IF Formula in Power BI DAX - powerbi

I would like to do a nested if statement within powerbi, I need to have multiple if statements in one column with some returning - value depending on the if statement.
I have tried to below however theyre all coming back as false.
Calculated value = if('TableName'[ColumnName1] = "exp1" && 'TableName'[columnName2] = "exp2", 'TableName'[value]|| if('TableName'[ColumnName1] = "exp1" && 'TableName'[ColumnName2] = "exp3", - 'TableName'[value],""))

In the first if you don't have any output to the false result. I Add an extra empty value in your calculated value as below only to exemplify what you need to add:
Calculated value = if('TableName'[ColumnName1] = "exp1" && 'TableName'[columnName2] = "exp2", 'TableName'[value]|| if('TableName'[ColumnName1] = "exp1" && 'TableName'[ColumnName2] = "exp3", - 'TableName'[value],""),"")
Check the example and tell something about this, please

Related

I am trying to get the difference of measure values in DAX but getting 0

I will like to get the difference between two measure values using DAX
AADPMAU_Increase = [AADPMAU_End] - [AADPMAU_Start]
But when I do the subtraction, I am getting 0
I have tried different things, but nothing is working
The two values are start and end values that are set by date selector filters. It appears that the calculation is always treating both as equal therefore returning 0
AADPMAU_Start = CALCULATE(AADPTable[AADPMAU_Sum],FILTER(DimDate,DimDate[StartDate] = DimDate[StartDate]))
AADPMAU_End = CALCULATE(AADPTable[AADPMAU_Sum],FILTER(DimDate,DimDate[EndDate] = DimDate[EndDate]))
AADPMAU Increase =
var at_end = AADPTable[AADPMAU_End]
var at_start = AADPTable[AADPMAU_Start]
return at_end - at_start

Return NOW if it's the current hour

I am trying to create a column with empty values if it's not the current hour, else return NOW.
I tried this:
CurrentHour = IF(Datatime_long[Date] = YEAR(TODAY()) && Datatime_long[Time] = HOUR(NOW()), "NOW","")
Could somebody spot the mistake or is there another way to tackle this ?
Data looks like this and sample output is CurrentHour with all empty values
One way to tackle this is to use DATEDIFF: using it with HOUR parameter will return zero only if we are in the current hour.
This column should work:
ThisHour = IF(DATEDIFF(DateTable[Datetime], NOW(), HOUR) = 0, NOW(), BLANK())

LOOP to Look up the value in M Query

I have a following data table:
I need to create a column called FINAL VALUE with certain rules in the power query editor:
The FINAL VALUE is created based on the COUNTRY
If VALUE is greater than 100, then the previous value will be taken
if the previous values (no previous value such as 202001) are all greater than 100, then 100
So the final table should look like:
I sort COUNTRY and DATE, and then I try to apply loop in M Query. As I am not familiar with the function in M query, I have hard time figuring out. I appreciate any help. Thank you.
I believe you are better of in DAX. You can create a new column like below:
Final Value =
var curCountry = TableCountry[Country]
var curDate = TableCountry[Date]
var prevDate = CALCULATE(MAX(TableCountry[Date]), FILTER(TableCountry, curDate >= TableCountry[Date] && curCountry = TableCountry[Country] && TableCountry[Value] <=100))
return LOOKUPVALUE(TableCountry[Value], TableCountry[Country], curCountry, TableCountry[Date], prevDate, 100)

