The ultimate Microsoft Fabric, Power BI, Azure AI, and SQL learning event: Join us in Stockholm, September 24-27, 2024.
Save €200 with code MSCUST on top of early bird pricing!
Find everything you need to get certified on Fabric—skills challenges, live sessions, exam prep, role guidance, and more. Get started
Good Day,
I have a data like this and those in red font color are what i need.
The Value needed is the value of max date per month.
Amount is cumulative that's why i only wanted to get the last value per month.
I tried it in power query but i did not succeed.
In DAX, i did not succeed.
Also, It will be nice if we will use calculated column for future steps.
Thank you
Date | AMT | Index | Value Needed |
01/09/2019 00:00:00 | 6,564,571.02 | 2319 | 6,564,571.02 |
30/08/2019 00:00:00 | 6,784,825.87 | 2318 | 6,784,825.87 |
29/08/2019 00:00:00 | 6,784,876.25 | 2317 | |
28/08/2019 00:00:00 | 10,646,261.63 | 2316 | |
27/08/2019 00:00:00 | 10,144,474.03 | 2315 | |
25/08/2019 00:00:00 | 9,680,986.07 | 2314 | |
24/08/2019 00:00:00 | 9,351,917.25 | 2313 | |
22/08/2019 00:00:00 | 8,903,386.66 | 2312 | |
21/08/2019 00:00:00 | 8,829,409.80 | 2311 | |
20/08/2019 00:00:00 | 8,504,821.45 | 2310 | |
17/08/2019 00:00:00 | 8,506,139.43 | 2309 | |
15/08/2019 00:00:00 | 8,487,484.41 | 2308 | |
14/08/2019 00:00:00 | 9,475,110.50 | 2307 | |
09/08/2019 00:00:00 | 8,967,067.26 | 2306 | |
08/08/2019 00:00:00 | 8,828,632.28 | 2305 | |
07/08/2019 00:00:00 | 8,584,191.72 | 2304 | |
06/08/2019 00:00:00 | 8,278,699.83 | 2303 | |
04/08/2019 00:00:00 | 7,456,815.72 | 2302 | |
03/08/2019 00:00:00 | 7,410,078.32 | 2301 | |
01/08/2019 00:00:00 | 7,325,497.01 | 2300 | |
31/07/2019 00:00:00 | 7,344,648.91 | 2299 | 7,344,648.91 |
30/07/2019 00:00:00 | 12,384,076.80 | 2298 | |
29/07/2019 00:00:00 | 12,250,113.29 | 2297 | |
28/07/2019 00:00:00 | 11,953,405.05 | 2296 | |
27/07/2019 00:00:00 | 11,922,883.41 | 2295 | |
26/07/2019 00:00:00 | 11,916,823.01 | 2294 | |
25/07/2019 00:00:00 | 11,798,432.56 | 2293 | |
24/07/2019 00:00:00 | 11,756,496.05 | 2292 | |
23/07/2019 00:00:00 | 11,602,221.32 | 2291 | |
22/07/2019 00:00:00 | 11,531,069.08 | 2290 | |
21/07/2019 00:00:00 | 11,373,897.13 | 2289 | |
20/07/2019 00:00:00 | 11,441,593.59 | 2288 | |
18/07/2019 00:00:00 | 10,621,671.32 | 2287 | |
17/07/2019 00:00:00 | 11,395,626.61 | 2286 | |
16/07/2019 00:00:00 | 11,254,372.45 | 2285 | |
15/07/2019 00:00:00 | 10,840,902.51 | 2284 | |
14/07/2019 00:00:00 | 11,445,551.68 | 2283 | |
13/07/2019 00:00:00 | 11,380,865.10 | 2282 | |
11/07/2019 00:00:00 | 11,321,219.69 | 2281 | |
10/07/2019 00:00:00 | 11,191,798.57 | 2280 | |
09/07/2019 00:00:00 | 11,150,184.15 | 2279 | |
08/07/2019 00:00:00 | 10,255,781.71 | 2278 | |
