In Google Sheets, I'm trying to query a column and look for a state abbreviation, and if that abbreviation is a match, then "East" if not then "West"
Wanting to return text values in my column based on state abbreviation. We have territory manager split into two domains--East and West. So, trying to easily sort my data by East/West.
Here's what I have:
=IF(M:M={"AL", "CA", "DE","FL","GA","IA","KY","ME","MD","MA","MN","MS","NH","NJ","NY","ND","RI","SD","TN","VT","VA","WV","WI"},"East","West")
But, when I fill down, it just fills down East, and does not seem to actually query M:M
Thoughts?
Not the cleanest code, but this should work:
=ARRAYFORMULA(IF(LEN(A:A), IF((A:A = "foo")+(A:A = "bar") = 1, "WEST", "EAST"), ))
To use IF with an OR in an ARRAYFORMULA, you evaluate the column with 1s and 0s. The A:A = "foo" will evaluate to 1 if foo is in the cell. So if one of your OR criteria is in the cell, the total value in the IF will be 1.
You have a lot of criteria so writing each of them in will take a while ...
E.g. IF( (A:A = "AL") + (A:A = "CA") ... (A:A = "WI") = 1, "East", "West")
Use ISERROR/MATCH():
=IF(ISERROR(MATCH(M:M,{"AL", "CA", "DE","FL","GA","IA","KY","ME","MD","MA","MN","MS","NH","NJ","NY","ND","RI","SD","TN","VT","VA","WV","WI"},0)),"West","East")
Related
I´ve been struggling with this:
My table shows 3 records but when expanding there are like 100 columns. I used this code:
#"Expanded Data" = Table.ExpandTableColumn(#"Source", "Document", List.Union(List.Transform(#"Source"[Document]), each Table.ColumnNames(_))),
but it's not working. How can I expand simultaneously all columns? Also, inside those columns there are even more, for example I expand the first time end then those new columns have more records inside.
What could I do? Thanks in advance!
Try this ExpandAllRecords function - it recursively expands every Record-type column:
https://gist.github.com/Mike-Honey/0a252edf66c3c486b69b
This should work for Records Columns.
let
ExpandIt = (TableToExpand as table, optional ColumnName as text) =>
let
ListAllColumns = Table.ColumnNames(TableToExpand),
ColumnsTotal = Table.ColumnCount(TableToExpand),
CurrentColumnIndex = if (ColumnName = null) then 0 else List.PositionOf(ListAllColumns, ColumnName),
CurrentColumnName = ListAllColumns{CurrentColumnIndex},
CurrentColumnContent = Table.Column(TableToExpand, CurrentColumnName),
IsExpandable = if List.IsEmpty(List.Distinct(List.Select(CurrentColumnContent, each _ is record))) then false else true,
FieldsToExpand = if IsExpandable then Record.FieldNames(List.First(List.Select(CurrentColumnContent, each _ is record))) else {},
ColumnNewNames = List.Transform(FieldsToExpand, each CurrentColumnName &"."& _),
ExpandedTable = if IsExpandable then Table.ExpandRecordColumn(TableToExpand, CurrentColumnName, FieldsToExpand, ColumnNewNames) else TableToExpand,
NextColumnIndex = CurrentColumnIndex+1,
NextColumnName = ListAllColumns{NextColumnIndex},
OutputTable = if NextColumnIndex > ColumnsTotal-1 then ExpandedTable else #fx_ExpandIt(ExpandedTable, NextColumnName)
in
OutputTable
in
ExpandIt
This basically takes Table to Transform as the main argument,and then one by one checks if the Column Record is expandable (if column has "records" in it, it will expand it, otherwise move to next column and checks it again).
Then it returns the Output table once everything is expanded.
This function is calling the function from inside for each iteration.
