I have a data set with cols (ID, Calc.CompleteBool where complete = 1 and incomplete = 0) of the form:
ID | Calc.CompleteBool
----------------------------
100| 1
101| 0
103| 1
105| 1
I need to create a measure that gives me a single percentage complete. Thus, the measure needs to count the total number of IDs (n) and divide by that number the total IDs that meet the condition of 'complete' or 1.
E.g. 3 / 4 = 75%
I have tried the following and it does not work. It is returning a value of zero (0). Your assistance is greatly appreciated.
Here is my code:
Calc.pctComplete =
VAR total_aps =
CALCULATE(
COUNT('TABLE_NAME'[ID]),
FILTER(
ALL('TABLE_NAME'),
'TABLE_NAME'[Calc.CompleteBool] = 'TABLE_NAME'[Calc.CompleteBool]
)
)
VAR total_aps_complete =
CALCULATE(
COUNT('TABLE_NAME'[Calc.CompleteBool]),
FILTER(
ALL('TABLE_NAME'),
'TABLE_NAME'[Calc.CompleteBool] = 1
)
)
RETURN total_aps_complete/total_aps
Update
I also need to add another filter in that only returns rows where "CheckID" = Yes.
There are 3,700 total IDs
There are ~ 1,500 IDs where CheckID = Yes
And roughly 8 where Calc.CompleteBool = 1
ID | Calc.CompleteBool | CheckID |
---------------------------------------
100| 1 | Yes
101| 0 | No
103| 1 | No
105| 1 | Yes
106| 0 | Yes
{100, 105, 106} are the set that would be included. So the division would be 2/3 = 66% complete.
Your result can be calculated with simple dax formula as following. The concept of calculate with filter can transform count into similar function like excel countifs:
Completion = CALCULATE(COUNT(Sheet1[ Calc.CompleteBool]),
Sheet1[ Calc.CompleteBool]=1, Sheet1[CheckID]="Yes") /
COUNT(Sheet1[ Calc.CompleteBool])
Output:
You may use this measure (add +0 to __completed if you want see 0% if all rows has 0 in Calc.CompleteBool either you get BLANK:
Percentage% =
var __completed = CALCULATE( COUNTROWS(VALUES(TABLE_NAME[ID])), 'TABLE_NAME'[Calc.CompleteBool] = 1) + 0
var __all = COUNTROWS('TABLE_NAME')
return
DIVIDE(__completed, __all)
Consider to use DIVIDE instead of "/" https://dax.guide/divide/
Related
I have the data below
create table #data (Post_Code varchar(10), Internal_Code varchar(10))
insert into #data values
('AB10','hb3'),('AB10','hb25'),('AB12','dd1'),('AB15','hb6'),('AB16','aa4'),('AB16','hb7'),
('AB16','aa2'),('AB16','ab9'),('AB18','rr6'),('AB18','rr9'),('AB18','hb10'),('AB20','rr15'),
('AB20','td2'),('AB21','hb8'),('AB21','cc4'),('AB21','cc4'),('AB24','td5'),('AB9','yy3'),
('RM2','CC1'),('RM6','hb6'),('RM7','cc2'),('SA24','rr1'),('SA24','hb5'),('SA24','rr2'),
('SA24','cc34'),('SE15','rr9'),('SE15','rr5'),('SE25','rr10'),('SE25','hb11'),('SE25','rr8'),
('SE25','rr1'),('LA15','rr2')
select * from #data
drop table #data
What I want to achieve is if the same post code area have “hb” or “rr” in the same post code I want to return 1 else 0
The “hb” or “rr” internal_code must be in the same post_code if they in different post code. It should be 0
I wrote this DAX
Result = IF(left(Data[Internal_Code],2)="hb" || left(Data[Internal_Code],2)="rr",1,0)
it is not returning the correct result
current output
expected output
I think your expected result is incorrect as SA24 should also be 1. You should definitely do a calculation like this in PQ but if you need to do it in DAX in a calculated column, then use the following code which works.
Result =
VAR post_code = Data[Post_code]
RETURN
VAR hb = CALCULATE (COUNTROWS(Data),'Data'[Post_code] = post_code && left(Data[Internal_Code],2) = "hb" )
VAR rr = CALCULATE (COUNTROWS(Data),'Data'[Post_code] = post_code && left(Data[Internal_Code],2) = "rr" )
RETURN IF(hb>0 && rr > 0,1)
I have a table with numeric values and blank records. I'm trying to calculate a number of rows that are not blank and bigger than 20.
+--------+
| VALUES |
+--------+
| 2 |
| 0 |
| 13 |
| 40 |
| |
| 1 |
| 200 |
| 4 |
| 135 |
| |
| 35 |
+--------+
I've tried different options but constantly get the next error: "Cannot convert value '' of type Text to type Number". I understand that blank cells are treated as text and thus my filter (>20) doesn't work. Converting blanks to "0" is not an option as I need to use the same values later to calculate AVG and Median.