06/07/2019 00:00:00 | 11,796,536.57 | 2277 | |
05/07/2019 00:00:00 | 11,101,169.96 | 2276 | |
04/07/2019 00:00:00 | 11,039,629.96 | 2275 | |
03/07/2019 00:00:00 | 11,013,240.08 | 2274 | |
02/07/2019 00:00:00 | 10,915,945.95 | 2273 | |
01/07/2019 00:00:00 | 10,857,137.88 | 2272 | |
30/06/2019 00:00:00 | 11,102,376.96 | 2271 | 11,102,376.96 |
29/06/2019 00:00:00 | 9,879,163.11 | 2270 | |
28/06/2019 00:00:00 | 9,879,178.10 | 2269 | |
27/06/2019 00:00:00 | 9,822,649.14 | 2268 | |
26/06/2019 00:00:00 | 16,028,568.40 | 2267 | |
25/06/2019 00:00:00 | 15,411,345.26 | 2266 | |
24/06/2019 00:00:00 | 14,814,525.10 | 2265 | |
23/06/2019 00:00:00 | 15,374,982.22 | 2264 | |
22/06/2019 00:00:00 | 15,398,195.10 | 2263 | |
20/06/2019 00:00:00 | 14,987,452.75 | 2262 | |
19/06/2019 00:00:00 | 14,889,967.02 | 2261 | |
18/06/2019 00:00:00 | 14,713,552.74 | 2260 | |
17/06/2019 00:00:00 | 14,352,570.70 | 2259 | |
16/06/2019 00:00:00 | 15,421,314.71 | 2258 | |
15/06/2019 00:00:00 | 15,270,984.00 | 2257 | |
13/06/2019 00:00:00 | 15,335,104.28 | 2256 | |
12/06/2019 00:00:00 | 14,879,602.15 | 2255 | |
11/06/2019 00:00:00 | 14,180,981.89 | 2254 | |
10/06/2019 00:00:00 | 14,016,994.65 | 2253 | |
09/06/2019 00:00:00 | 13,881,245.45 | 2252 | |
08/06/2019 00:00:00 | 13,190,966.75 | 2251 | |
07/06/2019 00:00:00 | 12,986,507.78 | 2250 | |
06/06/2019 00:00:00 | 12,936,747.02 | 2249 | |
02/06/2019 00:00:00 | 12,477,657.82 | 2248 | |
01/06/2019 00:00:00 | 12,477,725.94 | 2247 | |
31/05/2019 00:00:00 | 12,443,463.45 | 2246 | 12,443,463.45 |
30/05/2019 00:00:00 | 12,249,631.13 | 2245 | |
29/05/2019 00:00:00 | 16,926,496.96 | 2244 | |
28/05/2019 00:00:00 | 16,474,498.44 | 2243 | |
27/05/2019 00:00:00 | 16,405,291.78 | 2242 | |
26/05/2019 00:00:00 | 16,405,305.92 | 2241 | |
25/05/2019 00:00:00 | 16,236,689.47 | 2240 | |
24/05/2019 00:00:00 | 16,220,981.51 | 2239 | |
23/05/2019 00:00:00 | 15,942,284.55 | 2238 | |
22/05/2019 00:00:00 | 15,682,658.16 | 2237 | |
21/05/2019 00:00:00 | 15,542,894.55 | 2236 | |
20/05/2019 00:00:00 | 17,283,482.01 | 2235 | |
19/05/2019 00:00:00 | 17,191,384.51 | 2234 | |
18/05/2019 00:00:00 | 17,106,850.27 | 2233 | |
16/05/2019 00:00:00 | 17,002,308.08 | 2232 | |
15/05/2019 00:00:00 | 16,771,051.57 | 2231 | |
14/05/2019 00:00:00 | 16,948,269.26 | 2230 | |
13/05/2019 00:00:00 | 16,299,412.40 | 2229 | |
12/05/2019 00:00:00 | 16,252,739.76 | 2228 | |
11/05/2019 00:00:00 | 15,368,532.15 | 2227 | |
10/05/2019 00:00:00 | 15,368,577.07 | 2226 | |
09/05/2019 00:00:00 | 14,922,381.87 | 2225 | |
08/05/2019 00:00:00 | 14,858,479.23 | 2224 | |
07/05/2019 00:00:00 | 14,333,399.34 | 2223 | |
06/05/2019 00:00:00 | 13,706,829.49 | 2222 | |
05/05/2019 00:00:00 | 13,236,172.79 | 2221 | |