I have a table of Project:
that I would like to filter by the FIELD, OPERATOR, and VALUE columns contained in the Project Group table:
The Power Query M to apply this filter would be:
let
Source = #"Project",
#"Changed Type" = Table.TransformColumnTypes(Source,{{"Projectid", Int64.Type}}),
#"Filtered Rows" = Table.SelectRows(#"Changed Type", each [Projectid] >= 100000 and [Projectid] <= 500000)
in
#"Filtered Rows"
Results (need to remove the error row):
How do I convert the FIELD, OPERATOR, and VALUE columns into a function that can be used as a condition for the SelectRows function?
If you need to do comparisons, might be best to first change the types of the columns (in both tables) that are being compared. Preferably to type number.
The code below assumes that:
the OPERATOR column of Project Group table can only contain: > or < and that these values should be interpreted as >= and <= respectively.
the column in Project table (that needs to be compared) can change and its name will be in the FIELD column of the Project Group. It's assumed that the name matches exactly. If this is not the case, you might need to standardise things (or at least perform a case-insensitive search) to ensure values can be mapped to column names correctly.
Based on the assumptions above, here's one approach:
let
// Dummy table for example purposes
project = Table.FromColumns({
{0..10},
{5..15}
}, type table [projectId = number, name = number]),
// Dummy table for example purposes
projectGroup = Table.FromColumns({
{"projectId", "projectId"},
{">", "<"},
{5, 7}
}, type table [FIELD = text, OPERATOR = text, VALUE = number]),
// Should take in a row from "Project" table and return a boolean
// representing whether said row matches the criteria contained
// within "Project Group" table.
selectorFunc = (projectRow as record) as logical =>
let
shouldKeepProjectRow = Table.MatchesAllRows(projectGroup, (projectGroupRow as record) =>
let
fieldNameToCheck = projectGroupRow[FIELD],
valueFromProjectRow = Record.Field(projectRow, fieldNameToCheck),
compared = if projectGroupRow[OPERATOR] = ">" then
valueFromProjectRow >= projectGroupRow[VALUE]
else
valueFromProjectRow <= projectGroupRow[VALUE]
in compared
)
in shouldKeepProjectRow,
selectedRows = Table.SelectRows(project, selectorFunc)
in
selectedRows
The main function used is Table.MatchesAllRows (https://learn.microsoft.com/en-us/powerquery-m/table-matchesallrows).
Another approach could potentially be: Expression.Evaluate: https://learn.microsoft.com/en-us/powerquery-m/expression-evaluate. However, I've not used it, so I'm not sure whether there are any "gotchas"/implications to be aware of.
This is driving me nuts. Let's say we want to use a slicer which has two distinct values to choose from a dimension. There is A and B.
Let us also say that my Fact table is connected to this dimension, however it has the same dimension with more options.
My slicer now has A, B and (Blank). No biggie.
Let's now say I want to list out all of the possible calculation outcomes by selecting the slicer in a DAX formula, but in my visual I need all those outcomes to be listed in an IF() branched formula:
I can list out A:
IF(MAX(SlicerDim[Column]) = "A", CALCULATE([Calculation], SlicerDim[Column] = "A")
I can list out B:
IF(MAX(SlicerDim[Column]) = "A", CALCULATE([Calculation], SlicerDim[Column] = "A")
I can list out the (Blank) calculation too:
CALCULATE([Calculation], SlicerDim[Column] = Blank())
And I've managed to get a calculation out of it even when all of the slicer elements are on or off, using:
NOT(ISFILTERED(SlicerDim[Column])), CALCULATE([Calculation], SlicerDim[Column] = "A" || SlicerDim[Column] = "B")
Notice I need this IF() branch to actually return a calculation using A & B values, so now I have returns for when A or B or (Blank) or All or None are selected; BUT NOT when multiple values of A & B are selected!
How do I write out this IF() branch for it to return the same thing, but when both A & B are selected? Since there are only two real options in the slicer - I managed to use MIN() and MAX() get it to work by using their names or Index numbers.
IF((MIN(SlicerDim[Column]) = "A" && MAX(SlicerDim[Column]) = "B") || NOT(ISFILTERED(Paslauga[Paslauga])), CALCULATE([Calculation], SlicerDim[Column] = "A" || SlicerDim[Column] = "B")
BUT - I want a more understandable/robust/reusable formula, so that I could list out many selectable values from the slicer and have it return a calculation for specifically selected slicer values.
