@bkamins How about sampling the dataframe by boolean values. I mean take every column for the row, the the boolean is true?

Like this example:

```
julia> df = DataFrame(rand(3,3), :auto)
3×3 DataFrame
Row │ x1 x2 x3
│ Float64 Float64 Float64
─────┼───────────────────────────────
1 │ 0.045519 0.468771 0.387336
2 │ 0.0133922 0.383619 0.418809
3 │ 0.870746 0.898979 0.628106
```

For example: I want to get every dataframe, at every row where x1 is larger 0.02

I’m not sure I follow the original question, but for the example you can do

```
df[df.x1 .> 0.02, :]
```

to select the subset of rows satisfying the desired criterion.

Alternatively, you can use the subset function:

```
subset(df, :x1 => ByRow(>(0.02)))
```

3 Likes

In DataFramesMeta.jl, this is simply

```
@rsubset df :x1 > .02
```

2 Likes

I think maybe you want this:

```
using Tidier,DataFrames
df = DataFrame(a = [1, 2, missing, 4, 5])
```

## @filter

```
@chain df begin
@filter(a >=2))
end
```

## Conditionals

```
@chain df begin
@mutate(a = if_else(a >= 2, true, false))
end
```