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Krzysiek87
Helper II
Helper II

Single product on document

Hi,
I have a problem with power query that I can't deal with, namely: I have many columns (2 are the most important)
1. Document - containing the document numbers and how many items there are (the document is nothing more than the receipt number, as in MCdonalds),
2. ProductName - here are the names of the products appearing on the document,

Now I would like to check how many documents were Coca Cola and what else was on those receipts. Simply analyzing the sale of a product on the basis of verification of what is associated with a given product on a given document.

 

Unfortunately, I did not find a similar topic here, so I assume the topic:)

1 ACCEPTED SOLUTION
BA_Pete
Super User
Super User

Hi @Krzysiek87 ,

 

I've gone about this a different way from before due to the extra flexibility you need around selecting different items. As you need this to be dynamic, I've done it in DAX instead of Power Query.

I've called your example data 'factSales', which you will see referenced below, which you can replicate with the following PQ code:

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 [DokumentTow = _t, IndeksTow = _t, Nazwa = _t, GrupaAdm = _t, Ilosc = _t, Sprzedaz = _t]),
    repCommaDecimal = Table.ReplaceValue(Source,",",".",Replacer.ReplaceText,{"Sprzedaz"}),
    chgTypes = Table.TransformColumnTypes(repCommaDecimal,{{"DokumentTow", type text}, {"IndeksTow", type text}, {"Nazwa", type text}, {"GrupaAdm", type text}, {"Ilosc", Int64.Type}, {"Sprzedaz", type number}})
in
    chgTypes

 

You can delete the 'repCommaDecimal' step to return to your regional number formats.

 

1) I set up a disconnected product table (nazwaDisc) in Power Query, like this:

let
    Source = Table.Distinct(Table.SelectColumns(factSales, "Nazwa"))
in
    Source

 

2) I sent both tables to the data model, ensuring that is NO relationship between them (PBI might do this automatically when loaded, so make sure to delete if it does).

 

3) I created a basic measure to count items sold:

_noofItemsSold = SUM(factSales[Ilosc])

 

Then I created the following measure that will count all items on all transactions that contain the item selected from the disconnected product table:

_noofItemsSoldWithSelection = 
CALCULATE(
      [_noofItemsSold],
      CALCULATETABLE(
          VALUES(factSales[DokumentTow]),
          INTERSECT(
             ALL(factSales[Nazwa]), 
             VALUES(NazwaDisc[Nazwa])
          )
      )
  )

 

This gives me the following output:

BA_Pete_0-1662556917787.png

 

I've attached my PBIX below so you can have a play with it and see how it's all set up.

 

Pete



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View solution in original post

16 REPLIES 16
BA_Pete
Super User
Super User

Hi @Krzysiek87 ,

 

I've gone about this a different way from before due to the extra flexibility you need around selecting different items. As you need this to be dynamic, I've done it in DAX instead of Power Query.

I've called your example data 'factSales', which you will see referenced below, which you can replicate with the following PQ code:

