d4 | A friendly reusable charts DSL for D3 | Chart library
kandi X-RAY | d4 Summary
kandi X-RAY | d4 Summary
D4 is a friendly charting DSL for D3. The goal of D4 is to allow developers to quickly build data-driven charts with little knowledge of the internals of D3.
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Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of d4
d4 Key Features
d4 Examples and Code Snippets
def expand_dims(input: ragged_tensor.Ragged, axis, name=None): # pylint: disable=redefined-builtin
"""Inserts a dimension with shape 1 into a potentially ragged tensor's shape.
Given a potentially ragged tenor `input`, this operation inserts a
moment('2010-10-20').isBetween('2010-10-19', '2010-10-25');
moment("11/04/2022 11:28 AM", 'DD/MM/YYYY hh:mm A')
console.log('--------- TEST CLASSIC DATES ---------')
const startDate = ne
DECLARE @Values TABLE
(
Col1 VARCHAR(20),
Col2 VARCHAR(20),
Col3 VARCHAR(20),
Col4 VARCHAR(20)
UNIQUE (Col1, Col2, Col3, Col4)
);
WITH Data AS
( SELECT Value, v.Ordinal
FROM (VALUES (1, @Col1), (2, @Col2), (3
WITH cte AS (
SELECT loop_msg.msg_id
, channel
, COALESCE(
LEAD(content) OVER w1
, FIRST_VALUE(content) OVER w1
) AS conten
Option Explicit
Sub changeFormat():
' Declare variables
Dim Number As Variant
Dim check As Boolean
'Converts the format of cells D3 and D4 to "Text"
Range("D3:D4").NumberFormat = "@"
'Assign cell to be evaluated
Number = Range("D3")
sameShape :: [a] -> [b] -> Bool
sameShape [] [] = ...
sameShape [] (y:ys) = ...
sameShape (x:xs) [] = ...
sameShape (x:xs) (y:ys) = ...
sameShapes :: [[a]] -> [[b]]
with cte as (
Select *
From YourTable
Cross Apply (
Select d1 = max(case when RN=1 then item end)
,d2 = max(case when RN=2 then item end)
,d3 = max(case when RN=3 then item end)
graph decision_path {
rankdir=LR
node [shape="rectangle"]
edge [dir="both"]
newrank=true
nodesep=.6
{ rank=same
Top
d1 [label="Decision 1"]
cd1 [label="Composite Decision 1"]
cd2 [label="Composi
SELECT
a.*,
d1.data AS Label1,
d2.data AS Label2,
d3.data AS Label3,
d4.data AS Label4
FROM assets a
LEFT JOIN data d1 ON d1.asset_id = a.ID AND d1.input_id = 1
LEFT JOIN data d2 ON d2.asset_id = a.ID AND d2.input_id = 2
LEFT JOI
git checkout master
git cherry-pick D3
git cherry-pick D4
git revert D3^..D4
Community Discussions
Trending Discussions on d4
QUESTION
For reference:
Device- MacBook; I normally work with windows. I haven't had any issues with compatibility.
OS- Big Sur v11.5.2
Excel Ver.- 16.60
File Type- xlsm
Operation detail:
I need Column Range D4:D26 to Input date stamp when any value is input to corresponding cells in column C.
Problem:
I have this code-
...ANSWER
Answered 2022-Apr-14 at 16:54Two immediate issues:
- You need to test
If Not Intersect(Target, rngA) Is Nothing
first. That is, you need to test whetherTarget
and column D intersect, before you attempt to use.Value
. - You're modifying the worksheet inside the
Worksheet_Change
event handler, causing the event to fire again. Normally one usesApplication.EnableEvents = False
to avoid this.
QUESTION
I've written a small function with C-code and a short inline assembly statement.
Inside the inline assembly statement I need 2 "temporary" registers to load and compare some memory values.
To allow the compiler to choose "optimal temporary registers" I would like to avoid hard-coding those temp registers (and putting them into the clobber list).
Instead I decided to create 2 local variables in the surrounding C-function just for this purpose. I used "=r" to add these local variables to the output operands specification of the inline asm statement and then used them for my load/compare purposes.
These local variables are not used elsewhere in the C-function and (maybe because of this fact) the compiler decided to assign the same register to the two related output operands which makes my code unusable (comparison is always true).
Is the compiler allowed to use overlapping registers for different output operands or is this a compiler bug (I tend to rate this as a bug)?
I only found information regarding early clobbers which prevent overlapping of register for inputs and outputs... but no statement for just output operands.
A workaround is to initialize my temporary variables and to use "+r" instead of "=r" for them in the output operand specification. But in this case the compiler emits initialization instructions which I would like to avoid.
Is there any clean way to let the compiler choose optimal registers that do not overlap each other just for "internal inline assembly usage"?
Thank you very much!
P.S.: I code for some "exotic" target using a "non-GNU" compiler that supports "GNU inline assembly".
P.P.S.: I also don't understand in the example below why the compiler doesn't generate code for "int eq=0;" (e.g. 'mov d2, 0'). Maybe I totally misunderstood the "=" constraint modifier?
Totally useless and stupid example below just to illustrate (focus on) the problem:
...ANSWER
Answered 2022-Apr-12 at 04:54I think this is a bug in your compiler.
If it says it supports "GNU inline assembly" then one would expect it to follow GCC, whose manual is the closest thing there is to a formal specification. Now the GCC manual doesn't seem to explicitly say "output operands will not share registers with each other", but as o11c mentions, they do suggest using output operands for scratch registers, and that wouldn't work if they could share registers.
