?
Because I create a report with the cost to date and with the cost in the last month.
And I need it in Power query instead of DAX, because later this column has relationships with another column of other data, and with Dax doesn't work right.
Relationships are created in the Data model (not in Power Query) so we can create a calculated column formula. I still do not understand how you arived at 5000 and 7000 in column 3.
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