02/05/2019 00:00:00 | 13,073,516.20 | 2220 | |
01/05/2019 00:00:00 | 13,038,987.11 | 2219 | |
30/04/2019 00:00:00 | 12,966,690.09 | 2218 | 12,966,690.09 |
29/04/2019 00:00:00 | 17,070,367.66 | 2217 | |
28/04/2019 00:00:00 | 17,059,598.80 | 2216 | |
27/04/2019 00:00:00 | 17,064,113.16 | 2215 | |
26/04/2019 00:00:00 | 16,808,617.54 | 2214 | |
25/04/2019 00:00:00 | 16,808,672.04 | 2213 | |
24/04/2019 00:00:00 | 16,780,668.21 | 2212 | |
23/04/2019 00:00:00 | 16,742,610.73 | 2211 | |
22/04/2019 00:00:00 | 16,382,162.33 | 2210 | |
21/04/2019 00:00:00 | 15,864,695.34 | 2209 | |
20/04/2019 00:00:00 | 15,904,837.57 | 2208 | |
18/04/2019 00:00:00 | 15,865,711.01 | 2207 | |
17/04/2019 00:00:00 | 17,386,357.16 | 2206 | |
16/04/2019 00:00:00 | 17,218,986.27 | 2205 | |
15/04/2019 00:00:00 | 17,219,000.41 | 2204 | |
14/04/2019 00:00:00 | 17,646,418.81 | 2203 | |
13/04/2019 00:00:00 | 17,333,572.42 | 2202 | |
11/04/2019 00:00:00 | 17,100,053.95 | 2201 | |
10/04/2019 00:00:00 | 17,080,604.75 | 2200 | |
09/04/2019 00:00:00 | 17,210,955.81 | 2199 | |
08/04/2019 00:00:00 | 16,543,353.82 | 2198 | |
07/04/2019 00:00:00 | 16,417,625.02 | 2197 | |
06/04/2019 00:00:00 | 14,970,108.89 | 2196 | |
05/04/2019 00:00:00 | 14,970,123.86 | 2195 | |
04/04/2019 00:00:00 | 14,882,377.11 | 2194 | |
03/04/2019 00:00:00 | 14,679,561.97 | 2193 | |
02/04/2019 00:00:00 | 14,489,547.64 | 2192 | |
01/04/2019 00:00:00 | 14,926,570.78 | 2191 | |
31/03/2019 00:00:00 | 14,340,613.32 | 2190 | 14,340,613.32 |
Solved! Go to Solution.
Hi @mussaenda
I am attaching pbix file with your sample data and formula
It works with sample data
Here is a way of doing it in Power Query
Please see attached file's Query Editor for steps
let Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText("rVpLjuU4DLtKodeGWz//5iqNvv81hn52npXZDeRC1SooxlBIiZL8588v4t80fgvx+CH65/P7K/36+V8/NZVqqTTOJPhnUR4PxuvR3/Tnl9Jv6uH3tW6pS8m9rff18z73aL5PxrX3tZqlrPfN1/4s/B7EZ0rVapLKuepCrwe9xdHZLFmzTBu9HPQSj81ItVMavWba38IOvt3A18JpcPvGXg++xPF7GqRJcf5aF74cfL6B32Uko5E7LXw++Be00FOhSXjOtuNDX3yOsmfj18Q6si3+0Dj4F/jTk/WGP8vGC78f/Cv8sVYSM+Wy4k9Hu3QhN4A/tSWq4OfiDx31UjQ3/Cz+9FRVsvSFf/RLd74vchsPzm3lbjr6pXoDXxrOP8D/zZ+jX7rwfcGdUlPn8j3/0S/pFXzkUGo968Y/+qUL+aEllZJstEyb/0e/CvwWx0f+r9bz+ODL+Nbm16OnNofex4JMaohW3dlOxlHzrMRRdCmoZ6xZxkJ/1+EYOqpMUWTqkj8SA/q7DofRRVLvuvOcDFeH6wV0hgpEN4tkuCpc4uhtIE8jB5W60F0NtgvoULCN+o27q8AaR68E3qA+Lv3KcPVX4uhFGdl/5E/ZAvpRr0TVC3Rtmjpyw8f0iPRTeyWsVU5mOP/QXJaauqu8YTXB1Qpi375x70erfEFNOgreANe2+N6PVvmCmqQYYi/bU0k/WuWwmih1g2MmqGmf/WiVL6jJrKRS0E0sRvajVb6gJoXb77VkXvm9H63yDb6DM8Ij183Io1W+wHe4nJnJcmkL/WiVwrUJ6LM2wcfy4kw7WqULapJS0IXCpS3OtKNVusD3NtCoa30i05xHvlA9mPCHHDlW9WjOIV/gOyl6UDnozh9f4DuxJjF68ntz7jhcPZAFuKRhJY/NGeeNw2qCTktD59Zy32c/Wp1Or4a/KtwenN4Td14I7yeP8Qu97Ge2cb0NkEgzbwG4Qtuv4cPm78RWXaltV/Bh/6qN/JmPAN8Z4xr9GDURmsRSe7Z9emeMSxQd7clMzaDpanGlOmNsUXRD82apyLekVGeMNX52bZZGR/u8bEh1xlguoMMY8zhnd8Y4LLF57tneSm4rPVRXbKOamnHvYw4v9tBWqiu2UUUBvSFxlnn2zff3WCqKrkVSaZTbintxQ6mwmsB32BBle4ptccb4gpqQu/BlLdM+uzPGN/iuBQnY9rhIijPGYb7bJ0uioXpMTnHGmOPo/Bklc+7L/hVnjC+oiZAnx7Bc99ldsQ2rCW1ah3VFjtwtQ3FjqLCaFDkGkan1yQTFDaHCapI5vk+FWm6bM84Yh9UEdK2p2TfPmDPGYUZKstZSLTA5G90Z4zAjF3pDbRori9nR6hzOlSi6aTJ4ms0Zq9tCvZ48fi36MgQ+VeVnlmCuzI4oOoQla4az3aC5Mtvj6IYibujcbH8GV2bbBXRCUp4T8EV/c/OnegddCRTaBHXzpxJHF4ir9pFtdW7mbLFdQJeVkPekQp0p1ij67HzAShTCsuivzhJLHL12GO4CQ78Yqc4Sh6VbUsHZ+zhnd5Y4rNWGqED+MK17mquuzIa12j5zEJ1x3+iuzIa1CnSq6Dwpy2KkuvlTWE0t0ewtqT/9uDpLfEFNraHjL/zMQdRZ4gtqGtYTGsunjVJnicNqglbHQKMmTwsozhKH1QR0GO6mI7d1dnGW+IKatKJ91a+tFGeJw2ra6K3tGwoibv4UVpN99jo6TetGd/OnsJpguEtH9QNnVtUWN38KVz60UapoYUfWVVfFWeKwVjW1mQkEtWnZeXGWOKxV/VQ+bmgwN7qzxGG+a6KG9pVrlq0mZ4nDfAe69tncP8MsPlqdTs+ihrvCEwzKtCLz3I56P3mMX+xlSMjoZrW2fX1G/nM1KoxeRiowfnud/J+rUWH0ap918rYI/F7JxtBBfeqpcstliYvfK9kr6KA/bfT3SjaK3tCJ19qzbIK+V7JhdJinypTbSmr8XslG0RXGj6tk3ejvlWwMvaQOztRRnpRJ75VsFH3My1zaHgNC75Vs/OwlNebHVtJ7JRtVk3bEHp34VhO9V7JRdKSxzzXDbSvpvZKNow9YS3ouZ9B7JRtFnxc8jZHFNvp7JRuOO4p4mcvq1WDSeyUbRWciZGF9VlT0XsmGM/DMM2TPXMtdfqILtUnmiq2UHXce75VsNM8Ug3lCZNbkid1VJwqrafIFvJGyp2bsrjpRWE0wrajajDZqTVrZXXWisJo2uiAydaE7SxxW09xbzPXiY57YXXWisJqQ2xscR+X8CTjQnSUO1yZDUw90g1uyhe4scVir9hnCfbYifaEfrc5ppUabBYNW4ZZ0M3IjvJ/8/fsv", BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type text) meta [Serialized.Text = true]) in type table [Date = _t, #" AMT " = _t, Index = _t, #" Value Needed" = _t]), #"Changed Type" = Table.TransformColumnTypes(Source,{{"Date", type text}, {" AMT ", type number}, {"Index", Int64.Type}, {" Value Needed", type number}}), #"Changed Type1" = Table.TransformColumnTypes(#"Changed Type",{{"Date", type datetime}}), #"Renamed Columns" = Table.RenameColumns(#"Changed Type1",{{" AMT ", "AMT"}}), #"Inserted Year" = Table.AddColumn(#"Renamed Columns", "Year", each Date.Year([Date]), Int64.Type), #"Inserted Month" = Table.AddColumn(#"Inserted Year", "Month", each Date.Month([Date]), Int64.Type), #"Grouped Rows" = Table.Group(#"Inserted Month", {"Year", "Month"}, {{"ALL", each _, type table [Date=datetime, #" AMT "=number, Index=number, #" Value Needed"=number, Year=number, Month=number]}}), #"Added Custom" = Table.AddColumn(#"Grouped Rows", "Custom", each let mydate=List.Max([ALL][Date]) in Table.AddColumn([ALL], "Column",each (if [Date]=mydate then [AMT] else null))), #"Removed Columns" = Table.RemoveColumns(#"Added Custom",{"Year", "Month", "ALL"}), #"Expanded Custom" = Table.ExpandTableColumn(#"Removed Columns", "Custom", {"Date", "AMT", "Index", " Value Needed", "Column"}, {"Date", "AMT", "Index", " Value Needed", "Column"}) in #"Expanded Custom"
