# How to create a range out of a continuous variable in Julia?

I am running the average marginal effects in Julia using the Effects package. My aim is to see how weight change between men and women at different ages. As you can see in the output below, it runs the average marginal effects for each age for man and women. However, I would like to take a range of the age variable and not take each year on itself alone. For example I would like to have the age range of 0:5, 5:10, 10:15 and so on. This has to be done after the regression model is run and not beforehand. I tried to work it on my own, but I am not fluent enough in Julia.

So the only line that needs to be rectified is the following:

``````d1 = Dict(:sex => ["male","female"],:age => [0:5; 6:20])
``````

Here is the code:

``````using DataFrames, Effects, GLM, StatsModels, StableRNGs
rng = StableRNG(42)
growthdata = DataFrame(; age=[13:20; 13:20],
sex=repeat(["male", "female"], inner=8),
weight=[range(100, 155; length=8); range(100, 125; length=8)] .+ randn(rng, 16))

mod_uncentered = lm(@formula(weight ~ 1 + sex * age), growthdata)
d1 = Dict(:sex => ["male","female"],:age => [0:5; 6:20])
ave = effects(d1, mod_uncentered)
``````

OUTPUT

``````sex   age   weight   err    lower   upper
String  Int64   Float64 Float64 Float64 Float64
1   male    0   0.287822    2.88762 -2.5998 3.17545
2   female  0   56.4387 2.88762 53.5511 59.3263
3   male    1   8.00869 2.71603 5.29266 10.7247
4   female  1   59.8481 2.71603 57.1321 62.5641
5   male    2   15.7296 2.54468 13.1849 18.2742
6   female  2   63.2575 2.54468 60.7128 65.8022
7   male    3   23.4504 2.37361 21.0768 25.824
8   female  3   66.6669 2.37361 64.2933 69.0405
9   male    4   31.1713 2.2029  28.9684 33.3742
10  female  4   70.0763 2.2029  67.8734 72.2792
11  male    5   38.8922 2.03264 36.8595 40.9248
12  female  5   73.4857 2.03264 71.4531 75.5184
13  male    6   46.613  1.86295 44.7501 48.476
14  female  6   76.8951 1.86295 75.0322 78.7581
15  male    7   54.3339 1.69399 52.6399 56.0279
16  female  7   80.3046 1.69399 78.6106 81.9985
17  male    8   62.0548 1.52602 60.5288 63.5808
18  female  8   83.714  1.52602 82.1879 85.24
19  male    9   69.7756 1.3594  68.4162 71.135
20  female  9   87.1234 1.3594  85.764  88.4828
21  male    10  77.4965 1.19469 76.3018 78.6912
22  female  10  90.5328 1.19469 89.3381 91.7275
23  male    11  85.2174 1.03282 84.1846 86.2502
24  female  11  93.9422 1.03282 92.9094 94.975
25  male    12  92.9383 0.875345    92.0629 93.8136
26  female  12  97.3516 0.875345    96.4762 98.2269
27  male    13  100.659 0.72515 99.934  101.384
28  female  13  100.761 0.72515 100.036 101.486
29  male    14  108.38  0.587838    107.792 108.968
30  female  14  104.17  0.587838    103.583 1
``````