Forum Discussion
jhaanand81
4 years agoFrequent Visitor
Subtotal of Negative Values
Hi, Please help me with subtotal of negative value in single row and adding it with a positive value without splitting the row Amount 27733.51 -6201900.18 6177381.24 -77460.65 96...
- 4 years ago
Hi Nathaniel,
Thank you for your reply please find the details and let me know if you are able to understand my query.
Yes need to split the single to get the output.
Document Date Amount in doc. curr. Subtotal Positive Values(Amount in doc. curr.) more than 1 Output 1 Total of Value(Amount in doc. curr.) less than 0 Output 2 Total of Negative Value(-16197615.03+Subtotal of Positive Value) Output 3 31-10-2021 27733.51 -6201900.18 -16169881.52 31-10-2021 -6201900.18 -77460.65 -9992500.28 31-10-2021 6177381.24 -164075.37 -9896376.28 30-09-2021 -77460.65 -164075.37 -9732154.28 23-09-2021 96124 -164075.37 -9567932.28 01-10-2021 -164075.37 -107457.97 -9403710.28 24-09-2021 164222 -127615.96 -9296156.28 01-10-2021 -164075.37 -34430.54 -9168426.28 24-09-2021 164222 -153512.81 -9133961.28 01-10-2021 -164075.37 -163591.81 -8980311.28 24-09-2021 164222 -92810.06 -8816573.28 01-10-2021 -107457.97 -298319.41 -8723680.28 24-09-2021 107554 -184541.08 -8425094.28 01-10-2021 -127615.96 -164510.98 -8240388.28 24-09-2021 127730 -127596.97 -8075730.28 04-10-2021 -34430.54 -216945.13 -7948019.28 27-09-2021 34465 -124299.92 -7730880.28 04-10-2021 -153512.81 -88004.36 -7606469.28 27-09-2021 153650 -125634.73 -7518386.28 04-10-2021 -163591.81 -23637.34 -7392639.28 27-09-2021 163738 -98490.41 -7368978.28 04-10-2021 -92810.06 -64018.92 -7270389.28 27-09-2021 92893 -171185.02 -7206306.28 04-10-2021 -298319.41 -114399.77 -7034968.28 27-09-2021 298586 -99440.14 -6920466.28 04-10-2021 -184541.08 -119750 -6820937.28 27-09-2021 184706 -49491 -6701080.28 04-10-2021 -164510.98 -140522 -6651539.28 27-09-2021 164658 -113436 -6510891.28 04-10-2021 -127596.97 -82038 -6397354.28 27-09-2021 127711 -153218.08 -6315243.28 04-10-2021 -216945.13 -133116.04 -6161888.28 27-09-2021 217139 -49595.68 -6028653.28 04-10-2021 -124299.92 -392974.82 -5979013.28 27-09-2021 124411 -152298.9 -5585687.28 04-10-2021 -88004.36 -132026.02 -5433254.28 27-09-2021 88083 -148817.01 -5301110.28 04-10-2021 -125634.73 -155374.15 -5152160.28 27-09-2021 125747 -99440.14 -4996647.28 04-10-2021 -23637.34 -166459.24 -4897118.28 27-09-2021 23661 -102597.31 -4730510.28 05-10-2021 -98490.41 -138842.92 -4627821.28 28-09-2021 98589 -146134.72 -4488854.28 05-10-2021 -64018.92 -131258.7 -4342573.28 28-09-2021 64083 -130762.14 -4211197.28 05-10-2021 -171185.02 -75018.96 -4080318.28 28-09-2021 171338 -45141.81 -4005232.28 05-10-2021 -114399.77 -158252.58 -3960045.28 28-09-2021 114502 -176340.41 -3801649.28 05-10-2021 -99440.14 -14583.97 -3625151.28 28-09-2021 99529 -32748.22 -3610554.28 12-10-2021 -119750 -3605345.94 -3577773.28 05-10-2021 119857 -3397625.28 12-10-2021 -49491 179987.15 05-10-2021 49541 12-10-2021 -140522 05-10-2021 140648 12-10-2021 -113436 05-10-2021 113537 12-10-2021 -82038 05-10-2021 82111 16-10-2021 -153218.08 08-10-2021 153355 16-10-2021 -133116.04 08-10-2021 133235 16-10-2021 -49595.68 08-10-2021 49640 18-10-2021 -392974.82 11-10-2021 393326 19-10-2021 -152298.9 12-10-2021 152433 19-10-2021 -132026.02 12-10-2021 132144 20-10-2021 -148817.01 13-10-2021 148950 20-10-2021 -155374.15 13-10-2021 155513 25-10-2021 -99440.14 18-10-2021 99529 25-10-2021 -166459.24 18-10-2021 166608 25-10-2021 -102597.31 18-10-2021 102689 25-10-2021 -138842.92 18-10-2021 138967 25-10-2021 -146134.72 18-10-2021 146281 27-10-2021 -131258.7 20-10-2021 131376 27-10-2021 -130762.14 20-10-2021 130879 27-10-2021 -75018.96 20-10-2021 75086 27-10-2021 -45141.81 20-10-2021 45187 29-10-2021 -158252.58 22-10-2021 158396 29-10-2021 -176340.41 22-10-2021 176498 29-10-2021 -14583.97 22-10-2021 14597 29-10-2021 -32748.22 22-10-2021 32781 25-10-2021 180148 31-10-2021 -3605345.94 31-10-2021 3577612.43 31-10-2021 24518.94 25-10-2021 95548 25-10-2021 116893 25-10-2021 182577 26-10-2021 281997 27-10-2021 133627 27-10-2021 120197 27-10-2021 151009 27-10-2021 99529 27-10-2021 2762 27-10-2021 121188 27-10-2021 172152 27-10-2021 161734 27-10-2021 124411 27-10-2021 156379 27-10-2021 43792 28-10-2021 141123 28-10-2021 127334 28-10-2021 183513 28-10-2021 298586 28-10-2021 281997 28-10-2021 130535 28-10-2021 111337 28-10-2021 88731 29-10-2021 225678 30-10-2021 28198 - 4 years ago
Hi jhaanand81 ,
Based on your description, you can try this query:
let Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText("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", BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type nullable text) meta [Serialized.Text = true]) in type table [#"Document Date" = _t, #"Amount in doc. curr." = _t]), #"Changed Type" = Table.TransformColumnTypes(Source,{{"Document Date", type text}, {"Amount in doc. curr.", type number}}), #"Changed Type with Locale" = Table.TransformColumnTypes(#"Changed Type", {{"Document Date", type date}}, "en-GB"), #"Added Index" = Table.AddIndexColumn(#"Changed Type with Locale", "Index", 1, 1, Int64.Type), #"Filtered Rows" = Table.SelectRows(#"Added Index", each [#"Amount in doc. curr."] > 1), #"Added Index1" = Table.AddIndexColumn(#"Filtered Rows", "Index.1", 1, 1, Int64.Type), #"Merged Queries" = Table.NestedJoin(#"Added Index", {"Index"}, #"Added Index1", {"Index.1"}, "Added Index1", JoinKind.LeftOuter), #"Expanded Added Index1" = Table.ExpandTableColumn(#"Merged Queries", "Added Index1", {"Amount in doc. curr."}, {"Added Index1.Amount in doc. curr."}), #"Renamed Columns" = Table.RenameColumns(#"Expanded Added Index1",{{"Added Index1.Amount in doc. curr.", "Output1"}}), #"Filtered Rows1" = Table.SelectRows(#"Renamed Columns", each [#"Amount in doc. curr."] < 0), #"Added Index2" = Table.AddIndexColumn(#"Filtered Rows1", "Index.1", 1, 1, Int64.Type), #"Merged Queries1" = Table.NestedJoin(#"Renamed Columns", {"Index"}, #"Added Index2", {"Index.1"}, "Added Index2", JoinKind.LeftOuter), #"Expanded Added Index2" = Table.ExpandTableColumn(#"Merged Queries1", "Added Index2", {"Amount in doc. curr."}, {"Added Index2.Amount in doc. curr."}), #"Renamed Columns1" = Table.RenameColumns(#"Expanded Added Index2",{{"Added Index2.Amount in doc. curr.", "Ouput2"}}), BufferedValues = List.Buffer(#"Renamed Columns1"[Output1]), CumulativeTotal = Table.AddColumn(#"Renamed Columns1", "Output3", each -16197615.03 + List.Sum(List.FirstN(BufferedValues,[Index])),type number), #"Removed Columns" = Table.RemoveColumns(CumulativeTotal,{"Index"}) in #"Removed Columns"Best Regards,
Community Support Team _ Yingjie Li
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.
