For the below stacked 5 datasets, how can I get the average of y by common values of x1 and x2? Note that the size of each data vary (either 4 or 5). This is like merging the 5 datasets by x1, x2 and evaluating the mean of y
Data
x1
x2
y
1
0
0
1
1
1
0
0.96580995
1
4
1
0.9488297
1
6
1
0.93190954
2
0
0
1
2
2
0
0.96580995
2
4
1
0.9488297
2
5
1
0.93190954
2
6
1
0.85664971
3
0
0
0.96580995
3
2
0
0.79060542
3
4
0
0.77424697
3
5
1
0.76613367
3
7
10
0.75801814
4
0
0
1
4
2
0
0.9488297
4
4
1
0.93190954
4
5
1
0.70995093
5
0
0
1
5
2
0
0.67061919
5
4
1
0.66277152
5
5
1
0.65492144
5
6
1
0.63914986
prubin
November 6, 2024, 5:33pm
2
Assuming that your data is in a data frame named df, you can load the dplyr library and run the following:
df2 <- df |> group_by(x1, x2) |> summarize(y_mean = mean(y))
The resulting data frame df2 looks like this:
# A tibble: 8 × 3
# Groups: x1 [7]
x1 x2 y_mean
<dbl> <dbl> <dbl>
1 0 0 0.993
2 1 0 0.966
3 2 0 0.844
4 4 0 0.774
5 4 1 0.873
6 5 1 0.766
7 6 1 0.809
8 7 10 0.758
Thanks so much for the fast response. This is doing exactly what I wanted
As a follow-up to my previous question, how can I get the minimum of y within groups of x1 and x2? for example, the results should be as follows
x1 x2 min_y
0-2 0 x.xxx
3-4 0 x.xxx
0-2 1 x.xxx
etc etc
prubin
November 7, 2024, 4:09pm
5
First create a new column with the x1 grouping (let's call it x1g). Then repeat the previous solution but group by x1g and x2 (or x1g and x2g if you do groupings on both variables) and change mean(y) to min(y).
system
November 14, 2024, 4:09pm
6
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