let
    Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText("zVjNbttGEH6VhYDeVIc/oiwdV+Ra2pLcZXbJMmQaGHYNBEUCJ0iQS25G/Qa5FH2VHGO9V2eWS8qm5J+EbNGDLZrWfJyfb2a+5cuXk4yqZ3Pf9YLJdKIzXs58uIBPSSKmM6ZoJDXRdW7vwocLP958upy8mu7Mj+Hm63dnb98sPbiiYCgTojPF83oKNyLFRcytse/fNXaDIcbNky/OLtHxnK45zVmSMFITLTVLSUjVSgqqKEZAdV4RTlIaUyVFZTFn7l1MJxgf0/PHx9zFPjPVo+sNy3NOSoTkjGRM5xIeoIpYJjfXh4Ex5Yvj6eKOs54BvnztLrAgKVM8pEKC2faKnsItQTP5CyNrqW6uQ2bdc+cH3FtL/B0riDCTKY+kkmWFPvFQ5rlxqi6yNkKvV13PMY6cf/qAHoUbxjRbFWrNFBKjueqyc9x7vP/jts6iTcD8TgJqkiYs5hDMI6no4y0N3ltDdR2ruorY9iqmABgXKqyhHERQInWuGkKQ1eo51kvVLL651jv6e/8RsNvMAQ+ZtWFcsJgJ4kwDkpAVC+uY9gZCMKq57wwy94Y93U6zofR3DcrnS6SfljEpq5DrmIoKOwEaffsn1IfMHAdI1XyFQ2vqDY1bSG/Wc8y1jpnIdJVRqC3VmgIfWcLE+ql8dJd23LtOO+4zWiRUMEVWRX70+MQfASEYjIA3Lz6+MQ1+oqocEug5DmYhkhHFP6El5IrL8t5ENJPufdC6sC64EExrSxQSOI6pzi037unBQRjuYgQ/TEJFzd0APSohBWRN62cCfgH7/cRm1DKk5qno0uL0iNa4Ayv5GIuz5gL8YCcMdpYCxhpPaBLLjYQNlsrQAGEq5/7dTeIj+vnl2fvf56fujrM1ZwksO6KZCDdA4STf0EKbbzydv7D53l0YT1P+gmhszpyYwrP4FgVKClOx3IV6aNCNLSDmzeo5MxyHiLngiFdXAoYuNjnDhZjyVJ4KVuKChKxk3TD2euF6jSB5P+/YoXi6YrDBRMsP39/jx95Mnv1/UOwke/vuAi9AagKvEhmBNvjtk+OYAWxuVs/KSh2FBexcJXhYd5OxLxRGxrMzKcAot1+rkrOQ8IxiG923RHoc8N2WV9gX2yup5fZvSBb9NaEvOnKlha5/TrmMpniJbNuomorJgQ09Wx5YcqbdZ9gNGcs0B/+8B7rcO7BlTZfPEav89iWC6m2/yu3VzXUUy5Le2+smYu+AQ0ZwIV0bgUVOFBVh0UTR01zLg/vyh82Xg8yt5gfz+c48k8n3Pfp4Z4sMjGX9hCe3aqNRK2pFc0pAGShhxEGa3K84evKgU634Cac3BfsDznEyy7gk8weR+pvVDsUPf2Ba1vI0lDqVkA6eG3I+eCRzuvOc2xivEimjCoamycEdW6+fStt3/l7fPVl5YjEGioIRIPzBEN7cVhP/mdA8Z48J0P6AWA4EMAe488+f0BEl9bcv26ujut19MKt8q0nsAQ5DnfVPkk47pExJmyGVwgCEQfWQHjkksYbDuME43iwsjGfoito+B0WPBQYpTxY/3QPTE1lG89UxSwzK84JpGvEkoaSEASxLLpDpEYgHCkrh5i/dAe3Nn8ACmWwLGm7gnPcYSNBnCxbbyPHZwnYYaTsw0zXDbSnYrWbcl+eHxtGoiK1K/vDZpCyHSalsoBUe6vd3Zl8mzDoCYM5yCT4QHW5KlmVMm+35HTzwFmOiOc3rEhMZdBTsALYqElzCNcgGEAVx/23J3tR2hiJ4s250m3VsJYHOZRgT3Cc5XzMjCo4mT1UF/wLkYjL4xVIwGMLubSDjskEpGY71GrY+HMUjGKxHBynZ31fBeDAjHv7GgXIbhfnRrMPmhBYjLUHd2IOPvdmF1X/FGQwFaLcohtJpIv9BMWTo9uof", BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type nullable text) meta [Serialized.Text = true]) in type table [DokumentTow = _t, IndeksTow = _t, Nazwa = _t, GrupaAdm = _t, Ilosc = _t, Sprzedaz = _t]),
    repCommaDecimal = Table.ReplaceValue(Source,",",".",Replacer.ReplaceText,{"Sprzedaz"}),
    chgTypes = Table.TransformColumnTypes(repCommaDecimal,{{"DokumentTow", type text}, {"IndeksTow", type text}, {"Nazwa", type text}, {"GrupaAdm", type text}, {"Ilosc", Int64.Type}, {"Sprzedaz", type number}})
in
    chgTypes

 

You can delete the 'repCommaDecimal' step to return to your regional number formats.

 

1) I set up a disconnected product table (nazwaDisc) in Power Query, like this:

let
    Source = Table.Distinct(Table.SelectColumns(factSales, "Nazwa"))
in
    Source

 

2) I sent both tables to the data model, ensuring that is NO relationship between them (PBI might do this automatically when loaded, so make sure to delete if it does).