v-yingjl
4 years agoCommunity Support
Hi jhaanand81 ,
Based on your description, you can try this query:
let
Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText("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", BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type nullable text) meta [Serialized.Text = true]) in type table [#"Document Date" = _t, #"Amount in doc. curr." = _t]),
#"Changed Type" = Table.TransformColumnTypes(Source,{{"Document Date", type text}, {"Amount in doc. curr.", type number}}),
#"Changed Type with Locale" = Table.TransformColumnTypes(#"Changed Type", {{"Document Date", type date}}, "en-GB"),
#"Added Index" = Table.AddIndexColumn(#"Changed Type with Locale", "Index", 1, 1, Int64.Type),
#"Filtered Rows" = Table.SelectRows(#"Added Index", each [#"Amount in doc. curr."] > 1),
#"Added Index1" = Table.AddIndexColumn(#"Filtered Rows", "Index.1", 1, 1, Int64.Type),
#"Merged Queries" = Table.NestedJoin(#"Added Index", {"Index"}, #"Added Index1", {"Index.1"}, "Added Index1", JoinKind.LeftOuter),
#"Expanded Added Index1" = Table.ExpandTableColumn(#"Merged Queries", "Added Index1", {"Amount in doc. curr."}, {"Added Index1.Amount in doc. curr."}),
#"Renamed Columns" = Table.RenameColumns(#"Expanded Added Index1",{{"Added Index1.Amount in doc. curr.", "Output1"}}),
#"Filtered Rows1" = Table.SelectRows(#"Renamed Columns", each [#"Amount in doc. curr."] < 0),
#"Added Index2" = Table.AddIndexColumn(#"Filtered Rows1", "Index.1", 1, 1, Int64.Type),
#"Merged Queries1" = Table.NestedJoin(#"Renamed Columns", {"Index"}, #"Added Index2", {"Index.1"}, "Added Index2", JoinKind.LeftOuter),
#"Expanded Added Index2" = Table.ExpandTableColumn(#"Merged Queries1", "Added Index2", {"Amount in doc. curr."}, {"Added Index2.Amount in doc. curr."}),
#"Renamed Columns1" = Table.RenameColumns(#"Expanded Added Index2",{{"Added Index2.Amount in doc. curr.", "Ouput2"}}),
BufferedValues = List.Buffer(#"Renamed Columns1"[Output1]),
CumulativeTotal = Table.AddColumn(#"Renamed Columns1", "Output3", each -16197615.03 + List.Sum(List.FirstN(BufferedValues,[Index])),type number),
#"Removed Columns" = Table.RemoveColumns(CumulativeTotal,{"Index"})
in
#"Removed Columns"
Best Regards,
Community Support Team _ Yingjie Li
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.