CALCULATE(
COUNTROWS(Table3),
VALUE(Table3[VALUES]) > 20
)
OR getting "10" as a result:
=CALCULATE(
COUNTROWS(ALLNOBLANKROW(Table3[VALUES])),
VALUE(Table3[VALUES]) > 20
)
The final result in the example table should be: 4
Would be grateful for any help!
First, the VALUE function expects a string. It converts strings like "123"into the integer 123, so let's not use that.
The easiest approach is with an iterator function like COUNTX.
CountNonBlank = COUNTX(Table3, IF(Table3[Values] > 20, 1, BLANK()))
Note that we don't need a separate case for BLANK() (null) here since BLANK() > 20 evaluates as False.
There are tons of other ways to do this. Another iterator solution would be:
CountNonBlank = COUNTROWS(FILTER(Table3, Table3[Values] > 20))
You can use the same FILTER inside of a CALCULATE, but that's a bit less elegant.
CountNonBlank = CALCULATE(COUNT(Table3[Values]), FILTER(Table3, Table3[Values] > 20))
Edit
I don't recommend the CALCULATE version. If you have more columns with more conditions, just add them to your FILTER. E.g.
CountNonBlank =
COUNTROWS(
FILTER(Table3,
Table3[Values] > 20
&& Table3[Text] = "xyz"
&& Table3[Number] <> 0
&& Table3[Date] <= DATE(2018, 12, 31)
)
)
You can also do OR logic with || instead of the && for AND.
Is it possible to perform calculations between records in a Django query?
I know how to perform calculations across records (e.g. data_a + data_b). Is there way to perform say the percent change between data_a row 0 and row 4 (i.e. 09-30-17 and 09-30-16)?
+-----------+--------+--------+
| date | data_a | data_b |
+-----------+--------+--------+
| 09-30-17 | 100 | 200 |
| 06-30-17 | 95 | 220 |
| 03-31-17 | 85 | 205 |
| 12-31-16 | 80 | 215 |
| 09-30-16 | 75 | 195 |
+-----------+--------+--------+
I am currently using Pandas to perform these type of calculations, but would like eliminate this additional step if possible.
I would go with a Database cursor raw SQL
(see https://docs.djangoproject.com/en/2.0/topics/db/sql/)
combined with a Lag() window function as so:
result = cursor.execute("""
select date,
data_a - lag(data_a) over (order by date) as data_change,
from foo;""")
This is the general idea, you might need to change it according to your needs.
There is no row 0 in a Django database, so we'll assume rows 1 and 5.
The general formula for calculation of percentage as expressed in Python is:
((b - a) / a) * 100
where a is the starting number and b is the ending number. So in your example:
a = 100
b = 75
((b - a) / a) * 100
-25.0
If your model is called Foo, the queries you want are:
(a, b) = Foo.objects.filter(id__in=[id_1, id_2]).values_list('data_a', flat=True)
values_list says "get just these fields" and flat=True means you want a simple list of values, not key/value pairs. By assigning it to the (a, b) tuple and using the __in= clause, you get to do this as a single query rather than as two.
I would wrap it all up into a standalone function or model method:
def pct_change(id_1, id_2):
# Get a single column from two rows and return percentage of change
(a, b) = Foo.objects.filter(id__in=[id_1, id_2]).values_list('data_a', flat=True)
return ((b - a) / a) * 100
And then if you know the row IDs in the db for the two rows you want to compare, it's just:
print(pct_change(233, 8343))
If you'd like to calculate progressively the change between row 1 and row 2, then between row 2 and row 3, and so on, you'd just run this function sequentially for each row in a queryset. Because row IDs might have gaps we can't just use n+1 to compute the next row. Instead, start by getting a list of all the row IDs in a queryset:
rows = [r.id for r in Foo.objects.all().order_by('date')]
Which evaluates to something like
rows = [1,2,3,5,6,9,13]
Now for each elem in list and the next elem in list, run our function:
for (index, row) in enumerate(rows):
if index < len(rows):
current, next_ = row, rows[index + 1]
print(current, next_)
print(pct_change(current, next_))
I have a series of numbers and I would like to know % of numbers falling in every bucket of a dataframe.
df['cuts'] have 10, 20 and 50 as values. Specifically, I would like to what % of series are in [0-10], (10-20] and (20-50] bin and this should be appended to the df dataframe.