 

3) I created a basic measure to count items sold:

_noofItemsSold = SUM(factSales[Ilosc])

 

Then I created the following measure that will count all items on all transactions that contain the item selected from the disconnected product table:

_noofItemsSoldWithSelection = 
CALCULATE(
      [_noofItemsSold],
      CALCULATETABLE(
          VALUES(factSales[DokumentTow]),
          INTERSECT(
             ALL(factSales[Nazwa]), 
             VALUES(NazwaDisc[Nazwa])
          )
      )
  )

 

This gives me the following output:

BA_Pete_0-1662556917787.png

 

I've attached my PBIX below so you can have a play with it and see how it's all set up.

 

Pete



Now accepting Kudos! If my post helped you, why not give it a thumbs-up?

Proud to be a Datanaut!




Thank you kindly, great 🙂

Krzysiek87
Helper II
Helper II

Krzysiek87_0-1662471565133.png

 

 

Ok, so I've made a basic example of the steps to get to a solid basis for your analysis. In the absence of copyable data and a clear indication of the anlysis required, I'm hoping you can take this base and amend it to exactly what you need.

First, copy this and paste it over the default code in Advanced Editor to see the steps in action:

let
    Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText("fZlNkiUhCITv0uteqKDieo7R0fe/xvAmooXhq9fbDERMfkyrvr4+ZByZ++PzQ/60ph/fn/+gYatCcrRCWzsXNi4c/0PS9jrwtbiwwUoadpQFaAp2bMcYF3ZULTuKE7Hhi0HMNovVnkfeQl1+FpogiLnhXg+gRXJMaNWRx72ECwegauXMN1pN1MQxQmKVVT2Vr4B+yJEmMuFrKxaycvyQSNqqOwZ0dxwouQSluBBEQGHVBFZq6LRzEOqoB3qVb63oeWpqxc8Doq1SmKB0IPq6UFgtRU0Iy2SQe294uu+Ivk6T10L6WpWJIZtJ20xanXKv0qm+AroLJ1pUFA3zsnoPXV9r1h5KUFSh1QkgY6NMAroLZaN8p9V+TFCQMwcWno5OO60yEVAqE0OGFEnzbL+HMhPIUJcaakCx8MD9EAOrF0oTgNFfKIhemF+N876tBQptsh8n+tHAfUDZCjteKEIdq1ZOQPnY1VdAKbXjoQrRfBfK7sGEoAodAjkXiiD2wDS5UM5QnYUBpQNhWA1e5QHlwmRqd10oOlGrF0q+Bn2NSo5HwWE1a2G2rZhybdTUBpQWVuGWoBwqysQeOq3KlQSlbKMwAworyJUEJV+KyXShvOPDXEW2N4SIpxahmlSi3eo9FFdArzr6ZcV7e9da9bhA9IWy1cMZwb0h2wFFyTVYBRRWCtURUIqLA2ZjwHhBo4c6LsOAUqiQd0J550Mas/BC+RaF1YXCqkPVBpR3hFV7IEdIjoCcraicC2W5whalQDIIJJn1WZOgNIa0Qq4nat0HlJiANnGI5LRKzt54lHk6sHBjoTOBPHaM2oDSGSFOAwqr0zBXx0DDXCgdCFrOoXqgaZ16lSU3IDGEk1w4yWUqGuZCyYq36MQt6gtB9IXCShCql0ldGFDqR96iG7eo6OIYWjVU7RwwGzIqoFjY8JAShQZwifEeytoEGZrooYByOrjwMLVQon6vgsKFaRJQ1Co1pkOoVUHdq+FFEdB17y+k2mmTO06KZmvY0Z8w9UDa8K7VhjdMQJFtCrelGI8BpQOhrQIKK316UvLY9XtOglKG8JlhDlyZLpBrXG4FCg31FVDeEfP+YFhNSv5p0F/uqxbTMozHgHIQNUPbIAJ9Rxzb+CnFIKPcVw3VqHM2ta8yHW7FHkLzOVTca+94i06+03whH/0YtR5WjT6gOHZDPzqET5sXSnzNyr1DzPaEeBjQvm5Vjx1Q3hFxUUdvSp/JF/6mHN6Uw15eD75wgTVkO6A4Np/NviP5egoV7ike9sNXH96ibkUKcSCHMO/3QbsvDmSDQHIrnhEzx6EHKzBxGnqoQ7m7Fc548DnSX0ggB5+7ExRVeCAo3QpQY7YbPpL4mGBcaD5nFb2tGFa+8MEXRq3+AuUzou75bN74w5KgeP0q+Aoo7Qjl7lYsAHzrcKtaTAEl95iFDjFD+GC8FNdcQJFHqg5vbRQm36Jr4QIzvgI2n5RONN3jyvRQme1eM+Q7kgneHUaiJ1M7kdq18AXJHiZ5Q2rdiqxSpS3w5fc2rnLDHxajNnGolpz7QvRKUdM5ajseLO4Lqe2/QEljojsCSu6hAU7rlejTrIZ6Otwf1pdDHDDQAB4XhYjUmjCobX+m1Twm6C48nQe60I+VL6xtlaBsNWg1aKW0UlpNWvFAVHyj1mqCXu6//wI=", BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type nullable text) meta [Serialized.Text = true]) in type table [transaction = _t, prodCode = _t]),
    groupTransaction = Table.Group(Source, {"transaction"}, {{"data", each _, type table [transaction=nullable text, prodCode=nullable text]}}),
    addHasProd = Table.AddColumn(groupTransaction, "hasProd", each List.Contains([data][prodCode], "3C013")),
    filterFalseHasProd = Table.SelectRows(addHasProd, each ([hasProd] = true))
in
    filterFalseHasProd

