In Excel sheet 1, I have the following data:
A B C D E F G
------------------------------
Name1 1 2 3 4 5 6
Name2 2 9 3 8 4 7
Name3 4 6 0 3 2 1
In Excel sheet 2, I have to calculate cumulative sum based on values in sheet 1
For example,
A B C D E F G
------------------------------
Name1 1 3 6 10 15 21
While I can calculate cumulative sum easily, I do not know how to select the correct range of cells from sheet 1, by searching for 'Name1'
You need a SUMPRODUCT with both relative and absolute column/row cell references.
=SUMPRODUCT(($A2:INDEX($A:$A,MATCH(1E+99,$B:$B))=$I5)*($B2:INDEX(B:B,MATCH(1E+99, B:B))))
Related
how I can fin the first and last elements of a dataframe based on a group of rows with respect of a column?
df1:=
g col1 col2
h 1 2
h 0 1
h 7 8
h 5 2
h 0 1
k 7 3
k 2 1
k 9 1
if I wanna group the column with respect of g, and for each group and column I need the following information:
first element, last element, size of the group
IIUC, try:
df_g = df.groupby('dates1').agg(['first','last','size']).T.unstack()
df_g.columns = [f'{i}/{j}' for i, j in df_g.columns]
print(df_g)
Output:
2020-01/first 2020-01/last 2020-01/size 2020-02/first 2020-02/last 2020-02/size
col1 7 9 3 1 0 5
col2 3 1 3 2 1 5
I have a set of values in the following pattern.
A B C D
1 5 6 11
2 6 5 21
3 7 3 42
4 3 7 22
1 2 3 54
2 3 2 43
3 4 3 27
4 3 2 14
I exported the every column into MATLAB workspace as follows.
A = xlsread('F:\R.xlsx','Complete Data','A2:A43');
B = xlsread('F:\R.xlsx','Complete Data','B2:B43');
C = xlsread('F:\R.xlsx','Complete Data','C2:C43');
D = xlsread('F:\R.xlsx','Complete Data','D2:D43');
I need help with code where the it has to check the Column A, find the lowest D value and output the corresponding B and C values. I need the output to look like.
1 5 6 11
2 6 5 21
3 4 3 27
4 3 2 14
I read through related questions and understand that I need to make it a matrix and sort it based on the element on the 4th column using
sortrows
and get indices of the sorted elements. But I am stuck here. Please Guide me.
You can export those columns in one go as:
ABCD = xlsread('F:\R.xlsx','Complete Data','A2:D43');
Now use sortrows to sort the rows according to the first and the fourth column.
req = sortrows(ABCD, [1 4]);
☆ If all elements of the first column exist twice then:
req = req(1:2:end,:);
☆ If it is not necessary that all elements of the first column will exist twice then:
[~, ind] = unique(req(:,1));
req = req(ind,:);
I will try to explain what I need through an example.
Suppose you have a matrix x as follows:
1 2 3
4 5 6
And another matrix y as follows:
1 4 5
7 4 8
What I need is (without looping over the rows) to perform an intersection between each 2 corresponding rows in x & y. So I wish to get a matrix z as follows:
1
4
The 1st rows in x and y only have 1 as the common value. The 2nd rows have 4 as the common value.
EDIT:
I forgot to add that in my case, it is guaranteed that the intersection results will have the same length and the length is always 1 actually.
I am thinking bsxfun -
y(squeeze(any(bsxfun(#eq,x,permute(y,[1 3 2])),2)))
Sample runs -
Run #1:
>> x
x =
1 2 3
4 5 6
>> y
y =
1 4 5
7 4 8
>> y(squeeze(any(bsxfun(#eq,x,permute(y,[1 3 2])),2)))
ans =
1
4
Run #2:
>> x
x =
3 5 7 9
2 7 9 0
>> y
y =
6 4 3
6 0 2
>> y(squeeze(any(bsxfun(#eq,x,permute(y,[1 3 2])),2)))
ans =
0
3
2
The idea is to put the matrices together and to look for duplicates in the rows. One idea to find duplicated numeric values is to diff them; the duplicates will be marked by the value 0 in result.
Which leads to:
%'Initial data'
A = [1 2 3; 8 5 6];
B = [1 4 5; 7 4 8];
%'Look in merged data'
V = sort([A,B],2); %'Sort matrix values in rows'
R = V(diff(V,1,2)==0); %'Find duplicates in rows'
This should work with any number of matrices that can be concatenated horizontally. It will detect all the duplicates, but it will return a column the same size as the number of rows only if there is one and only one duplicate per row in the matrices.
