Make connections between two datasets - r

Question

I would like to make a connection between the x and df2 datasets. Notice that the dataset x, I have a percentage value, which in this case for the day 03-01-2021 is 0.1 and for the days 01-02-2021 and 01-01-2022 it is 0.45. So from that information, I know the percentage value for 03-01-2021 is 0.1, so this value falls into category I of my dataset df2 (since the values range from 0.1 to 0.2). As for the days 02-01-2021 and 01-01-2022, they correspond to category F of the df2,since the values range from 0.4 to 0.5. So, I would like to generate an output table as follows:
library(dplyr)
df1<- structure(
list(date2= c("01-01-2022","01-01-2022","03-01-2021","03-01-2021","01-02-2021","01-02-2021"),
Category= c("ABC","CDE","ABC","CDE","ABC","CDE"),
coef= c(5,4,0,2,4,5)),
class = "data.frame", row.names = c(NA, -6L))
x<-df1 %>%
group_by(date2) %>%
summarize(across("coef", sum),.groups = 'drop')%>%
arrange(date2 = as.Date(date2, format = "%d-%m-%Y"))
number<-20
x$Percentage<-x$coef/number
date2 coef Percentage
<chr> <dbl> <dbl>
1 03-01-2021 2 0.1
2 01-02-2021 9 0.45
3 01-01-2022 9 0.45
df2 <- structure(
list(
Category = c("A", "B", "C", "D",
"E", "F", "G", "H", "I", "J"),
From = c(0.9,
0.8, 0.7, 0.6, 0.5, 0.4, 0.3, 0.2, 0.1, 0),
Until = c(
1,
0.8999,
0.7999,
0.6999,
0.5999,
0.4999,
0.3999,
0.2999,
0.1999,
0.0999
),
`1 Val` = c(
2222,
2017.8,
1793.6,
1621.5,
1522.4,
1457.3,
1325.2,
1229.15,
1223.1,
1177.05
),
`2 Val` = c(3200, 2220, 2560,
2200, 2220, 2080, 1220, 1240, 1720, 1620),
`3 Val` = c(
4665,
4122.5,
3732,
3498.75,
3265.5,
3032.25,
2799,
2682.375,
2565.75,
2449.125
),
`4 Val` = c(
6112,
5222.8,
4889.6,
4224,
4278.4,
3972.8,
3667.2,
3224.4,
3361.6,
3222.8
)
),
row.names = c(NA,-10L),
class = c("tbl_df",
"tbl", "data.frame")
)
Category From Until 1 Val 2 Val 3 Val 4 Val
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 A 0.9 1 2222 3200 4665 6112
2 B 0.8 0.900 2018 2220 4122 5223
3 C 0.7 0.800 1794 2560 3732 4890
4 D 0.6 0.700 1622 2200 3499 4224
5 E 0.5 0.600 1522 2220 3266 4278
6 F 0.4 0.500 1457 2080 3032 3973
7 G 0.3 0.400 1325 1220 2799 3667
8 H 0.2 0.300 1229 1240 2682 3224
9 I 0.1 0.200 1223 1720 2566 3362
10 J 0 0.0999 1177 1620 2449 3223

Answer 1

Using tidyverse, we do a rowwise on the 'x' dataset, slice the rows of 'df2' where the 'Percentage' falls between the 'From' and 'Until', and unpack the data.frame/tibble column
library(dplyr)
library(tidyr)
x %>%
rowwise %>%
mutate(out = df2 %>%
slice(which(Percentage>= From &
Percentage <= Until)[1]) %>%
select(-(1:3)) ) %>%
ungroup %>%
unpack(out)
-output
# A tibble: 3 × 7
date2 coef Percentage `1 Val` `2 Val` `3 Val` `4 Val`
<chr> <int> <dbl> <dbl> <dbl> <dbl> <dbl>
1 03-01-2021 2 0.1 1223. 1720 2566. 3362.
2 01-02-2021 9 0.45 1457. 2080 3032. 3973.
3 01-01-2022 9 0.45 1457. 2080 3032. 3973.
Or this could be done with a non-equi join
library(data.table)
nm1 <- names(df2)[endsWith(names(df2), 'Val')]
setDT(x)[setDT(df2), (nm1) := mget(nm1),
on = .(Percentage >= From, Percentage <= Until)]
-output
> x
date2 coef Percentage 1 Val 2 Val 3 Val 4 Val
1: 03-01-2021 2 0.10 1223.1 1720 2565.75 3361.6
2: 01-02-2021 9 0.45 1457.3 2080 3032.25 3972.8
3: 01-01-2022 9 0.45 1457.3 2080 3032.25 3972.8