Table Row returning blank when Filtered Criteria not met on 2nd table - filter

Question

I have the following two tables:
Historical_Data_Tbl:
DATE
Cloud%
Wind_KM
Solar_Utiliz
Price
01-Jan
0.85
0
0.1
4.5
02-Jan
0.85
0
0.1
4.5
03-Jan
0.95
15
0
10
04-Jan
0.95
15
0
8
05-Jan
0.6
25
0.35
6
06-Jan
0.6
25
0.35
6
07-Jan
0.2
55
0.8
6
08-Jan
0.2
55
0.8
7
09-Jan
0.55
10
0.5
5.5
10-Jan
0.55
10
0.5
5.5
11-Jan
0.28
12
0.6
2
12-Jan
0.28
12
0.6
2
13-Jan
0.1
40
0.9
3
14-Jan
0.1
40
0.9
3
15-Jan
0.33
17
0.7
8
16-Jan
0.01
17
0.95
1
17-Jan
0.01
17
0.95
1
Forecast_Tbl:
Date
Fcst_Cloud
Fcst_Wind
Fcst_Solar
Max_Cloud
Min_Cloud
Max_Wind
Min_Wind
Max_Solar
Min_Solar
1
0.5
12
0.5
0.7
0.3
27
-3
0.75
0.25
2
0.8
10
0.1
1
0.6
25
-5
0.35
-0.15
3
0.15
15
0.8
0.35
-0.05
30
0
1.05
0.55
4
0.75
10
0.2
0.95
0.55
25
-5
0.45
-0.05
5
0.1
99
0.99
0.3
-0.1
114
84
1.24
0.74
6
0.11
35
0.8
0.31
-0.09
50
20
1.05
0.55
CODE BELOW:
let
//Read in Historical table and set data types
Source = Excel.CurrentWorkbook(){[Name="Historical"]}[Content],
Historical = Table.Buffer(Table.TransformColumnTypes(Source,{
{"DATE", type date}, {"Cloud%", type number}, {"Wind_KM", Int64.Type},
{"Solar_Utiliz", type number}, {"Price", type number}})),
//Read in Forecast table anda set data types
Source1 = Excel.CurrentWorkbook(){[Name="Forecast"]}[Content],
Forecast = Table.Buffer(Table.TransformColumnTypes(Source1,{
{"Date", Int64.Type}, {"Fcst_Cloud", type number}, {"Fcst_Wind", Int64.Type},
{"Fcst_Solar", type number}, {"Max_Cloud", type number},
{"Min_Cloud", type number}, {"Max_Wind", Int64.Type}, {"Min_Wind", Int64.Type},
{"Max_Solar", type number}, {"Min_Solar", type number}})),
//Generate list of filtered Historical Table for each row in Forecast Table with aggregations
//Merge aggregations with the associated Forecast row
#"Filtered Historical" = List.Generate(
()=>[t=Table.SelectRows(Historical, (h)=>
h[#"Cloud%"] <= Forecast[Max_Cloud]{0} and h[#"Cloud%"]>= Forecast[Min_Cloud]{0}
and h[Wind_KM] <= Forecast[Max_Wind]{0} and h[Wind_KM] >= Forecast[Min_Wind]{0}
and h[Solar_Utiliz] <= Forecast[Max_Solar]{0} and h[Solar_Utiliz] >= Forecast[Min_Solar]{0}),
idx=0],
each [idx] < Table.RowCount(Forecast),
each [t=Table.SelectRows(Historical, (h)=>
h[#"Cloud%"] <= Forecast[Max_Cloud]{[idx]+1} and h[#"Cloud%"]>= Forecast[Min_Cloud]{[idx]+1}
and h[Wind_KM] <= Forecast[Max_Wind]{[idx]+1} and h[Wind_KM] >= Forecast[Min_Wind]{[idx]+1}
and h[Solar_Utiliz] <= Forecast[Max_Solar]{[idx]+1} and h[Solar_Utiliz] >= Forecast[Min_Solar]{[idx]+1}),
idx=[idx]+1],
each Forecast{[idx]} & Record.FromList(
{List.Count([t][Price]),List.Min([t][Price]), List.Max([t][Price]),
List.Modes([t][Price]){0}, List.Median([t][Price]), List.Average([t][Price])},
{"Count","Min","Max","Mode","Median","Average"})),
#"Converted to Table" = Table.FromList(#"Filtered Historical", Splitter.SplitByNothing(), null, null, ExtraValues.Error),
#"Expanded Column1" = Table.ExpandRecordColumn(#"Converted to Table", "Column1",
