Given a table with data like:
A
B
Qty.
Running Total
5
5
5
10
5
15
I can create the running total using the formula =SUM($A$2:A2) and then drag down to get the running total after each quantity (here Qty.)
What may I do for calculating running total using two columns which may or may not be consecutive as shown below:
A
B
C
D
Qty. 1
Other
Qty. 2
RT
2
blah
2
4
2
phew
2
8
3
xyz
2
13
Place in cell D2 the formula =SUM(A2,C2,D1). Do not pay attention to the fact that the function will refer to a non-numeric cell D1 - the SUM() function will not break, unlike ordinary addition =A2+C2+D1. Now, just stretch the formula down.
To be generic the issue is: I need to create group means that exclude own group observations before calculating the mean.
As an example: let's say I have firms, products and product characteristics. Each firm (f=1,...,F) produces several products (i=1,...,I). I would like to create a group mean for a certain characteristic of the product i of firm f, using all products of all firms, excluding firm f product observations.
So I could have a dataset like this:
firm prod width
1 1 30
1 2 10
1 3 20
2 1 25
2 2 15
2 4 40
3 2 10
3 4 35
To reproduce the table:
firm=[1,1,1,2,2,2,3,3]
prod=[1,2,3,1,2,4,2,4]
hp=[30,10,20,25,15,40,10,35]
x=[firm' prod' hp']
Then I want to estimate a mean which will use values of all products of all other firms, that is excluding all firm 1 products. In this case, my grouping is at the firm level. (This mean is to be used as an instrumental variable for the width of all products in firm 1.)
So, the mean that I should find is: (25+15+40+10+35)/5=25
Then repeat the process for other firms.
firm prod width mean_desired
1 1 30 25
1 2 10 25
1 3 20 25
2 1 25
2 2 15
2 4 40
3 2 10
3 4 35
I guess my biggest difficulty is to exclude the own firm values.
This question is related to this page here: Calculating group mean/medians in MATLAB where group ID is in a separate column. But here, we do not exclude the own group.
p.s.: just out of curiosity if anyone works in economics, I am actually trying to construct Hausman or BLP instruments.
Here's a way that avoids loops, but may be memory-expensive. Let x denote your three-column data matrix.
m = bsxfun(#ne, x(:,1).', unique(x(:,1))); % or m = ~sparse(x(:,1), 1:size(x,1), true);
result = m*x(:,3);
result = result./sum(m,2);
This creates a zero-one matrix m such that each row of m multiplied by the width column of x (second line of code) gives the sum of other groups. m is built by comparing each entry in the firm column of x with the unique values of that column (first line). Then, dividing by the respective count of other groups (third line) gives the desired result.
If you need the results repeated as per the original firm column, use result(x(:,1))
I am new to tableau and need help in figuring this out.I have a dataset in below format:
hid:id for the house the customer belong
cid:customer id
hID CustomerID
1 A
1 B
1 C
2 D
2 E
3 F
3 G
3 H
3 I
4 J
5 K
5 L
5 M
5 N
5 O
So A,B belong to house 1 so count of hid '1' is 3 so:
hid count of members
1 3
2 2
3 3
4 1
5 5
I want to show a graph in tableau as size of house that is X-axis :Size of house and Y-axis :Count no of house with same size so for above data the values as below:
Size of house no of house
1 1
2 1
3 2
4 0
5 1
The final graph should be:
In Tableau jargon, you're looking to bin based upon an aggregate value. Take a look at the following blog post for a more detailed description/walk-through.
One way to accomplish this is by leveraging talbeau's level of detail calculations. Creating a calculated field along the lines of:
{FIXED [hID] : COUNTD([CustomerID])}
You can then create a bin field by right clicking on the new field and binning based on a parameter, or a a static size (1?) of your choosing.
To create the visual, place this second bin field on the row shelf and on the column shelf drag the hID dimension and right click to convert to a measure by selecting Count Distinct.
As a side note, depending on whether you set your bin field as continuous or discrete, the 4 bin in your sample data will or will not appear.
I have a table that looks like:
id aff1 aff2 aff3 value
1 a x b 5
2 b c x 4
3 a b g 1
I would like to aggregate the aff columns to calculate the sum of "value" for each aff. For example, the above gives:
aff sum
a 6
b 10
c 4
g 1
x 9
Ideally, I'd like to do this directly in tableau without remaking the table by unfolding it along all the aff columns.
You can use Tableau’s inbuilt pivot method as below, without reshaping in source .
CTRL Select all 3 dimensions you want to merge , and click on pivot .
You will get your new reshaped data as below, delete other columns :
Finally build your view.
I hope this answers . Rest other options for the above results include JOIN at DB level, or creating multiple calculated fields for each attribute value which are not scalable.
I have a postgresql table that looks like this
Division Rate
a 7
b 3
c 4
a 5
b 2
a 1
I want to return a table that looks like this
Division Average
a 3.5
b 1.6
c 5
Is there any way for me to do that? I can't seem to come up for the logic for it.
select Division,avg(Rate) from your_table group by Division;