jhaanand81
4 years agoFrequent Visitor
Hi, Yingil,
Please help with the same output 1,2,3 with the below data set:
| Account | Document Number | Document Date | Amount in doc. curr. |
| IN00001950 | 6500173166 | 08-09-2021 | 11,79,677.00 |
| IN00001950 | 6500173814 | 08-09-2021 | 2,56,564.00 |
| IN00001950 | 6500174906 | 10-09-2021 | 13,35,889.00 |
| IN00001950 | 6500176160 | 12-09-2021 | 11,17,600.00 |
| IN00001950 | 6500176195 | 10-09-2021 | 12,51,291.00 |
| IN00001950 | 6500176772 | 12-09-2021 | 67,517.00 |
| IN00001950 | 6500176784 | 13-09-2021 | 10,01,480.00 |
| IN00001950 | 6500176785 | 13-09-2021 | 5,03,902.00 |
| IN00001950 | 6500176978 | 14-09-2021 | 15,93,720.00 |
| IN00001950 | 6500177902 | 15-09-2021 | 4,45,705.00 |
| IN00001950 | 6500177908 | 15-09-2021 | 11,13,140.00 |
| IN00001950 | 6500178867 | 16-09-2021 | 19,30,226.00 |
| IN00001950 | 6500179503 | 16-09-2021 | 41,517.00 |
| IN00001950 | 6500181239 | 18-09-2021 | 15,77,427.00 |
| IN00001950 | 6500181240 | 18-09-2021 | 14,67,081.00 |
| IN00001950 | 6500181241 | 18-09-2021 | 10,14,993.00 |
| IN00001950 | 6500181242 | 18-09-2021 | 4,21,663.00 |
| IN00001950 | 6500182264 | 20-09-2021 | 14,32,321.00 |
| IN00001950 | 6500182265 | 20-09-2021 | 12,89,969.00 |
| IN00001950 | 6500182337 | 21-09-2021 | 15,35,120.00 |
| IN00001950 | 6500182434 | 21-09-2021 | 9,96,713.00 |
| IN00001950 | 6500182435 | 21-09-2021 | 8,14,891.00 |
| IN00001950 | 6500183138 | 21-09-2021 | 2,31,638.00 |
| IN00001950 | 6500183139 | 21-09-2021 | 43,247.00 |
| IN00001950 | 6500192792 | 04-10-2021 | 7,65,191.00 |
| IN00001950 | 6500192793 | 04-10-2021 | 7,39,727.00 |
| IN00001950 | 6500192817 | 05-10-2021 | 10,75,197.00 |
| IN00001950 | 6500192843 | 05-10-2021 | 16,16,259.00 |
| IN00001950 | 6500193473 | 05-10-2021 | 13,92,459.00 |
| IN00001950 | 6500193702 | 06-10-2021 | 14,88,516.00 |
| IN00001950 | 6500194337 | 06-10-2021 | 17,15,166.00 |
| IN00001950 | 6500194338 | 06-10-2021 | 55,589.00 |
| IN00001950 | 6500195954 | 09-10-2021 | 8,50,445.00 |
| IN00001950 | 6500195955 | 09-10-2021 | 1,60,135.00 |
| IN00001950 | 6500195964 | 09-10-2021 | 5,39,357.00 |
| IN00001950 | 6500196333 | 09-10-2021 | 2,925.00 |
| IN00001950 | 6500196344 | 09-10-2021 | 9,87,324.00 |
| IN00001950 | 6500196484 | 09-10-2021 | 18,55,928.00 |
| IN00001950 | 6500197049 | 10-10-2021 | 15,46,766.00 |
| IN00001950 | 6500198016 | 11-10-2021 | 9,03,227.00 |
| IN00001950 | 6500198243 | 12-10-2021 | 17,39,031.00 |
| IN00001950 | 6500198244 | 12-10-2021 | 13,31,305.00 |
| IN00001950 | 6500198662 | 12-10-2021 | 1,98,500.00 |
| IN00001950 | 6500199274 | 12-10-2021 | 10,802.00 |
| IN00001950 | 6500199529 | 14-10-2021 | 9,82,355.00 |
| IN00001950 | 6500199596 | 14-10-2021 | 4,00,099.00 |
| IN00001950 | 6500200988 | 16-10-2021 | 2,79,669.00 |
| IN00001950 | 6500200993 | 16-10-2021 | 17,26,621.00 |
| IN00001950 | 6500200994 | 16-10-2021 | 10,42,559.00 |
| IN00001950 | 6500201380 | 18-10-2021 | 57,017.00 |
