R: Check If Value from Dataframe Is Within Range Other Dataframe

R: Check if value from dataframe is within range other dataframe

Here's a simple base method that uses the OP's logic:

f <- function(vec, id) {
  if(length(.x <- which(vec >= x$from & vec <= x$to & id == x$number))) .x else NA
}
y$name <- x$name[mapply(f, y$location, y$id_number)]
y
#  location id_number     name
#1      1.5        30 region 1
#2      2.8        30 region 2
#3     10.0        38     <NA>
#4      3.5        40     <NA>
#5      2.0        36 region 7

Check if column value from one dataframe is in between (range) of two other columns of second dataframe

I believe this gives you your desired result:

df1 %>%
  left_join(df2 %>% rename_at(vars(Start, End, sample_id), paste0, "_2")) %>%
  mutate(sample_id_new = case_when(Start < End_2 & Start > Start_2 ~ sample_id_2)) %>% 
  select(Chr, Start, End, Gene, sample_id, sample_id_new)

Output:

  Chr Start End  Gene sample_id sample_id_new
1   1    15  15 gene1       ss6           ss1
2   1   120 130 gene2       ss7           ss1
3   2   210 210 gene3       ss9          <NA>
4   3   210 210 gene3       ss9           ss1
5   4   450 450 gene3      ss10          <NA>

Check if a value in a dataframe is conditionally between a range of values specified by two columns of another dataframe

Use a non-equi join with data.table - convert the first data to data.table (setDT), create the filter column as logical (FALSE) values. Do a non-equi join, and assign (:=) the filter to TRUE, which changes the FALSE to TRUE only when the condition (abs(weight - th_weight) < 2) meets

library(data.table)
setDT(df1)[, filter := FALSE]
df1[df2, filter := abs(weight - th_weight) < 2, 
       on = .(low <= th_weight, high >= th_weight)]

-output

> df1
     weight      low     high filter
      <num>    <num>    <num> <lgcl>
1: 94.99610 94.99608 94.99613   TRUE
2: 95.00561 95.00558 95.00566  FALSE

data

df1 <- structure(list(weight = c(94.9961, 95.00561), low = c(94.99608, 
95.00558), high = c(94.99613, 95.00566)), class = "data.frame", row.names = c(NA, 
-2L))

df2 <- structure(list(index = 1:5, th_weight = c(94.996092, 95.496336, 
95.509906, 97.473292, 100.51906)), class = "data.frame", row.names = c(NA, 
-5L))

Check if column value is in between (range) of two other column values

We can loop over each x$number using sapply and check if it lies in range of any of y$number1 and y$number2 and give the value accordingly.

x$found <- ifelse(sapply(x$number, function(p) 
                 any(y$number1 <= p & y$number2 >= p)),"YES", NA)
x

#  id number found
#1  1   5225   YES
#2  2   2222  <NA>
#3  3   3121   YES

Using the same logic but with replace

x$found <- replace(x$found, 
         sapply(x$number, function(p) any(y$number1 <= p & y$number2 >= p)), "YES")

EDIT

If we want to also compare the id value we could do

x$found <- ifelse(sapply(seq_along(x$number), function(i) {
           inds <- y$number1 <= x$number[i] & y$number2 >= x$number[i]
           any(inds) & (x$id[i] == y$id[which.max(inds)])
           }), "YES", NA)

x$found
#[1] "YES" NA    "YES"

Check if value in a dataframe is between two values in another dataframe

For loop solution use:

for v in df['volumne']:
    df3 = df2[(df2['range_low'] < v) &  (df2['range_high'] > v)]
    print (df3)

For non loop solution is possible use cross join, but if large DataFrames there should be memory problem:

df = df.assign(a=1).merge(df2.assign(a=1), on='a', how='outer')
print (df)
   volumne  a  range_low  range_high  price
0       11  1         10          20      1
1       11  1         21          30      2
2       24  1         10          20      1
3       24  1         21          30      2
4       30  1         10          20      1
5       30  1         21          30      2

df3 = df[(df['range_low'] < df['volumne']) &  (df['range_high'] > df['volumne'])]
print (df3)
   volumne  a  range_low  range_high  price
0       11  1         10          20      1
3       24  1         21          30      2

How to check if a column value is within a range of another two for each row in data table

This works idiomatically in data.table

dat[, inConf := ifelse(true >= low & true <= up,T,F)]

###alternatively with 0,1
dat[, inConf := ifelse(true >= low & true <= up,1,0)]

R: find rows in data frame within range of each other across multiple columns

You can check all the conditions using outer to form a logical matrix (remembering to exclude the self-matching diagonal), and apply the result to subset the ID column, pasting the result together into strings:

df$ID.matches <- apply(outer(df$lat,   df$lat,   function(x, y) abs(x - y) <   1) &
                       outer(df$lon,   df$lon,   function(x, y) abs(x - y) <   1) &
                       outer(df$score, df$score, function(x, y) abs(x - y) < 0.7) &
                       diag(nrow(df)) == 0, 
                       MARGIN = 1,
                       function(x) paste(df$ID[x], collapse = ", "))
df
#>   ID  lat  long score ID.matches
#> 1  1 41.5 -62.3  22.4       3, 7
#> 2  2 41.0 -70.2  21.9           
#> 3  3 42.2 -63.0  22.7          1
#> 4  4 36.7 -72.9  20.0           
#> 5  5 36.2 -62.4  24.1          6
#> 6  6 35.8 -61.7  24.7          5
#> 7  7 40.8 -61.9  22.1          1

^{Created on 2020-07-07 by the reprex package (v0.3.0)}

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