 

Summary:

1) Source = Start with just the [transaction] and [productCode] columns - this would be your [Dokument] and [ProdName] columns. This isn't necessary, just simpler to see what's going on.

2) groupTransaction = Group the table on [transaction] using an All Rows aggregation so we have a nested table with all the products on each transaction.

3) addHasProd = Add a new column that reads each of the nested tables to see whether the product we want is there. Instead of my " List.Contains([data][prodCode], "3C013") " code, you would use something like " List.Contains([data][ProdName], "Coca Cola").

4) filterFalseHasProd = Filter out any false values in our new column. This leaves us only transactions that contain the product we want.

 

From here, it's up to you where you go depending on what you want to achieve. I would probably expand the [data] column nested tables back out to get each product row back and send to the PBI data model to run measures for analysis etc.

 

Pete



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Thank you kindly, but I can see that I can't handle it because I don't know much about it: ((I thought it would be easier

 

Fair enough. If you can provide an example of your data in a copyable format and give an indication of exactly the metrics you want to produce, I'm happy to do this based on your actual data.

 

To provide example data, the best way would be to filter your data table to the top 100 rows, then copy the entire table:

BA_Pete_0-1662480363716.png

 

Go to the Home tab > Enter Data > paste into there. Then open the Advanced Editor for that query, copy everything in there, and paste into a code window here ( </> button ).

 

Pete



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ok, I'll try tomorrow;)

Krzysiek87
Helper II
Helper II

its not in ROWS but in columns what i wrote up as example

Krzysiek87
Helper II
Helper II

Document

WarehouselocalID

Local

ExecutionDate

Yearmonth

Weekday

Sales

hour

Prodindex

ProdName

ProdGroupName

Quantity

Sales amount

PaymentKind

BA_Pete
Super User
Super User

Hi @Krzysiek87 ,

 

Can you provide an example of what your source columns look like please?

 

Ta,

 

Pete



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Krzysiek87_0-1662489739079.png

Due to the fact that I can not show more data, I have prepared a trial table that you can operate on. My point is to check selected main items, for example "burger" on which "dokument" appears and with what. Of course, there may be more needs to check "burger" and "frytki", or other combinations, the point is that when we check sales in restaurants, we want to know whether the staff recommends something else for sale or rather passive and the guest chooses from the card himself and they just save the orders without creating any sales

Hi @Krzysiek87 ,

 

I understand what you're trying to do here, and the solution actually needs to be approached in a different way in order to give you the flexibility to change the item that you want to focus on each time (e.g. select burger, or cola, or pizza etc.).

Can you copy the example data you've prepared in Excel and paste it directly into a post here so I can copy it straight out please? I'm afraid I don't have the time to manually type all this information into a new table to work on.

 

Thanks,

 

Pete



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Your post has been changed because invalid HTML was found in the message body. The invalid HTML has been removed. Please review the message and submit the message when you are satisfied. 

 

always the same command stupuid website 😞

 

 

 

Try copying and pasting your Excel table into Power Query, like this:

Copy your Excel table, go to the Home tab > Enter Data > paste into there.