I wrote the following code. I definitely feel that it could be improvised. Any help is appreciated.
bin_cuts = [-1] + list(df['cuts'].values)
out = pd.cut(series, bins = bin_cuts)
df_pct_bins = pd.value_counts(out, normalize= True).reset_index()
df_pct_bins = pd.concat([df_pct_bins['index'].str.split(', ', expand = True), df_pct_bins['cuts']], axis = 1)
df_pct_bins[1] = df_pct_bins[1].str[:-1].astype(str)
df['cuts'] = df['cuts'].astype(str)
df_pct_bins = pd.merge(df, df_pct_bins, left_on= 'cuts', right_on= 1)
Consider the sample data df and s
df = pd.DataFrame(dict(cuts=[10, 20, 50]))
s = pd.Series(np.random.randint(50, size=1000))
Option 1
np.searchsorted
c = df.cuts.values
df.assign(
pct=df.cuts.map(
pd.value_counts(
c[np.searchsorted(c, s)],
normalize=True
)))
cuts pct
0 10 0.216
1 20 0.206
2 50 0.578
Option 2
pd.cut
c = df.cuts.values
df.assign(
pct=df.cuts.map(
pd.cut(
s,
np.append(-np.inf, c),
labels=c
).value_counts(normalize=True)
))
cuts pct
0 10 0.216
1 20 0.206
2 50 0.578
I have an Excel table in sheet1 in which column A:
Name of company Company 1 Company 2 Company
3 Company 1 Company 4 Company 1 Company
3
I want to extract a unique list of company names to sheet2 also in column A. I can only do this with help of a helper column if I dont have any blanks between company names but when I do have I get one more company which is a blank.
Also, I've researched but the example was for non-dynamic tables and so it doesn't work because I don't know the length of my column.
I want in Sheet2 Column A:
Name of company Company 1 Company 2 Company 3
Company 4
Looking for the solution that requires less computational power Excel or Excel-VBA. The final order which they appear in sheet2 don't really matter.
Using a slight modification to Recorder-generated code:
Sub Macro1()
Sheets("Sheet1").Range("A:A").Copy Sheets("Sheet2").Range("A1")
Sheets("Sheet2").Range("A:A").RemoveDuplicates Columns:=1, Header:=xlYes
With Sheets("Sheet2").Sort
.SortFields.Clear
.SortFields.Add Key:=Range("A2:A" & Rows.Count) _
, SortOn:=xlSortOnValues, Order:=xlAscending, DataOption:=xlSortNormal
.SetRange Range("A2:A" & Rows.Count)
.Header = xlGuess
.MatchCase = False
.Orientation = xlTopToBottom
.SortMethod = xlPinYin
.Apply
End With
End Sub
Sample Sheet1:
Sample Sheet2:
The sort removes the blanks.
EDIT#1:
If the original data in Sheet1 was derived from formulas, then using PasteSpecial will remove unwanted formula copying. There is also a final sweep for empty cells:
Sub Macro1_The_Sequel()
Dim rng As Range
Sheets("Sheet1").Range("A:A").Copy
Sheets("Sheet2").Range("A1").PasteSpecial Paste:=xlPasteValues
Sheets("Sheet2").Range("A:A").RemoveDuplicates Columns:=1, Header:=xlYes
Set rng = Sheets("Sheet2").Range("A2:A" & Rows.Count)
With Sheets("Sheet2").Sort
.SortFields.Clear
.SortFields.Add Key:=rng, SortOn:=xlSortOnValues, Order:=xlAscending, DataOption:=xlSortNormal
.SetRange rng
.Header = xlGuess
.MatchCase = False
.Orientation = xlTopToBottom
.SortMethod = xlPinYin
.Apply
End With
Call Kleanup
End Sub
Sub Kleanup()
Dim N As Long, i As Long
With Sheets("Sheet2")
N = .Cells(Rows.Count, "A").End(xlUp).Row
For i = N To 1 Step -1
If .Cells(i, "A").Value = "" Then
.Cells(i, "A").Delete shift:=xlUp
End If
Next i
End With
End Sub
All of these answers use VBA. The easiest way to do this is to use a pivot table.
First, select your data, including the header row, and go to Insert -> PivotTable:
Then you will get a dialog box. You don't need to select any of the options here, just click OK. This will create a new sheet with a blank pivot table. You then need to tell Excel what data you're looking for. In this case, you only want the Name of company in the Rows section. On the right-hand side of Excel you will see a new section named PivotTable Fields. In this section, simply click and drag the header to the Rows section:
This will give a result with just the unique names and an entry with (blank) at the bottom:
If you don't want to use the Pivot Table further, simply copy and paste the result rows you're interested in (in this case, the unique company names) into a new column or sheet to get just those without the pivot table attached. If you want to keep the pivot table, you can right click on Grand Total and remove that, as well as filter the list to remove the (blank) entry.
