We are trying to load data with custom cell renderers on grid in Safari 16.x and the grid renders each time very slowly when we scroll and is visually not good.
We have a data like:
Column A
Column B
Column C
Column D
A
X
C
1
A
X
C
2
A
X
D
1
A
X
D
2
A
X
D
3
B
X
E
1
which we want to represent like:
Column A
Column B
Column C
Column D
C
1
2
--------
--------
A
X
1
D
2
3
--------
--------
--------
--------
B
X
E
1
C, D & E data is represented as a tree, for which we have used a custom cell renderer.
We tried enabling rowBuffer property but then it increases the # of DOM elements and grid response is not good. For ~100 row expand and collapse takes around 10sec to render.
Angular: 14.x
ag-grid: 28.x
A few suggestions:
Carefully read the documentation on ag-grid's row virutalization, and make sure that you are not suppressing row virtualization.
As you have seen, for best performance, you'll probably want to keep the rowbuffer as small as possible, but smooth rendering requires a decent sized rowbuffer, so you'll have to find the right size that balances performance vs rendering smoothness.
Ultimately, the cause of your rendering issues is probably the amount of time that it takes to render your custom renderer. If you are using a "platform renderer", i.e. an Angular component, you'll have a lot more overhead than if you use a function. I'd work on making the custom renderer as lightweight as possible.
Related
picture of example dataset
I am looking for a function to change the values from 0,1,2,3,4,5,6 etc. to every 5 in R. I have a big dataset similar to column A and B and would like to change it to columns H and I (like shown in the attached picture).
I'd like to change every cm til every 5 cm so that species that covers 5cm or shorter than 5 cm are registered as a point (similar to equ_palu). Moreover, the specie bet_nana covers 0-10 cm and is therefore registered as 5 and 10 in column H and I.
I have a dataset that I shaped according to my needs, the dataframe is as follows:
Index A B C D ..... Z
Date/Time 1 0 0 0,35 ... 1
Date/Time 0,75 1 1 1 1
The total number of rows is 8878
What I try to do is create a time-series dendrogram (Example: Whole A column will be compared to whole B column in whole time).
I am expecting an output like this:
(source: rsc.org)
I tried to construct the linkage matrix with Z = hierarchy.linkage(X, 'ward')
However, when I print the dendrogram, it just shows an empty picture.
There is no problem if a compare every time point with each other and plot, but in that way, the dendrogram becomes way too complicated to observe even in truncated form.
Is there a way to handle the data as a whole time series and compare within columns in SciPy?
I was thinking about simple reordering rows in relational database's table.
I would like to avoid method described here:
How can I reorder rows in sql database
My simple idea was to use as ListOrder column of type double-precision 64-bit IEEE 754 floating point.
At inserting a row between two existing rows we calculate listOrder value as average of these sibling elements.
Example:
1. Starting state:
value, listOrder
a 1
b 2
c 3
d 4
e 5
f 6
2. Moving "e" two rows up
One simple sql update on e-row: update mytable set listorder=2.5 where value='e'
value, listOrder
a 1
b 2
e 2.5
c 3
d 4
f 6
3. Moving "a" one position down
value, listOrder
b 2
a 2.25
e 2.5
c 3
d 4
f 6
I have a question. How many insertions can I perform (in the edge situation) to have properly ordered list.
For the 64 bit integer there is less than 64 insertions in the same place.
Is floating point types allows to more insertions?
There are other problems with described approach?
Do you see any patches/adjustments to make this idea safe and usable in applications?
This is similar to a lexical order, which can also be done with varchar columns:
A
B
C
D
E
F
becomes
A
B
BM
C
D
F
becomes
B
BF
BM
C
D
F
I prefer the two step process, where you update every row in the table after the one you move to be one larger. Sql is efficient about this, where updating the rows following a change is not as bad as it seems. You preserve something that's more human readable, the storage size for your ordinal value scales in a linear rather with your data size, and you don't risk coming to a point where you don't have enough precision to put an item in between two values
I have a range of data columns A, B, and C. I have displayed as a line graph with B as the primary axis and C as the secondary axis. Column A is the category axis. I want to find the maximum value of column C and put a data callout on the point that is the maximum of column C and where column B occurs.
I know this sounds confusing. In this example, the maximum of Column C occurs at Point 27 (or 1.50% on the category axis). I would like a dot at point 27 for both Column B and C.
Column A is percentage from -5.00 to 10.00 incremented at .25%. Columns B and C are plotted against the change.
In the past I have done something similar, use a formula in column D to identify the largest number in Column C and B and make it a value high on your chart if the result is true.
Add Column D as a series to the chart.
Change the chart type on that series only to a scatter chart or something that puts points up there.
You can put a label on or simply put the amount showing above the plotted point.
You don't need VBA for this.
You might be interested to know I found a solution that works for me. First, I added columns D and E using the formula =IF(C2=MAX(C$2:C$62),C2,NA()) and =IF(C2=MAX(C$2:C$62),B2,NA()), this gave me the point on the graph for both lines B and C where B was maximum. I then formatted the graph so that these points had data callouts (a request from the client). Finally, I set columns D and E to have white font, to match the background so the appear invisible. I don't love this step, but I don't want the client to see the extra rows of #NA, etc.
The basic VBA for data callout is ActiveChart.FullSeriesCollection(5).Select
ActiveChart.SetElement (msoElementDataLabelCallout)
Where the series is 5 (column E) and I'm putting a data callout on the graphed point, which happens to be the maximum of column 3.
I want to combine multiple lists of items into a single list, retaining the overall order requirements. i.e.:
1: A C E
2: D E
3: B A D
result: B A C D E
above, starting with list 1, we have ACE, we then know that D must come before E, and from list 3, we know that B must come before A, and D must come after B and A.
If there are conflicting orderings, the first ordering should be used. i.e.
1: A C E
2: B D E
3: F D B
result: A C F B D E
3 conflicts with 2 (B D vs D B), therefore requirements for 2 will be used.
If ordering requirements mean an item must come before or after another, it doesn't matter if it comes immediately before or after, or at the start or end of the list, as long as overall ordering is maintained.
This is being developed using VB.Net, so a LINQy solution (or any .Net solution) would be nice - otherwise pointers for an approach would be good.
Edit: Edited to make example 2 make sense (a last minute change had made it invalid)
The keyword you are probably interested in is "Topological sorting". The solution based on that would look as follows:
Create an empty directed graph.
Process sequences in order, for each two consecutive elements X,Y in a sequence add an edge X->Y to the graph, unless this would form a cycle.
Perform a topological sort on the vertices of the graph. The resulting sequence should satisfy your requirements.