Then open the Advanced Editor for that query, copy everything in there, and paste into a code window here ( </> button ).

 

BA_Pete_2-1662533730058.png

 

Pete



Now accepting Kudos! If my post helped you, why not give it a thumbs-up?

Proud to be a Datanaut!




DokumentTowIndeksTowNazwaGrupaAdmIloscSprzedaz

PAR/63125SPIW43PIWO DESPERADOS SZTPIWO126,9
PAR/63127goalk92APEROL SPRITZ,DRINKI133,9
PAR/63115goalk92APEROL SPRITZ,DRINKI133,9
PAR/63117godan3TAGIATELLE Z SOSEM CARBONARAPASTY I MAKARONY141,9
PAR/63105godan3TAGIATELLE Z SOSEM CARBONARAPASTY I MAKARONY141,9
PAR/63123godan3TAGIATELLE Z SOSEM CARBONARAPASTY I MAKARONY141,9
PAR/63117godan4SPAGHETTI W SOSIE PESTO Z RUKOLĄPASTY I MAKARONY287,8
PAR/63122gong18AMERICANO MAŁA_NAPOJE GORĄCE116,9
PAR/63117GO7KREM POMIDOROWY Z RICOTTĄZUPY123,9
PAR/63120gobur2CHEESEBURGER,BURGERY147,9
PAR/63113gobur2CHEESEBURGER,BURGERY147,9
PAR/63108gong16AMERICANO Z MLEKIEM MAŁA_NAPOJE GORĄCE117,9
PAR/63109gol15SKRZYDEŁKA Z KURCZAKA NA OSTR Z SOS BBQPRZEKĄSKI132,9
PAR/63109gol15SKRZYDEŁKA Z KURCZAKA NA OSTR Z SOS BBQPRZEKĄSKI132,9
PAR/63113PI24HEINEKEN 0,5 L BECZKAPIWO125,9
PAR/63113PI24HEINEKEN 0,5 L BECZKAPIWO125,9
PAR/63130PI24HEINEKEN 0,5 L BECZKAPIWO125,9
PAR/63123PI24HEINEKEN 0,5 L BECZKAPIWO125,9
PAR/63127gong18AMERICANO MAŁA_NAPOJE GORĄCE116,9
PAR/63111gozn2SOK WYCISKANY POMARAŃCZA 400 MLSOKI I SHAKE124,9
PAR/63121gong24SYPANA ASSAM MELENGNAPOJE GORĄCE117,9
PAR/63119SPIW10PIWO PAULANER BUT. SZTPIWO126,9
PAR/63119SPIW10PIWO PAULANER BUT. SZTPIWO126,9
PAR/63115SPIW10PIWO PAULANER BUT. SZTPIWO126,9
PAR/63111dskr2FRYTKI 200GDODATKI SKROBIOWE117,9
PAR/63112gop5PIWO GUINNESS BECZKA 500MLPIWO132,9
PAR/63109gop5PIWO GUINNESS BECZKA 500MLPIWO132,9
PAR/63118gop5PIWO GUINNESS BECZKA 500MLPIWO132,9
PAR/63105SNZI159WODA GAZ/NGAZ 0,3L SZTNAPOJE ZIMNE110,9
PAR/63128goalk70GIN BEEFEATER 40MLALKOHOLE MOCNE263,8
PAR/63131bnapc6_1SYPANA ZIELONA SENCHA ALTHAUS_1NAPOJE GORĄCE117,9
PAR/63119godod28MIX SAŁAT DODATEKDODATKI WARZYWNE112,9
PAR/63113godan3TAGIATELLE Z SOSEM CARBONARAPASTY I MAKARONY141,9
PAR/63106goba15PANINI Z SZYNKĄ I SEREM MIMO_NEWKANAPKI127,9
PAR/63125gop6PIWO GRIMBERGEN BECZKA 330MLPIWO125,9
PAR/63114gop6PIWO GRIMBERGEN BECZKA 330MLPIWO125,9
PAR/63114gop6PIWO GRIMBERGEN BECZKA 330MLPIWO125,9
PAR/63121golod1DESER LODOWY'DESERY/WYR.CUKIERNICZE123,9
