Canovice - 1 year ago 60

R Question

My last few posts have been written poorly, so I will attempt to do a better and cleaner job this time.

I am learning how to work with the data tables object, and one task I am struggling with is updating values in the data table by both row number and column name at the same time. With data.frames this is much easier and I just do the following:

`my_df = as.data.frame(matrix(ncol = 10, nrow = (100)))`

names(my_df) = c("P1", "P2", "P3", "P4", "P5", "Q1", "Q2", "Q3", "Q4", "Q5")

head(my_df)

P1 P2 P3 P4 P5 Q1 Q2 Q3 Q4 Q5

1 NA NA NA NA NA NA NA NA NA NA

2 NA NA NA NA NA NA NA NA NA NA

3 NA NA NA NA NA NA NA NA NA NA

4 NA NA NA NA NA NA NA NA NA NA

5 NA NA NA NA NA NA NA NA NA NA

6 NA NA NA NA NA NA NA NA NA NA

replacement = c(1, 2, 3, 4, 5)

my_df[2, names(my_df)[1:5]] = replacement

head(my_df)

P1 P2 P3 P4 P5 Q1 Q2 Q3 Q4 Q5

1 NA NA NA NA NA NA NA NA NA NA

2 1 2 3 4 5 NA NA NA NA NA

3 NA NA NA NA NA NA NA NA NA NA

4 NA NA NA NA NA NA NA NA NA NA

5 NA NA NA NA NA NA NA NA NA NA

6 NA NA NA NA NA NA NA NA NA NA

so, fairly easy with a dataframe. however, I am struggling with this same exact task with a datatable. using the same structure for an example data table as i did with the dataframe above, i've tried the following:

`my_dt = data.table(matrix(ncol = 10, nrow = (100)))`

names(my_dt) = c("P1", "P2", "P3", "P4", "P5", "Q1", "Q2", "Q3", "Q4", "Q5")

head(my_dt)

P1 P2 P3 P4 P5 Q1 Q2 Q3 Q4 Q5

1: NA NA NA NA NA NA NA NA NA NA

2: NA NA NA NA NA NA NA NA NA NA

3: NA NA NA NA NA NA NA NA NA NA

4: NA NA NA NA NA NA NA NA NA NA

5: NA NA NA NA NA NA NA NA NA NA

6: NA NA NA NA NA NA NA NA NA NA

replacement = c(1, 2, 3, 4, 5)

# my_dt[i == 2, names(my_dt)[1:5]] = replacement

# my_dt[i == 2, names(my_dt)[1:5] := replacement]

# my_dt[2, names(my_dt)[1:5]] = replacement

# my_dt[2, names(my_dt)[1:5] := replacement]

however none of the four commented lines did the correct substitution. appreciate any help!

Thanks,

Canovice

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Answer Source

Or you can do this:

```
x <- names(my_dt)[1:5]
my_dt[, (x) := lapply(.SD, as.numeric), .SDcols = x]
my_dt[2, (x):= as.list(replacement)]
```

First we convert the target columns in `my_dt`

to `numeric`

. `.SDcols`

represents the subset of columns in `.SD`

that we are interested in. `.SD`

holds all the columns in the `data.table`

(except the ones used in `by`

).

Once we convert the target columns to numeric, we update the values by reference.

**Note**: It is not necessary to define x beforehand, everything can be done on the fly. However, if you define `x`

, you need to wrap it in `()`

to make sure `data.table`

doesn't look for the column `x`

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