A workaround that might be more efficient than yours would be to follow your inline asm with a second dummy asm statement that "uses" both the outputs. Hopefully this will convince the compiler that they are potentially different values and therefore need separate registers:
QUESTION
I would like to calcul the distribution of a card hand in prolog. It means get this result:
...ANSWER
Answered 2022-Apr-11 at 13:35A possible solution is:
QUESTION
I'm trying to concatenate two dataframes with these conditions :
- for an existing header, append to the column ;
- otherwise add a new column.
The code is working but the columns names are lost in case 2. Why? It doesn't seem to be mentioned in Pandas doc. Or I missed something?
How to keep the column names?
The code :
...ANSWER
Answered 2022-Apr-09 at 04:29You requested to drop the index with ignore_index=True
. As you are concatenating on axis=1
the index is the columns!
QUESTION
This question is a little confusing, but I'll try my best to explain it. I have a dataset with 7 numeric columns (DIF1, DIF2, DIF3, DIF4, DIF5, DIF6, DIF7) and I want to compare them to see which one has the lowest number in each row.
After I do that, I need to create a column to fill with other 7 character columns (D1, D2, D3, D4, D5, D6, D7). I thought about doing it using ifelse statement as below:
...ANSWER
Answered 2022-Apr-07 at 14:42You could apply
which.min
row-wise on columns 1:3
and add 3L
to shift the index and subset the row with it. i.e. chose D*
.
QUESTION
I have the following dataframe df
ANSWER
Answered 2022-Mar-24 at 11:04With a fully dplyr
approach:
QUESTION
In a 'hospital' collection, there are docs for every department in the hospital. Each document has details like department_name, doctors and nurses assigned for this department. The document structure looks like below:
...ANSWER
Answered 2022-Mar-16 at 10:01You can try this query:
- First group all (using
_id: null
) to get the total number of doctor and nurses. - Also here use a
$cond
to$sum
0 if the value is not an array and otherwise the array size. - And then use a
$project
stage to output the sum of these two values.
QUESTION
In the data frame df1, how to convert q1,....q9,q0,...d5 days into day of years?
...ANSWER
Answered 2022-Mar-10 at 17:22IIUC:
QUESTION
I have implemented a Convolutional Neural Network in C and have been studying what parts of it have the longest latency.
Based on my research, the massive amounts of matricial multiplication required by CNNs makes running them on CPUs and even GPUs very inefficient. However, when I actually profiled my code (on an unoptimized build) I found out that something other than the multiplication itself was the bottleneck of the implementation.
After turning on optimization (-O3 -march=native -ffast-math
, gcc cross compiler), the Gprof result was the following:
Clearly, the convolution2D
function takes the largest amount of time to run, followed by the batch normalization and depthwise convolution functions.
The convolution function in question looks like this:
...ANSWER
Answered 2022-Mar-10 at 13:57Looking at the result of Cachegrind, it doesn't look like the memory is your bottleneck. The NN has to be stored in memory anyway, but if it's too large that your program's having a lot of L1 cache misses, then it's worth thinking to try to minimize L1 misses, but 1.7% of L1 (data) miss rate is not a problem.
So you're trying to make this run fast anyway. Looking at your code, what's happening at the most inner loop is very simple (load-> multiply -> add -> store), and it doesn't have any side effect other than the final store. This kind of code is easily parallelizable, for example, by multithreading or vectorizing. I think you'll know how to make this run in multiple threads seeing that you can write code with some complexity, and you asked in comments how to manually vectorize the code.
I will explain that part, but one thing to bear in mind is that once you choose to manually vectorize the code, it will often be tied to certain CPU architectures. Let's not consider non-AMD64 compatible CPUs like ARM. Still, you have the option of MMX, SSE, AVX, and AVX512 to choose as an extension for vectorized computation, and each extension has multiple versions. If you want maximum portability, SSE2 is a reasonable choice. SSE2 appeared with Pentium 4, and it supports 128-bit vectors. For this post I'll use AVX2, which supports 128-bit and 256-bit vectors. It runs fine on your CPU, and has reasonable portability these days, supported from Haswell (2013) and Excavator (2015).
The pattern you're using in the inner loop is called FMA (fused multiply and add). AVX2 has an instruction for this. Have a look at this function and the compiled output.
QUESTION
Hello!
So I have different (non-numeric) values in Column B (B3:B). And I have transactions (formatted as currency) in Columns C through E (range C3:E). So I want every cell in any given row within that range to be colored, whenever that cell has some value (non-empty) AND the corresponding cell (of the same row) in Column B has "$" value in it.
In other words I need a formula that would check the whole (C3:E) range, find all non-empty cells (assuming that there will be blank cells in that range), check the corresponding (of the same row number) cells in Column B and, if those corresponding cells contain "$" value, color all the non-empty cells in that row (even if there are several non-empty cells in there) within the (C3:E) range.
Let's say we see that in row 7 there are two cells (and they are within our C3:E range) that have values 23.54 and 67.90 (non-empty). That's the first condition. And we also see that the value of the corresponding cell in row 7 of Column B (B7) is "$". That's the second condition. So only cells C7 and E7 (not the whole C7-E7 row) must be colored by conditional formatting. So in the table I provided only cells D4, C7 and E7 must be colored.
That's the custom formula for Conditional Formatting that I came up with =AND(NOT(ISBLANK(C3:E)),AND($B3="$"))
but the problem is that it colors the whole row instead of the non-empty cells in that row only.
Where am I making a mistake?
Please advise.
Column B Column C Column D Column E
3 None 14.50 12.00
4 $ 45.90
5 Some 23.90
6 Few
7 $ 23.54 67.90
P.S: What would the formula be to color the cells that contain anything else but "$" with another color?
ANSWER
Answered 2022-Feb-12 at 17:57try like this:
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