PAR/63121golod1DESER LODOWY'DESERY/WYR.CUKIERNICZE123,9
PAR/63110PI56ŻYWIEC IPA 0,3 L BECZKAPIWO121,9
PAR/63131godan2ŁOSOŚ GRAVLAX Z SOSEM MUSZ-MIOD, MUSEM CHRZANPRZEKĄSKI149,9
PAR/63123SNZI149PEPSI 0,2 SZTNAPOJE ZIMNE112,9
PAR/63130goalk63WÓDKA ŻOŁĄDKOWA 40MLALKOHOLE MOCNE122,9
PAR/63123gobur5BURGER FRANCUSKIBURGERY149,9
PAR/63111gobur5BURGER FRANCUSKIBURGERY149,9
PAR/63119gobur5BURGER FRANCUSKIBURGERY149,9
PAR/63105gobur6BURGER POLSKIBURGERY149,9
PAR/63119gobur7BURGER SER KOZIBURGERY149,9
PAR/63107gong4HERBATA CZARNA 400ML_NAPOJE GORĄCE114,9
PAR/63108gong8ESPRESSO DOPPIO 60ML_NAPOJE GORĄCE116,9
PAR/63113godri5GO_COSMOPOLITANDRINKI133,9
PAR/63105goalk1GO_BLOODY MARYDRINKI129,9
PAR/63110PI53ŻYWIEC IPA 0,5 L BECZKAPIWO125,9
PAR/63119dskr2FRYTKI 200GDODATKI SKROBIOWE117,9
PAR/63119dskr2FRYTKI 200GDODATKI SKROBIOWE117,9
PAR/63113dskr2FRYTKI 200GDODATKI SKROBIOWE117,9
PAR/63126gong1LATTE MAŁA_NAPOJE GORĄCE119,9
PAR/63129gong1LATTE MAŁA_NAPOJE GORĄCE119,9
PAR/63117bzu6ROSÓŁ.Z MAKARONEM 300MLZUPY247,8
PAR/63120SNZI153PEPSI MAX 0,2L SZTNAPOJE ZIMNE112,9
PAR/63109SNZI153PEPSI MAX 0,2L SZTNAPOJE ZIMNE112,9
PAR/63115SNZI153PEPSI MAX 0,2L SZTNAPOJE ZIMNE112,9
PAR/63108SNZI210SOK TOMA 200 ML 8%NAPOJE ZIMNE110,9
PAR/63118ZKEL10QUESADILLA WOŁOWINADANIA MIĘSNE149,9
PAR/63115ZKEL20NACHOS WOŁOWINADANIA MIĘSNE159,9
PAR/63127SPIW148PIWO ŻYWIEC PSZENICZNE IPA 0,5 L SZTPIWO124,9
PAR/63108SPIW148PIWO ŻYWIEC PSZENICZNE IPA 0,5 L SZTPIWO124,9
PAR/63118goprz10TATAR WOŁOWY,PRZEKĄSKI143,9
PAR/63124SNZI155TONIC SCHWEPPES 0,2 L SZTNAPOJE ZIMNE112,9
PAR/63128SNZI155TONIC SCHWEPPES 0,2 L SZTNAPOJE ZIMNE112,9
PAR/63107GO10ZUPA CEBULOWA Z GRZANKĄZUPY116,9
PAR/63110GO10ZUPA CEBULOWA Z GRZANKĄZUPY116,9
PAR/63124goalk111WÓDKA STOCK PRESTIGE 40ML.ALKOHOLE MOCNE122,9
PAR/63124goalk111WÓDKA STOCK PRESTIGE 40ML.ALKOHOLE MOCNE122,9
PAR/63128GO7KREM POMIDOROWY Z RICOTTĄZUPY123,9
PAR/63125GO7KREM POMIDOROWY Z RICOTTĄZUPY123,9
PAR/63107goprz9KREWETKI Z KOLENDRĄ.PRZEKĄSKI145,9
PAR/63115goprz9KREWETKI Z KOLENDRĄ.PRZEKĄSKI145,9
PAR/63115SNZI159WODA GAZ/NGAZ 0,3L SZTNAPOJE ZIMNE110,9
PAR/63128SNZI159WODA GAZ/NGAZ 0,3L SZTNAPOJE ZIMNE110,9
PAR/63110gos13SAŁATKA CEZAR_NEWSAŁATKI141,9
PAR/63115gos13SAŁATKA CEZAR_NEWSAŁATKI141,9
PAR/63116gong9ESPRESSO 30ML_NAPOJE GORĄCE112,9

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