| IN00001950 | 6500204502 | 18-10-2021 | 21,07,730.00 |
| IN00001950 | 6500206547 | 22-10-2021 | 14,14,677.00 |
| IN00001950 | 6500206548 | 22-10-2021 | 1,66,489.00 |
| IN00001950 | 6500206909 | 23-10-2021 | 12,91,987.00 |
| IN00001950 | 6500207318 | 23-10-2021 | 20,12,481.00 |
| IN00001950 | 6500210906 | 27-10-2021 | 16,60,816.00 |
| IN00001950 | 6500211431 | 28-10-2021 | 10,92,960.00 |
| IN00001950 | 6500211432 | 28-10-2021 | 3,70,286.00 |
| IN00001950 | 6500211434 | 28-10-2021 | 2,30,072.00 |
| IN00001950 | 6500211679 | 28-10-2021 | 4,25,172.00 |
| IN00001950 | 6500211696 | 28-10-2021 | 12,36,244.00 |
| IN00001950 | 6500214044 | 01-11-2021 | 10,44,343.00 |
| IN00001950 | 6500214057 | 02-11-2021 | 12,91,322.00 |
| IN00001950 | 6500214088 | 02-11-2021 | 12,93,276.00 |
| IN00001950 | 6500214090 | 02-11-2021 | 16,97,788.00 |
| IN00001950 | 6500214091 | 02-11-2021 | 2,03,648.00 |
| IN00001950 | 6500214327 | 02-11-2021 | 12,81,387.00 |
| IN00001950 | 6500215048 | 04-11-2021 | 5,56,639.00 |
| IN00001950 | 6500215049 | 04-11-2021 | 8,36,231.00 |
| IN00001950 | 6500215052 | 05-11-2021 | 11,97,991.00 |
| IN00001950 | 6500217313 | 08-11-2021 | 13,95,994.00 |
| IN00001950 | 6500217556 | 09-11-2021 | 19,29,327.00 |
| IN00001950 | 6500217557 | 09-11-2021 | 1,70,463.00 |
| IN00001950 | 6500218085 | 09-11-2021 | 9,90,247.00 |
| IN00001950 | 6500218086 | 09-11-2021 | 10,50,344.00 |
| IN00001950 | 6500218087 | 09-11-2021 | 4,81,837.00 |
| IN00001950 | 6500218122 | 09-11-2021 | 1,45,516.00 |
| IN00001950 | 6500218628 | 10-11-2021 | 2,59,479.00 |
| IN00001950 | 6500219317 | 11-11-2021 | 18,07,971.00 |
| IN00001950 | 6500219343 | 11-11-2021 | 13,30,086.00 |
| IN00001950 | 6500219581 | 10-11-2021 | 13,54,193.00 |
| IN00001950 | 6500220267 | 11-11-2021 | 11,48,745.00 |
| IN00001950 | 6500220268 | 11-11-2021 | 4,08,187.00 |
| IN00001950 | 6500221404 | 13-11-2021 | 14,12,799.00 |
| IN00001950 | 6500221405 | 13-11-2021 | 3,58,445.00 |
| IN00001950 | 6500221809 | 13-11-2021 | 12,80,376.00 |
| IN00001950 | 6500222254 | 13-11-2021 | 12,09,988.00 |
| IN00001950 | 6500222255 | 13-11-2021 | 15,45,646.00 |
| IN00001950 | 6500222256 | 13-11-2021 | 4,17,431.00 |
| IN00001950 | 6500222489 | 14-11-2021 | 2,92,452.00 |
| IN00001950 | 6500222524 | 14-11-2021 | 13,16,386.00 |
| IN00001950 | 6500223502 | 15-11-2021 | 15,15,663.00 |
| IN00001950 | 6500223503 | 15-11-2021 | 6,35,743.00 |
| IN00001950 | 6500223685 | 16-11-2021 | 15,73,653.00 |
| IN00001950 | 6500223798 | 16-11-2021 | 17,15,579.00 |
| IN00001950 | 6500224626 | 17-11-2021 | 11,44,859.00 |
| IN00001950 | 6500224644 | 17-11-2021 | 11,13,279.00 |
| IN00001950 | 6500225638 | 18-11-2021 | 14,29,688.00 |
| IN00001950 | 6500225645 | 18-11-2021 | 12,77,593.00 |
| IN00001950 | 6500225646 | 18-11-2021 | 2,05,551.00 |
| IN00001950 | 6500225647 | 18-11-2021 | 17,966.00 |
| IN00001950 | 6500225754 | 18-11-2021 | 14,31,088.00 |