Please, help.
I've been searching high and low and there seems to not be an easy way to fix this albeit scraping the IF route and just using a damn slicer for this type of dilemma.
TL;DR:
How do I write an IF() branch calculation using DAX to get an outcome when All/None or non-blank or Specific slicer values are selected?
My best effort:
I am looking to improve the first IF() branch to not have to use MIN/MAX, because I would like to be able to reuse this type of formula if there were more than two real options in the slicer:
IF_branch =
IF((MIN(SlicerDim[Column]) = "A" && MAX(SlicerDim[Column]) = "B" || NOT(ISFILTERED(SlicerDim[Column])), CALCULATE([Calculation], SlicerDim[Column] = "A" || SlicerDim[Column] = "B"),
IF(MAX(SlicerDim[Column]) = "A", CALCULATE([Calculation], SlicerDim[Column] = "A"),
IF(MAX(SlicerDim[Column]) = "B", CALCULATE([Calculation], SlicerDim[Column] = "B"),
CALCULATE([Calculation], SlicerDim[Column] = BLANK()))))
Think what you are looking for is CONTAINS and VALUES
VALUES will give you the distinct current selection in scope.
CONTAINS lets you check if a table contains any row with a set of values.
[]
Formulas:
selected Scenarios = CONCATENATEX(VALUES(DimScenario[ScenarioName]);[ScenarioName];";")
Contains Forecast and Budget? =
IF(
CONTAINS(VALUES(DimScenario[ScenarioName]);[ScenarioName];"Forecast") &&
CONTAINS(VALUES(DimScenario[ScenarioName]);[ScenarioName];"Budget")
;"Yes"
;"No"
)
Suppose I have a table as follows:
TableA =
DATATABLE (
"Year", INTEGER,
"Group", STRING,
"Value", DOUBLE,
{
{ 2015, "A", 2 },
{ 2015, "B", 8 },
{ 2016, "A", 9 },
{ 2016, "B", 3 },
{ 2016, "C", 7 },
{ 2017, "B", 5 },
{ 2018, "B", 6 },
{ 2018, "D", 7 }
}
)
I want a measure that returns the top Group based on its Value that work inside or outside a Year filter context. That is, it can be used in a matrix visual like this (including the Total row):
It's not hard to find the maximal value using DAX:
MaxValue = MAX(TableA[Value])
or
MaxValue = MAXX(TableA, TableA[Value])
But what is the best way to look up the Group that corresponds to that value?
I've tried this:
Top Group = LOOKUPVALUE(TableA[Group],
TableA[Year], MAX(TableA[Year]),
TableA[Value], MAX(TableA[Value]))
However, this doesn't work for the Total row and I'd rather not have to use the Year in the measure if possible (there are likely other columns to worry about in a real scenario).
Note: I am providing a couple solutions in the answers below, but I'd love to see any other approaches as well.
Ideally, it would be nice if there were an extra argument in the MAXX function that would specify which column to return after finding the maximum, much like the MAXIFS Excel function has.
Another way to do this is through the use of the TOPN function.
The TOPN function returns entire row(s) instead of a single value. For example, the code
TOPN(1, TableA, TableA[Value])
returns the top 1 row of TableA ordered by TableA[Value]. The Group value associated with that top Value is in the row, but we need to be able to access it. There are a couple of possibilities.
Use MAXX:
Top Group = MAXX(TOPN(1, TableA, TableA[Value]), TableA[Group])
This finds the maximum Group from the TOPN table in the first argument. (There is only one Group value, but this allows us to covert a table into a single value.)
Use SELECTCOLUMNS:
Top Group = SELECTCOLUMNS(TOPN(1, TableA, TableA[Value]), "Group", TableA[Group])
This function usually returns a table (with the columns that are specified), but in this case, it is a table with a single row and a single column, which means the DAX interprets it as just a regular value.