Either way, you now have your list of unique results without blanks and it didn't require any formulas or VBA, and it took relatively few resources to complete (far fewer than any VBA or formula solution).
Here's another method using Excel's built-in Remove Duplicates feature, and a programmed method to remove the blank lines:
EDIT
I have deleted the code using the above methodology as it takes too long to run. I have replaced it with a method that uses VBA's collection object to compile a unique list of companies.
The first method, on my machine, took about two seconds to run; the method below: about 0.02 seconds.
Sub RemoveDups()
Dim wsSrc As Worksheet, wsDest As Worksheet
Dim rRes As Range
Dim I As Long, S As String
Dim vSrc As Variant, vRes() As Variant, COL As Collection
Set wsSrc = Worksheets("sheet1")
Set wsDest = Worksheets("sheet2")
Set rRes = wsDest.Cells(1, 1)
'Get the source data
With wsSrc
vSrc = .Range(.Cells(1, 1), .Cells(.Rows.Count, 1).End(xlUp))
End With
'Collect unique list of companies
Set COL = New Collection
On Error Resume Next
For I = 2 To UBound(vSrc, 1) 'Assume Row 1 is the header
S = CStr(Trim(vSrc(I, 1)))
If Len(S) > 0 Then COL.Add S, S
Next I
On Error GoTo 0
'Populate results array
ReDim vRes(0 To COL.Count, 1 To 1)
'Header
vRes(0, 1) = vSrc(1, 1)
'Companies
For I = 1 To COL.Count
vRes(I, 1) = COL(I)
Next I
'set results range
Set rRes = rRes.Resize(UBound(vRes, 1) + 1)
'Write the results
With rRes
.EntireColumn.Clear
.Value = vRes
.EntireColumn.AutoFit
'Uncomment the below line if you want
'.Sort key1:=.Columns(1), order1:=xlAscending, MatchCase:=False, Header:=xlYes
End With
End Sub
NOTE: You wrote you didn't care about the order, but if you want to Sort the results, that added about 0.03 seconds to the routine.
With two sheets named 1 and 2
Inside sheet named: 1
+----+-----------------+
| | A |
+----+-----------------+
| 1 | Name of company |
| 2 | Company 1 |
| 3 | Company 2 |
| 4 | |
| 5 | Company 3 |
| 6 | Company 1 |
| 7 | |
| 8 | Company 4 |
| 9 | Company 1 |
| 10 | Company 3 |
+----+-----------------+
Result in sheet named: 2
+---+-----------------+
| | A |
+---+-----------------+
| 1 | Name of company |
| 2 | Company 1 |
| 3 | Company 2 |
| 4 | Company 3 |
| 5 | Company 4 |
+---+-----------------+
Use this code in a regular module:
Sub extractUni()
Dim objDic
Dim Cell
Dim Area As Range
Dim i
Dim Value
Set Area = Sheets("1").Range("A2:A10") 'this is where your data is located
Set objDic = CreateObject("Scripting.Dictionary") 'use a Dictonary!
For Each Cell In Area
If Not objDic.Exists(Cell.Value) Then
objDic.Add Cell.Value, Cell.Address
End If
Next
i = 2 '2 because the heading
For Each Value In objDic.Keys
If Not Value = Empty Then
Sheets("2").Cells(i, 1).Value = Value 'Store the data in column D below the heading
i = i + 1
End If
Next
End Sub
The code return the date unsorted, just the way data appears.
if you want a sorted list, just add this code before the las line:
Dim sht As Worksheet
Set sht = Sheets("2")
sht.Activate
With sht.Sort
.SetRange Range("A:A")
.Header = xlYes
.MatchCase = False
.Orientation = xlTopToBottom
.SortMethod = xlPinYin
.Apply
End With
This way the result will be always sorted.
(The subrutine would be like this)
Sub extractUni()
Dim objDic
Dim Cell
Dim Area As Range
Dim i
Dim Value
Set Area = Sheets("1").Range("A2:A10") 'this is where your data is located
Set objDic = CreateObject("Scripting.Dictionary") 'use a Dictonary!
For Each Cell In Area
If Not objDic.Exists(Cell.Value) Then
objDic.Add Cell.Value, Cell.Address
End If
Next
i = 2 '2 because the heading
For Each Value In objDic.Keys
If Not Value = Empty Then
Sheets("2").Cells(i, 1).Value = Value 'Store the data in column D below the heading
i = i + 1
End If
Next
Dim sht As Worksheet
Set sht = Sheets("2")
sht.Activate
With sht.Sort
.SetRange Range("A:A")
.Header = xlYes
.MatchCase = False
.Orientation = xlTopToBottom
.SortMethod = xlPinYin
.Apply
End With
End Sub
If you have any question about the code, I will glad to explain.