Power Query conditional sumif

I need to add a column that Sums the value column of all columns that have a common id. However, any id = null is not summed, but equal to the value column.
The above example should result in:
TopPaymendId JournalLineNetAmount TopAmount
fcbcd407-ca26-4ea0-839a-c39767d05403 -3623.98 -7061.23
fcbcd407-ca26-4ea0-839a-c39767d05403 -3437.25 -7061.23
ce77faac-1638-40e9-ad62-be1813ce9031 -88.68 -88.68
531d9bde-3f52-47f3-a9cf-6f3566733af2 -152.23 -152.23
8266dfef-dd14-4654-a6d2-091729defde7 229.42 229.42
f8b97a47-15ef-427d-95e0-ce23cc8efb1f -777 -777
null -3.01 -3.01
null -2.94 -2.94
null 3312.5 3312.5
This code should work:
let
Source = Excel.CurrentWorkbook(){[Name="Data"]}[Content],
group = Table.Group(Source, {"TopPaymendId"}, {"TopAmount", each List.Sum([JournalLineNetAmount])}),
join = Table.Join(Source,{"TopPaymendId"},group,{"TopPaymendId"}),
replace = Table.ReplaceValue(join,each [TopAmount],each if [TopPaymendId] = null
then [JournalLineNetAmount] else [TopAmount],Replacer.ReplaceValue,{"TopAmount"})
in
replace

