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Getting the value of a Variable which has its name based upon another variable (in R)


Getting the value of a Variable which has its name based upon another variable (in R)

By : user2950977
Date : November 17 2020, 11:58 AM
Any of those help If you have a named list E where each element is length-one, and a constant constant that is also length one, then you can do the operation without a loop.
code :
E <- list(E1 = 300, E2 = 300, E3 = 300, E96 = 300)
constant <- 5
setNames(constant * do.call(c, E), paste0("d", names(E)))
#  dE1  dE2  dE3 dE96 
# 1500 1500 1500 1500 
constant * E
x <- setNames(constant * do.call(c, E), paste0("d", names(E)))
list2env(as.list(x), globalenv())


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Javascript "Variable Variables": how to assign variable based on another variable?

Javascript "Variable Variables": how to assign variable based on another variable?


By : Artur Trofymchuk
Date : March 29 2020, 07:55 AM
will help you I have a set of global counter variables in Javascript: , Looks like an array to me, or am I missing something?
code :
var counters = [0,0,0];

function process(index) {
   ++counters[index]; 
      /* or ++counters[index]+index, not sure what you want to do */
   if (counters[index] === 13) { 
      /* do stuff */ 
   }
}
How to extract an atomic value from a message based variable and assign to an output variable using XPATH

How to extract an atomic value from a message based variable and assign to an output variable using XPATH


By : javadavinci
Date : March 29 2020, 07:55 AM
I wish this help you For anyone who does come across a similar problem, i have solved this query as follows:
To extract atomic values from the output message variable of an invoked service you can use
code :
<bpel:copy>
<bpel:from>
    <![CDATA[count(bpel:getVariableData(‘$Variable','$partName')/ns:return)]]>
</bpel:from>
<bpel:to variable="itemCount"></bpel:to>
</bpel:copy>
AS3 Advanced Variable Usage - Retrieve Value In Variable Selected Based On Value In Another Variable

AS3 Advanced Variable Usage - Retrieve Value In Variable Selected Based On Value In Another Variable


By : a.e
Date : March 29 2020, 07:55 AM
seems to work fine Generally not a fan of having data-defining element names in XML, but - assuming event.dat is actually an XML object, and not an arbitrary object that you've manually parsed the XML into (can't tell from the question) - this is really a question about ECMAScript for XML (E4X) rather than variables in general.
If so, this should work:
code :
for each (var menuField:XML in event.dat.child(mnVariable).element)
{
   // Do something
}
// Note, no dot before the indexer:
for each (var menuField:XML in event.dat[mnVariable].element)
{
   // Do something
}
How to group by a Variable A to get a minimum value from Variable B based on a condition on Variable C

How to group by a Variable A to get a minimum value from Variable B based on a condition on Variable C


By : user2234724
Date : March 29 2020, 07:55 AM
it should still fix some issue I have a data of 3 variables A, B, C. I need to group by on A and need a minimum value of B when C is non-zero. , We group by 'A', get the min of 'B' where 'C' is not 0
code :
library(dplyr)
df1 %>% 
   group_by(A) %>% 
   summarise(B = min(B[C > 0]))
# A tibble: 2 x 2
#  A         B
#   <chr> <int>
#1 a         6
#2 b        12
df1 %>%
   filter(C > 0) %>%
   group_by(A) %>%
   summarise(B = min(B))
library(data.table)
setDT(df1)[,.(B = min(B[C > 0])) , A]
df1 <- structure(list(A = c("a", "a", "a", "a", "b", "b", "b", "b"), 
B = c(3L, 6L, 9L, 12L, 3L, 6L, 9L, 12L), C = c(0L, 1L, 2L, 
2L, 0L, 0L, 0L, 4L)), class = "data.frame", row.names = c("1", 
 "2", "3", "4", "5", "6", "7", "8"))
In pyspark, group based on a variable field, and add a counter for particular values (which resets when variable changes

In pyspark, group based on a variable field, and add a counter for particular values (which resets when variable changes


By : user2966236
Date : March 29 2020, 07:55 AM
it should still fix some issue Pyspark doesn't have a shift function, but you could work with the lag window function which gives you the row before the current row. The first window (called w) sets the value of the val column to 1 if the value of the pos_neg column is True and the value of the previous pos_neg is False and to 0 otherwise. With the second window (called w2) we calculate the cumulative sum to get your desired
code :
import pandas as pd
import pyspark.sql.functions as F
from pyspark.sql import Window

df = pd.DataFrame({"b": ['A','A','A','A','B', 'B','B','C','C','D','D', 'D','D','D','D','D','D','D','D','D'],"Sno": [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20],"a": [3,-4,2, -1, -3, -1,-7,-6, 1, 1, -1, 1,4,5,-3,2,3,4, -1, -2]})

df2=spark.createDataFrame(df) 

w = Window.partitionBy('b').orderBy('Sno')
w2 = Window.partitionBy('b').rowsBetween(Window.unboundedPreceding, 0).orderBy('Sno')

df2 = df2.withColumn("pos_neg",col("a") <0)

df2 = df2.withColumn('val', F.when((df2.pos_neg == True) & (F.lag('pos_neg', default=False).over(w) == False), 1).otherwise(0))
df2 = df2.withColumn('val',  F.sum('val').over(w2))

df2.show()
+---+---+---+-------+---+ 
|Sno|  a|  b|pos_neg|val| 
+---+---+---+-------+---+ 
|  5| -3|  B|   true|  1| 
|  6| -1|  B|   true|  1| 
|  7| -7|  B|   true|  1| 
| 10|  1|  D|  false|  0| 
| 11| -1|  D|   true|  1| 
| 12|  1|  D|  false|  1| 
| 13|  4|  D|  false|  1| 
| 14|  5|  D|  false|  1| 
| 15| -3|  D|   true|  2| 
| 16|  2|  D|  false|  2| 
| 17|  3|  D|  false|  2| 
| 18|  4|  D|  false|  2| 
| 19| -1|  D|   true|  3| 
| 20| -2|  D|   true|  3| 
|  8| -6|  C|   true|  1| 
|  9|  1|  C|  false|  1| 
|  1|  3|  A|  false|  0| 
|  2| -4|  A|   true|  1| 
|  3|  2|  A|  false|  1| 
|  4| -1|  A|   true|  2| 
+---+---+---+-------+---+
    b  Sno  a   pos_neg  val_2
0   A    1  3  False      0
1   A    2 -4   True      1
2   A    3  2  False      1
3   A    4 -1   True      2
4   A    5 -5   True      2
    b  Sno  a   pos_neg  val_2
0   A    1  3  False      0
1   A    3  2  False      0
2   A    2 -4   True      1
3   A    4 -1   True      1
4   A    5 -5   True      1
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