{"Date", "Fcst_Cloud", "Fcst_Wind", "Fcst_Solar", "Max_Cloud", "Min_Cloud", "Max_Wind", "Min_Wind", "Max_Solar", "Min_Solar",
"Count", "Min", "Max", "Mode", "Median", "Average"}),
#"Changed Type" = Table.TransformColumnTypes(#"Expanded Column1",{
{"Date", Int64.Type}, {"Fcst_Cloud", Percentage.Type}, {"Fcst_Wind", Int64.Type}, {"Fcst_Solar", type number},
{"Max_Cloud", type number}, {"Min_Cloud", type number}, {"Max_Wind", Int64.Type}, {"Min_Wind", Int64.Type},
{"Max_Solar", type number}, {"Min_Solar", type number}, {"Count", Int64.Type},
{"Min", Currency.Type}, {"Max", Currency.Type}, {"Mode", Currency.Type}, {"Median", Currency.Type}, {"Average", Currency.Type}})
in
#"Changed Type"
And this is the resulting output:
Date
Fcst_Cloud
Fcst_Wind
Fcst_Solar
Max_Cloud
Min_Cloud
Max_Wind
Min_Wind
Max_Solar
Min_Solar
Count
Min
Max
Mode
Median
Average
1
0.5
12
0.5
0.7
0.3
27
0
0.75
0.25
5
5.5
8
6
6
6.2
2
0.8
10
0.1
1
0.6
25
-5
0.35
-0.15
6
4.5
10
4.5
6
6.5
3
0.15
15
0.8
0.35
-0.05
30
0
1.05
0.55
5
1
8
2
2
2.8
4
0.75
10
0.2
0.95
0.55
25
-5
0.45
-0.05
6
4.5
10
4.5
6
6.5
6
0.11
35
0.8
0.31
-0.09
50
20
1.05
0.55
2
3
3
3
3
3
Forecast_Tbl OUTPUT](https://i.stack.imgur.com/8ozB2.png)
The issue is that when one forecast row (for example where Date "5" in output table should be) doesn't have any data points within the filtered range of Historical Data table, it return blank for the entire row.
What I would like it to do is return the original data from the Forecast_Tbl in the first 10 columns, for "Count" column show "0" (When no filtered Criteria are met), and use the previous rows "Average" column value (in this case 6.5) when no filtered Criteria are met. Below is the output I would like for the table to return:
Date
Fcst_Cloud
Fcst_Wind
Fcst_Solar
Max_Cloud
Min_Cloud
Max_Wind
Min_Wind
Max_Solar
Min_Solar
Count
Min
Max
Mode
Median
Average
1
0.5
12
0.5
0.7
0.3
27
0
0.75
0.25
5
5.5
8
6
6
6.2
2
0.8
10
0.1
1
0.6
25
-5
0.35
-0.15
6
4.5
10
4.5
6
6.5
3
0.15
15
0.8
0.35
-0.05
30
0
1.05
0.55
5
1
8
2
2
2.8
4
0.75
10
0.2
0.95
0.55
25
-5
0.45
-0.05
6
4.5
10
4.5
6
6.5
5
0.1
99
0.99
0.3
-0.1
114
84
1.24
0.74
0
6.5
6
0.11
35
0.8
0.31
-0.09
50
20
1.05
0.55
2
3
3
3
3
3
I have tried using conditional if functions but unsuccessful.

Answer 1

How about
....
{"Count","Min","Max","Mode","Median","Average"})),
#"Converted to Table" = Table.FromList(#"Filtered Historical", Splitter.SplitByNothing(), null, null, ExtraValues.Error),
#"Added Index" = Table.AddIndexColumn(#"Converted to Table", "Index", 0, 1, Int64.Type),
#"Added Custom" = Table.AddColumn(#"Added Index", "Column2", each try if Value.Is([Column1], type record ) then [Column1] else null otherwise Record.Combine({Forecast{[Index]}, [Count = 0, Average = #"Added Index"{[Index]-1}[Column1][Average]]})),
#"Expanded Column1" = Table.ExpandRecordColumn(Table.SelectColumns(#"Added Custom",{"Column2"}), "Column2",
{"Date", "Fcst_Cloud", "Fcst_Wind", "Fcst_Solar", "Max_Cloud", "Min_Cloud", "Max_Wind", "Min_Wind", "Max_Solar", "Min_Solar",
"Count", "Min", "Max", "Mode", "Median", "Average"}),
....