I have a big data.frame (`TOTAL`

) with some values (cols11-16) that I need to subtract a base from which is multiplied by a value depending on two conditions in `TOTAL`

.

The data.frame (`TOTAL`

) looks a little like this

```
Channel Hour Category cols11 cols12 cols13 cols14 cols15 base
TV1 01:00:00 New 2 5 4 5 6 2.4
TV5 23:00:00 Old 1 5 3 9 7 1.8
TV1 02:00:00 New 8 7 9 2 4 5.4
```

There are 4 different channels, and 24 different hours (`00:00:00-23:00:00`

)

I have four other vectors with the conditionedvariable that needs to be multiplied on the base depending on the Hour and the Channel, So for each channel I have a vector like this:

```
TV1Slope:
TV1Slope00 TV1Slope01 TV1Slope02.. TV1Slope23
0.0012 0.0015 0.013 0.0009
TV5Slope:
TV5Slope00 TV5Slope01 TV5Slope02.. TV5Slope23
0.0032 0.0023 0.016 0.002
TOTAL$Uplift0 <- (TOTAL$cols11 - TOTAL$base * conditionedvariable)
TOTAL$Uplift1 <- (TOTAL$cols12 - TOTAL$base * conditionedvariable)
TOTAL$Uplift2 <- (TOTAL$cols13 - TOTAL$base * conditionedvariable)
TOTAL$Uplift3 <- (TOTAL$cols14 - TOTAL$base * conditionedvariable)
TOTAL$Uplift4 <- (TOTAL$cols15 - TOTAL$base * conditionedvariable)
```

How do I make R choose the conditioned variable based on the conditions?

For example:

For `TOTAL$Uplift0`

I will get:

```
cols11 - base * conditionedvariable
```

For the first row where Channel is TV1 and hour is `01:00:00: 2 - 2.4 *0.0015`

For the second row where Channel is TV5 and hour is `23:00:00: 1 - 1.8 *0.002`

For the third row where Channel is TV1 and hour is `02:00:00: 8 - 5.4 *0.013`

Answer:

We `paste`

the 'Channel' and `substring`

of 'Hour' column together ('nm1'), concatenate the 'TV1Slope' and 'TV5Slope' vectors ('TV15'), `match`

the 'nm1 vector with names of 'TV15' after removing the 'Slope' substring with `sub`

, and get the corresponding 'TV15' value. Subset the columns with names starting with 'cols' using `grep`

, do the calculation, and assign it to new columns ('nm2').

```
nm1 <- with(TOTAL, paste0(Channel, substr(Hour, 1,2)))
TV15 <- c(TV1Slope, TV5Slope)
val <- TV15[match(nm1, sub('Slope', '', names(TV15)))]
indx <- grep('^cols', names(TOTAL))
nm2 <- paste0('Uplift',seq_along(indx)-1)
TOTAL[nm2] <- TOTAL[indx]-(TOTAL$base*val)
TOTAL
# Channel Hour Category cols11 cols12 cols13 cols14 cols15 base Uplift0
#1 TV1 01:00:00 New 2 5 4 5 6 2.4 1.9946026
#2 TV5 23:00:00 Old 1 5 3 9 7 1.8 0.9823184
#3 TV1 02:00:00 New 8 7 9 2 4 5.4 7.9619720
# Uplift1 Uplift2 Uplift3 Uplift4
#1 4.994603 3.994603 4.994603 5.994603
#2 4.982318 2.982318 8.982318 6.982318
#3 6.961972 8.961972 1.961972 3.961972
```

NOTE: Created reproducible 'TV1Slope' and 'TV5Slope' examples

```
TOTAL <- structure(list(Channel = c("TV1", "TV5", "TV1"), Hour = c("01:00:00",
"23:00:00", "02:00:00"), Category = c("New", "Old", "New"), cols11 = c(2L,
1L, 8L), cols12 = c(5L, 5L, 7L), cols13 = c(4L, 3L, 9L), cols14 = c(5L,
9L, 2L), cols15 = c(6L, 7L, 4L), base = c(2.4, 1.8, 5.4)), .Names = c("Channel",
"Hour", "Category", "cols11", "cols12", "cols13", "cols14", "cols15",
"base"), class = "data.frame", row.names = c(NA, -3L))
set.seed(24)
TV1Slope <- setNames(runif(24)/100, sprintf('TV1Slope%02d', 0:23))
set.seed(29)
TV5Slope <- setNames(runif(24)/100, sprintf('TV5Slope%02d', 0:23))
```

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