Try this column
Column = VAR maxdate = CALCULATE ( MAX ( TableName[Date] ), ALLEXCEPT ( TableName, TableName[Date].[Month], TableName[Date].[Year] ) ) RETURN IF ( [Date] = maxdate, CALCULATE ( SUM ( TableName[ AMT ] ), TableName[Date] = maxdate ) )
Hi @mussaenda
I am attaching pbix file with your sample data and formula
It works with sample data
My fault, i misused one column.
Worked. Thank you!
Also wondering if this can also be done in power query.
Here is a way of doing it in Power Query
Please see attached file's Query Editor for steps
let Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText("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", BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type text) meta [Serialized.Text = true]) in type table [Date = _t, #" AMT " = _t, Index = _t, #" Value Needed" = _t]), #"Changed Type" = Table.TransformColumnTypes(Source,{{"Date", type text}, {" AMT ", type number}, {"Index", Int64.Type}, {" Value Needed", type number}}), #"Changed Type1" = Table.TransformColumnTypes(#"Changed Type",{{"Date", type datetime}}), #"Renamed Columns" = Table.RenameColumns(#"Changed Type1",{{" AMT ", "AMT"}}), #"Inserted Year" = Table.AddColumn(#"Renamed Columns", "Year", each Date.Year([Date]), Int64.Type), #"Inserted Month" = Table.AddColumn(#"Inserted Year", "Month", each Date.Month([Date]), Int64.Type), #"Grouped Rows" = Table.Group(#"Inserted Month", {"Year", "Month"}, {{"ALL", each _, type table [Date=datetime, #" AMT "=number, Index=number, #" Value Needed"=number, Year=number, Month=number]}}), #"Added Custom" = Table.AddColumn(#"Grouped Rows", "Custom", each let mydate=List.Max([ALL][Date]) in Table.AddColumn([ALL], "Column",each (if [Date]=mydate then [AMT] else null))), #"Removed Columns" = Table.RemoveColumns(#"Added Custom",{"Year", "Month", "ALL"}), #"Expanded Custom" = Table.ExpandTableColumn(#"Removed Columns", "Custom", {"Date", "AMT", "Index", " Value Needed", "Column"}, {"Date", "AMT", "Index", " Value Needed", "Column"}) in #"Expanded Custom"
What can I do without your help @Zubair_Muhammad !
Thank you for this! If you will held a training, I will voluntarily participate!
Really, Thank you!!
Join the community in Stockholm for expert Microsoft Fabric learning including a very exciting keynote from Arun Ulag, Corporate Vice President, Azure Data.
Check out the August 2024 Power BI update to learn about new features.
Learn from experts, get hands-on experience, and win awesome prizes.
User | Count |
---|---|
113 | |
80 | |
79 | |
47 | |
39 |
User | Count |
---|---|
149 | |
110 | |
66 | |
64 | |
56 |