Get previous year's sales data in custom columns from another Power Query

[devtr]

Two power queries have sales data: Current Year and Previous Years.
The current Year has 2021 data.
Previous Years has 2019 and 2020 data.
Columns: Sales Date, Sales, Units

Current Year:

Sales Date	Sales	Units
08-11-2021	50000	1500
08-12-2021	45000	1200
08-13-2021	40000	1100
08-14-2021	42000	1150
08-15-2021	50000	1700
08-16-2021	52000	1750
08-17-2021	35000	800
08-18-2021	32000	700

Previous Years:

Sales Date	Sales	Units
08-11-2019	30000	700
08-12-2019	35000	800
08-13-2019	25000	750
08-14-2019	27000	700
08-15-2019	26000	650
08-16-2019	20000	550
08-17-2019	18000	500
08-18-2019	20000	700
08-11-2020	22000	750
08-12-2020	28000	900
08-13-2020	23000	800
08-14-2020	22000	700
08-15-2020	18000	600
08-16-2020	19000	650
08-17-2020	20000	800
08-18-2020	18000	800

I want to compare 2021 sales to the previous year's sales.
How do I bring historical data from Previous Years PQ to Current Year PQ with added custom columns for each date?
For Current Year PQ, columns will be Sales Date, Sales, Units, 2019 Sales, 2019 Units, 2020 Sales, 2020 Units.

New PQ for Current Year: (shows 08-17-2021 for example)

Sales Date	Sales	Units	2019 Sales	2019 Units	2020 Sales	2020 Units
08-17-2021	35000	800	18000	500	20000	800

I have very limited knowledge of Power Bi and PQ. This kind of situation can be taken care of in Excel with VLOOKUP and Index Match.
So, for the custom column 2019 Sales in Current Year PQ, what can be done to bring only 2019 sales value for every single date in 2021?
For example, for Aug 17, 2021, I want to bring Aug 17 2019 sales from Previous Years PQ.
Thank you for your help.

 

[JGordon11]

let
    Source = Excel.CurrentWorkbook(){[Name="Table1"]}[Content],
    #"Changed Type" = Table.TransformColumnTypes(Source,{{"Sales Date", type date}, {"Sales", Currency.Type}, {"Units", Int64.Type}}),
    #"Inserted Month" = Table.AddColumn(#"Changed Type", "Month", each Date.Month([Sales Date]), Int64.Type),
    #"Inserted Day" = Table.AddColumn(#"Inserted Month", "Day", each Date.Day([Sales Date]), Int64.Type),
    tblCurrent = Table.CombineColumns(Table.TransformColumnTypes(#"Inserted Day", {{"Month", type text}, {"Day", type text}}, "en-US"),{"Month", "Day"},Combiner.CombineTextByDelimiter("/", QuoteStyle.None),"Merged"),
    tblPrevious = Excel.CurrentWorkbook(){[Name="Table2"]}[Content],
    #"Changed Type1" = Table.TransformColumnTypes(tblPrevious,{{"Sales Date", type date}, {"Sales", Currency.Type}}),
    #"Renamed Columns" = Table.RenameColumns(#"Changed Type1",{{"Sales", "2019 Sales"}, {"Units", "2019 Units"}}),
    #"Inserted Month1" = Table.AddColumn(#"Renamed Columns", "Month", each Date.Month([Sales Date]), Int64.Type),
    #"Inserted Day1" = Table.AddColumn(#"Inserted Month1", "Day", each Date.Day([Sales Date]), Int64.Type),
    #"Merged Columns1" = Table.CombineColumns(Table.TransformColumnTypes(#"Inserted Day1", {{"Month", type text}, {"Day", type text}}, "en-US"),{"Month", "Day"},Combiner.CombineTextByDelimiter("/", QuoteStyle.None),"Merged"),
    #"Filtered Rows" = Table.SelectRows(#"Merged Columns1", each [Sales Date] >= #date(2019, 1, 1) and [Sales Date] <= #date(2019, 12, 31)),
    tbl2020 = Table.SelectRows(#"Merged Columns1", each [Sales Date] >= #date(2020, 1, 1) and [Sales Date] <= #date(2020, 12, 31)),
    #"Renamed Columns1" = Table.RenameColumns(tbl2020,{{"2019 Sales", "2020  Sales"}, {"2019 Units", "2020 Units"}, {"Sales Date", "2020 Sales Date"}}),
    tbl20192020 = Table.Join(#"Filtered Rows", "Merged", #"Renamed Columns1", "Merged"),
    #"Removed Columns" = Table.RemoveColumns(tbl20192020,{"Sales Date", "2020 Sales Date"}),
    tblAll = Table.Join(tblCurrent, "Merged", #"Removed Columns", "Merged"),
    #"Removed Columns1" = Table.RemoveColumns(tblAll,{"Merged"})
in
    #"Removed Columns1"

PQ Tables Merge.xlsm
	A	B	C	D	E	F	G	H	I	J	K	L	M	N	O	P
1	Sales Date	Sales	Units		Sales Date	Sales	Units		Sales Date	Sales	Units	2019 Sales	2019 Units	2020 Sales	2020 Units
2	8/11/2021	50000	1500		8/11/2019	30000	700		8/11/2021	50000	1500	30000	700	22000	750
3	8/12/2021	45000	1200		8/12/2019	35000	800		8/12/2021	45000	1200	35000	800	28000	900
4	8/13/2021	40000	1100		8/13/2019	25000	750		8/13/2021	40000	1100	25000	750	23000	800
5	8/14/2021	42000	1150		8/14/2019	27000	700		8/14/2021	42000	1150	27000	700	22000	700
6	8/15/2021	50000	1700		8/15/2019	26000	650		8/15/2021	50000	1700	26000	650	18000	600
7	8/16/2021	52000	1750		8/16/2019	20000	550		8/16/2021	52000	1750	20000	550	19000	650
8	8/17/2021	35000	800		8/17/2019	18000	500		8/17/2021	35000	800	18000	500	20000	800
9	8/18/2021	32000	700		8/18/2019	20000	700		8/18/2021	32000	700	20000	700	18000	800
10					8/11/2020	22000	750
11					8/12/2020	28000	900
12					8/13/2020	23000	800
13					8/14/2020	22000	700
14					8/15/2020	18000	600
15					8/16/2020	19000	650
16					8/17/2020	20000	800
17					8/18/2020	18000	800
18
Sheet2