Combining data from two dataframe columns into one column

I have time series data in two separate DataFrame columns which refer to the same parameter but are of differing lengths.
On dates where data only exist in one column, I'd like this value to be placed in my new column. On dates where there are entries for both columns, I'd like to have the mean value. (I'd like to join using the index, which is a datetime value)
Could somebody suggest a way that I could combine my two columns? Thanks.
Edit2: I written some code which should merge the data from both of my column, but I get a KeyError when I try to set the new values using my index generated from rows where my first df has values but my second df doesn't. Here's the code:
def merge_func(df):
null_index = df[(df['DOC_mg/L'].isnull() == False) & (df['TOC_mg/L'].isnull() == True)].index
df['TOC_mg/L'][null_index] = df[null_index]['DOC_mg/L']
notnull_index = df[(df['DOC_mg/L'].isnull() == True) & (df['TOC_mg/L'].isnull() == False)].index
df['DOC_mg/L'][notnull_index] = df[notnull_index]['TOC_mg/L']
df.insert(len(df.columns), 'Mean_mg/L', 0.0)
df['Mean_mg/L'] = (df['DOC_mg/L'] + df['TOC_mg/L']) / 2
return df
merge_func(sve)
And here's the error:
KeyError: "['2004-01-14T01:00:00.000000000+0100' '2004-03-04T01:00:00.000000000+0100'\n '2004-03-30T02:00:00.000000000+0200' '2004-04-12T02:00:00.000000000+0200'\n '2004-04-15T02:00:00.000000000+0200' '2004-04-17T02:00:00.000000000+0200'\n '2004-04-19T02:00:00.000000000+0200' '2004-04-20T02:00:00.000000000+0200'\n '2004-04-22T02:00:00.000000000+0200' '2004-04-26T02:00:00.000000000+0200'\n '2004-04-28T02:00:00.000000000+0200' '2004-04-30T02:00:00.000000000+0200'\n '2004-05-05T02:00:00.000000000+0200' '2004-05-07T02:00:00.000000000+0200'\n '2004-05-10T02:00:00.000000000+0200' '2004-05-13T02:00:00.000000000+0200'\n '2004-05-17T02:00:00.000000000+0200' '2004-05-20T02:00:00.000000000+0200'\n '2004-05-24T02:00:00.000000000+0200' '2004-05-28T02:00:00.000000000+0200'\n '2004-06-04T02:00:00.000000000+0200' '2004-06-10T02:00:00.000000000+0200'\n '2004-08-27T02:00:00.000000000+0200' '2004-10-06T02:00:00.000000000+0200'\n '2004-11-02T01:00:00.000000000+0100' '2004-12-08T01:00:00.000000000+0100'\n '2011-02-21T01:00:00.000000000+0100' '2011-03-21T01:00:00.000000000+0100'\n '2011-04-04T02:00:00.000000000+0200' '2011-04-11T02:00:00.000000000+0200'\n '2011-04-14T02:00:00.000000000+0200' '2011-04-18T02:00:00.000000000+0200'\n '2011-04-21T02:00:00.000000000+0200' '2011-04-25T02:00:00.000000000+0200'\n '2011-05-02T02:00:00.000000000+0200' '2011-05-09T02:00:00.000000000+0200'\n '2011-05-23T02:00:00.000000000+0200' '2011-06-07T02:00:00.000000000+0200'\n '2011-06-21T02:00:00.000000000+0200' '2011-07-04T02:00:00.000000000+0200'\n '2011-07-18T02:00:00.000000000+0200' '2011-08-31T02:00:00.000000000+0200'\n '2011-09-13T02:00:00.000000000+0200' '2011-09-28T02:00:00.000000000+0200'\n '2011-10-10T02:00:00.000000000+0200' '2011-10-25T02:00:00.000000000+0200'\n '2011-11-08T01:00:00.000000000+0100' '2011-11-28T01:00:00.000000000+0100'\n '2011-12-20T01:00:00.000000000+0100' '2012-01-19T01:00:00.000000000+0100'\n '2012-02-14T01:00:00.000000000+0100' '2012-03-13T01:00:00.000000000+0100'\n '2012-03-27T02:00:00.000000000+0200' '2012-04-02T02:00:00.000000000+0200'\n '2012-04-10T02:00:00.000000000+0200' '2012-04-17T02:00:00.000000000+0200'\n '2012-04-26T02:00:00.000000000+0200' '2012-04-30T02:00:00.000000000+0200'\n '2012-05-03T02:00:00.000000000+0200' '2012-05-07T02:00:00.000000000+0200'\n '2012-05-10T02:00:00.000000000+0200' '2012-05-14T02:00:00.000000000+0200'\n '2012-05-22T02:00:00.000000000+0200' '2012-06-05T02:00:00.000000000+0200'\n '2012-06-19T02:00:00.000000000+0200' '2012-07-03T02:00:00.000000000+0200'\n '2012-07-17T02:00:00.000000000+0200' '2012-07-31T02:00:00.000000000+0200'\n '2012-08-14T02:00:00.000000000+0200' '2012-08-28T02:00:00.000000000+0200'\n '2012-09-11T02:00:00.000000000+0200' '2012-09-25T02:00:00.000000000+0200'\n '2012-10-10T02:00:00.000000000+0200' '2012-10-24T02:00:00.000000000+0200'\n '2012-11-21T01:00:00.000000000+0100' '2012-12-18T01:00:00.000000000+0100'] not in index"
You are close, but you actually don't need to iterate over the rows when using the isnull() functions. by default
df[(df['DOC_mg/L'].isnull() == False) & (df['TOC_mg/L'].isnull() == True)].index
Will return just the index of the rows where DOC_mg/L is not null and TOC_mg/L is null.
Now you can do something like this to set the values for TOC_mg/L:
null_index = df[(df['DOC_mg/L'].isnull() == False) & \
(df['TOC_mg/L'].isnull() == True)].index
df['TOC_mg/L'][null_index] = df['DOC_mg/L'][null_index] # EDIT To switch the index position.
This will use the index of the rows where TOC_mg/L is null and DOC_mg/L is not null, and set the values for TOC_mg/L to the those found in DOC_mg/L in the same rows.
Note: This is not the accepted way for setting values using an index, but it is how I've been doing it for some time. Just make sure that when setting values, the left side of the equation is df['col_name'][index]. If col_name and index are switched you will set the values to a copy which is never set back to the original.
Now to set the mean, you can create a new column, we'll call this Mean_mg/L and set the value = 0.0. Then set this new column to the mean of both columns:
# Insert a new col at the end of the dataframe columns name 'Mean_mg/L'
# with default value 0.0
df.insert(len(df.columns), 'Mean_mg/L', 0.0)
# Set this columns value to the average of DOC_mg/L and TOC_mg/L
df['Mean_mg/L'] = (df['DOC_mg/L'] + df['TOC_mg/L']) / 2
In the columns where we filled null values with the corresponding column value, the average will be the same as the values.