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find column value and name based on minimum value in other column


By : Nada Sharshera
Date : September 15 2020, 05:00 AM
I think the issue was by ths following , I cannot guarantee whether this is a solution efficient enough for your working data, but this is what I would try first:
code :
m1 <- as.matrix(dt[, grep('^t', names(dt)), with = FALSE])
m2 <- as.matrix(dt[, grep('^p', names(dt)), with = FALSE])

t_min <- apply(m1, 1, min, na.rm = TRUE)
t_min[is.infinite(t_min)] <- NA_real_
p_min_index <- rep(NA_integer_, length(t_min))
p_min_index[!is.na(t_min)] <- apply(m1[!is.na(t_min), ], 1, which.min)

dt[, t_min  := t_min]
dt[, p_min := m2[cbind(seq_len(nrow(m2)), p_min_index)] ]
dt[, p_min_col := grep('^p', names(dt), value = TRUE)[p_min_index] ]


#    p1 p2   p3 t1 t2 t3 t_min p_min p_min_col
# 1:  a  b    z  1  7  8     1     a        p1
# 2:  b  c    x  2  6  3     2     b        p1
# 3:  c  d <NA>  3  5 NA     3     c        p1
# 4:  d  a <NA> NA NA NA    NA  <NA>      <NA>
# 5:  e  f    y  5  3  2     2     y        p3
# 6:  f  g <NA>  6  2 NA     2     g        p2
# 7:  g  h    s  7 NA  1     1     s        p3


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How to find minimum and maximum values in Column B based on a specific string in column A?


By : Bdbf
Date : March 29 2020, 07:55 AM
wish help you to fix your issue I have a list of items in Column A and have corresponding year and month values in Column B and C respectively. I am looking to find the minimum and maximum year in Column B (based on specific value in Column A), then find the corresponding month in Column C (only for max and min value) and then generate and fill in a Start and End date in Column E and F respectively. E.g. IF @Item = Laptop THEN FIND MIN,MAX of @YEAR and THEN FIND adjacent value in @Month. Finally formulate and display a date accordingly. Could i achieve this using a formula or is it out of scope and is better achieved using a macro? , For the Start date, in E2:
code :
=IF(A2<>A1,DATE(AGGREGATE(15,6,$B$1:$B$1000/($A$1:$A$1000=A2),1),AGGREGATE(15,6,$C$1:$C$1000/(($A$1:$A$1000=A2)*($B$1:$B$1000 = AGGREGATE(15,6,$B$1:$B$1000/($A$1:$A$1000=A2),1))),1),1),"")
=IF(A2<>A1,EOMONTH(DATE(AGGREGATE(14,6,$B$1:$B$1000/($A$1:$A$1000=A2),1),AGGREGATE(14,6,$C$1:$C$1000/(($A$1:$A$1000=A2)*($B$1:$B$1000 = AGGREGATE(14,6,$B$1:$B$1000/($A$1:$A$1000=A2),1))),1),1),0),"")
=IF(A2<>A1,AGGREGATE(15,6,DATE($B$1:$B$1000,$C$1:$C$1000,1)/($A$1:$A$1000=A2),1),"")
=IF(A2<>A1,AGGREGATE(14,6,EOMONTH(DATE($B$1:$B$1000,$C$1:$C$1000,1),0)/($A$1:$A$1000=A2),1),"")

how to read a text file column by column and find the minimum value in every column


By : Rubel Mahmud
Date : March 29 2020, 07:55 AM
may help you . In general, common tasks are often automated / optimised via libraries. The below code uses the numpy library to process your task:
code :
import numpy as np

arr = np.genfromtxt('file.txt', delimiter=',')

arr_colmin = arr.min(axis=0)

using sparksql and spark dataframe How can we find the COLUMN NAME based on the minimum value in a row


By : Pushkar Deodhar
Date : March 29 2020, 07:55 AM
Hope that helps i have a dataframe df . its having 4 columns , you can do something like,
code :
import org.apache.spark.sql.functions._

val cols = df.columns
val u1 = udf((s: Seq[Int]) => cols(s.zipWithIndex.min._2))

df.withColumn("res", u1(array("*")))

Arrayformula to pull the minimum value in a column based on cell contents of another column


By : user2886777
Date : March 29 2020, 07:55 AM
this one helps. I'm trying to find a way to get my minifs formula to work in an arrayformula in google sheets.
code :
=ARRAYFORMULA(TO_DATE(IFERROR(VLOOKUP(A2:A, 
 SORT(QUERY(Data!A2:C, "where B = 'Departure'"), 1, 1, 3, 1), 3, 0))))

How to find minimum value in a column based on condition in an another column of a dataframe?


By : Jaryt23
Date : March 29 2020, 07:55 AM
I wish this help you I have a dataframe like below: , If possible value 15 is not in data, use general solution:
code :
df = df.reset_index(drop=True)
out = df.loc[df.Req.eq(15)[::-1].cumsum().ne(0), 'Response'].sort_values()
print (out)
1    0
3    3
2    4
0    6
Name: Response, dtype: int64

print (next(iter(out), 'no match'))
0
print (df.Req.eq(15))
0    False
1    False
2    False
3     True
4    False
Name: Req, dtype: bool

print (df.Req.eq(15)[::-1])
4    False
3     True
2    False
1    False
0    False
Name: Req, dtype: bool

print (df.Req.eq(15)[::-1].cumsum())
4    0
3    1
2    1
1    1
0    1
Name: Req, dtype: int32

print (df.Req.eq(15)[::-1].cumsum().ne(0))
4    False
3     True
2     True
1     True
0     True
Name: Req, dtype: bool
print (df)
   Number  Req  Response
0       0    3         6
1       1    5         0
2       2   33         4
3       3  150         3
4       4   12         2


df = df.reset_index(drop=True)
out = df.loc[df.Req.eq(15)[::-1].cumsum().ne(0), 'Response'].sort_values()
print (out)
Series([], Name: Response, dtype: int64)

print (next(iter(out), 'no match'))
no match
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