I have three numerical vectors containing position values (pos), a category (type), and an index (ind), in these general forms:
pos =
2 4 5 11 1 5 8 11 12 20
type =
1 2 1 2 1 1 2 1 2 3
ind =
1 1 1 1 2 2 2 2 2 2
I want to calculate the difference between values held within pos but only between the same types, and confined to each index. Using the above example:
When ind = 1
The difference(s) between type 1 positions = 3 (5-2).
The difference(s) between type 2 positions = 7 (11-4).
In the case where more than two instances of any given type exist within any index, the differences are calculate sequentially from left to right as shown here:
When ind = 2
The difference(s) between type 1 positions = 4 (5-1), 6 (11-5).
The difference(s) between type 2 positions = 4 (12-8).
Even though index 2 contains type '3', no difference is calculated as only 1 instance of this type is present.
Types are not always only 1, 2 or 3.
Ideally, the desired output would be matrix containing the same number of columns as length(unique(type)) with rows containing all differences calculated for that type. The output does not need to separate by index, only the actual calculation needs to. In this case there are three unique types, so the output would be (labels added for clarity only):
Type 1 Type 2 Type 3
3 7 0
4 4 0
6 0 0
Any empty entries can be padded with zeroes.
Is there a concise or fast manner to do this?
EDIT:
EDIT 2:
Additional input/output example.
pos = [1 15 89 120 204 209 8 43 190 304]
type = [1 1 1 2 2 1 2 3 2 3]
ind = [1 1 1 1 1 1 2 2 2 2]
Desired output:
Type 1 Type 2 Type 3
14 84 261
74 182 0
120 0 0
In this case, the script works perfectly:
At least for creating the output matrix a loop is required:
pos = [2 4 5 11 1 5 8 11 12 20]
type = [1 2 1 2 1 1 2 1 2 3]
ind = [1 1 1 1 2 2 2 2 2 2]
%// get unique combinations of type and ind
[a,~,subs] = unique( [type(:) ind(:)] , 'rows')
%// create differences
%// output is cell array according to a
temp = accumarray(subs,1:numel(subs),[],#(x) {abs(diff(pos(x(end:-1:1))))} )
%// creating output matrix
for ii = 1:max(a(:,1)) %// iterating over types
vals = [temp{ a(:,1) == ii }]; %// differences for each type
out(1:numel(vals),ii) = vals;
end
out =
3 7 0
4 4 0
6 0 0
In case it doesn't work for your real data you may need unique(...,'rows','stable') and a 'stable' accumarray.
It appeared that the above solution gives different results depending on the system.
The only reason, why the code could give different results on different machines, is that accumarray is not "stable" as mentioned above. And in some very rare cases it could return unpredictable results. So please try the following:
pos = [2 4 5 11 1 5 8 11 12 20]
type = [1 2 1 2 1 1 2 1 2 3]
ind = [1 1 1 1 2 2 2 2 2 2]
%// get unique combinations of type and ind
[a,~,subs] = unique( [type(:) ind(:)] , 'rows')
%// take care of unstable accumarray
[~, I] = sort(subs);
pos = pos(I);
subs = subs(I,:);
%// create differences
%// output is cell array according to a
temp = accumarray(subs,1:numel(subs),[],#(x) {abs(diff(pos(x(end:-1:1))))} )
%// creating output matrix
for ii = 1:max(a(:,1)) %// iterating over types
vals = [temp{ a(:,1) == ii }]; %// differences for each type
out(1:numel(vals),ii) = vals;
end
out =
3 7 0
4 4 0
6 0 0
I have a 2D matrix and want to sort rows and columns based on two other vectors i.e. one for ordering rows another for ordering columns in MATLAB
Example: A (Matrix to order)
0 1 2 3 4
1 1 8 9 7
2 3 4 6 2
3 1 2 0 8
Row Vector (Order for sorting rows of matrix A)
1
4
2
3
And column vector
1 5 4 2 3
Modified A
0 4 3 1 2
3 8 0 1 2
1 7 9 1 8
2 2 6 3 4
How about:
ModifiedA=A(RowVector,ColumnVector);
Note: Matab's indexing starts at 1 not at 0, adapt your indexing vectors accordingly.
In MATLAB, you can use the second output of sort to get the 1-based indexes that MATLAB is looking for (in this case you could have just added 1, but using sort works even if the row and column vectors are not consecutive).
[~,rowIdx] = sort(rowVector);
[~,colIdx] = sort(colVector);
And then you can apply the indexing operation to the matrix:
modifiedA = A(rowIdx, colIdx);