One way to do this is to store the maximum value and use that as a filter condition.
For example,
Top Group =
VAR MaxValue = MAX(TableA[Value])
RETURN MAXX(FILTER(TableA, TableA[Value] = MaxValue), TableA[Group])
or similarly,
Top Group =
VAR MaxValue = MAX(TableA[Value])
RETURN CALCULATE(MAX(TableA[Group]), TableA[Value] = MaxValue)
If there are multiple groups with the same maximum value the measures above will pick the first one alphabetically. If there are multiple and you want to show all of them, you could use a concatenate iterator function:
Top Group =
VAR MaxValue = MAX(TableA[Value])
RETURN CONCATENATEX(
CALCULATETABLE(
VALUES(TableA[Group]),
TableA[Value] = MaxValue
),
TableA[Group],
", "
)
If you changed the 9 in TableA to an 8, this last measure would return A, B rather than A.
I cannot for the life of me understand the rbind function. I've tried using the examples on here, but I can't figure out what I am doing incorrectly. All I would like to do is add the data from my second data frame under the first.
Does rbind require the columns be the same name or...?
ParticipantA=c("A","B","C","D")
Score1A=c("21","20","21","21")
Score2A=c("32","40","32","31")
Score3A=c("47","50","43","46")
BlockA=data.frame(ParticipantA,Score1A,Score2A,Score3A)
BlockA$Major=c("Computer_Science","Computer_Science","Computer_Science","Computer_Science")
BlockA$Gender=c("Female","Female","Male","Male")
ParticipantB=c("E","F","G","H")
Score1B=c("28","28","21","22")
Score2B=c("30","36","37","32")
Score3B=c("41","49","49","46")
BlockB=data.frame(ParticipantB,Score1B,Score2B,Score3B)
BlockB$Major=c("Medical","Medical","Medical","Medical")
BlockB$Gender=c("Female","Female","Male","Male")
rbind requires that all columns be of the same name and class.
The problem is in the column titles. rbind uses column titles to orient how it will bind the rows. The columns can be in different orders, R will just use the first element to determine column order.
Alternatively, adding another column to your data frames, with the value "A" or "B" in it could preserve your information without putting "A"s and "B"s in your column names <-- the reason you can't use rbind. The additional column would also allow you to do more analyses in R, e.g. regression and other linear models.
Here is one way to handle your data:
Create a uniform set of column names that can be used for the data frames "BlockA" and "BlockB"
final_colnames <- c("Block", "Participant", "Score1", "Score2", "Score3")
Create a new list to identify which block the participants belong to.
BlockA = c("A", "A", "A", "A")
Your previous data
ParticipantA = c("A", "B", "C", "D")
Score1A = c("21", "20", "21", "21")
Score2A = c("32", "40", "32", "31")
Score3A = c("47", "50", "43", "46")
The label "BlockA" is recycled here to name the new data frame, but not before adding the "BlockA" column list of "A" "A" "A" "A".
BlockA = data.frame(BlockA, ParticipantA, Score1A, Score2A, Score3A)
The new column names have to be added at this point, so that the number of names and the number of columns are equal.
colnames(BlockA) <- final_colnames
Now you can add the remaining columns
BlockA$Major = c("Computer_Science", "Computer_Science", "Computer_Science", "Computer_Science")
BlockA$Gender = c("Female", "Female", "Male", "Male")
BlockB is the same process
BlockB = c("B", "B", "B", "B") # the extra column
ParticipantB = c("E", "F", "G", "H")
Score1B = c("28", "28", "21", "22")
Score2B = c("30", "36", "37", "32")
Score3B = c("41", "49", "49", "46")
BlockB = data.frame(BlockB, ParticipantB, Score1B, Score2B, Score3B)
colnames(BlockB) <- final_colnames # renaming the columns
BlockB$Major = c("Medical", "Medical", "Medical", "Medical")
BlockB$Gender = c("Female", "Female", "Male", "Male")
Uniform column names mean that rbind will now work.
rbind(BlockA,BlockB)