| IN00001950 | 6500227794 | 19-11-2021 | 13,92,590.00 |
| IN00001950 | 6500227800 | 19-11-2021 | 14,49,994.00 |
| IN00001950 | 6500228995 | 21-11-2021 | 8,35,413.00 |
| IN00001950 | 6500228998 | 21-11-2021 | 8,87,775.00 |
| IN00001950 | 6500228999 | 21-11-2021 | 2,22,172.00 |
| IN00001950 | 6500229077 | 20-11-2021 | 17,41,122.00 |
| IN00001950 | 6500230500 | 23-11-2021 | 13,70,348.00 |
| IN00001950 | 6500230516 | 23-11-2021 | 10,36,759.00 |
| IN00001950 | 6500233600 | 25-11-2021 | 7,09,524.00 |
| IN00001950 | 6500233605 | 25-11-2021 | 6,32,756.00 |
| IN00001950 | 6500237963 | 30-11-2021 | 15,42,508.00 |
| IN00001950 | 4300155546 | 01-10-2021 | -14,34,958.00 |
| IN00001950 | 4300155766 | 13-10-2021 | -36,18,261.00 |
| IN00001950 | 4300169870 | 15-11-2021 | -48,81,276.00 |
| IN00001950 | 4300155552 | 11-10-2021 | -30,11,346.00 |
| IN00001950 | 4300155550 | 08-10-2021 | -19,69,982.00 |
| IN00001950 | 4300168942 | 01-11-2021 | -59,37,358.00 |
| IN00001950 | 4300155547 | 04-10-2021 | -37,68,928.00 |
| IN00001950 | 4300169135 | 08-11-2021 | -30,46,125.00 |
| IN00001950 | 1100007842 | 30-09-2021 | -2,18,491.98 |
| IN00001950 | 4300172830 | 19-11-2021 | -33,51,701.00 |
| IN00001950 | 4300165011 | 26-10-2021 | -15,03,495.00 |
| IN00001950 | 4300155548 | 05-10-2021 | -15,03,984.00 |
| IN00001950 | 4300155570 | 12-10-2021 | -27,19,860.00 |
| IN00001950 | 4300169233 | 09-11-2021 | -21,62,810.00 |
| IN00001950 | 4300168946 | 05-11-2021 | -13,81,218.00 |
| IN00001950 | 4300168943 | 02-11-2021 | -41,79,131.00 |
| IN00001950 | 4300165018 | 27-10-2021 | -40,80,272.00 |
| IN00001950 | 4300165003 | 20-10-2021 | -14,65,771.00 |
| IN00001950 | 4300170479 | 17-11-2021 | -16,59,332.00 |
| IN00001950 | 4300165027 | 28-10-2021 | -32,56,360.00 |
| IN00001950 | 4300155549 | 07-10-2021 | -31,49,751.00 |
| IN00001950 | 5,34,24,123.02 | ||
| IN00001950 | 5,34,24,123.02 | ||
| IN00004576 | 6500195981 | 08-10-2021 | 68,449.00 |
| IN00004576 | 6500196762 | 08-10-2021 | 18,139.00 |
| IN00004576 | 6500200548 | 16-10-2021 | 46,610.00 |
| IN00004576 | 6500201158 | 16-10-2021 | 57,550.00 |
| IN00004576 | 6500211473 | 28-10-2021 | 20,056.00 |
| IN00004576 | 6500211867 | 28-10-2021 | 82,108.00 |
| IN00004576 | 6500212098 | 29-10-2021 | 11,211.00 |
| IN00004576 | 6500218903 | 10-11-2021 | 24,141.00 |
| IN00004576 | 6500219371 | 10-11-2021 | 65,128.00 |
| IN00004576 | 6500233091 | 25-11-2021 | 77,779.00 |
| IN00004576 | 6500233092 | 25-11-2021 | 23,946.00 |
| IN00004576 | 4300161155 | 26-10-2021 | -1,00,000.00 |
| IN00004576 | 4300172920 | 20-11-2021 | -1,00,000.00 |
| IN00004576 | 4300155897 | 16-10-2021 | -1,00,000.00 |
| IN00004576 | 4300169422 | 10-11-2021 | -1,00,000.00 |
| IN00004576 | 4300154887 | 07-10-2021 | -1,00,000.00 |
| IN00004576 | 1000082200 | 30-09-2021 | 422.00 |
| IN00004576 | 1100008077 | 30-09-2021 | -7,416.00 |
| IN00004576 | -11,877.00 | ||
| IN00004576 | -11,877.00 | ||
| 5,34,12,246.02 |