How do I adjust my Scor column, as I notice that the others are in percentage format, but Scor is not.
df1<-structure(list(Scor = c(7464.65871998132, 7464.65871998132,
7464.65871998132, 6828.03114705642, 6828.03114705642, 4283.33056756974,
4283.33056756974, 4283.33056756974, 4283.33056756974, 4283.33056756974,
2471.01407552018, 2471.01407552018, 1167.72213085951, 1759.83563490657,
2832.42425394852, 2216.93502047899, 2216.93502047899, 2216.93502047899,
2216.93502047899, 2216.93502047899, 2216.93502047899, 2216.93502047899,
2216.93502047899, 2216.93502047899, 2216.93502047899, 1382.78244210074,
1382.78244210074, 1382.78244210074, 1382.78244210074, 225.532020592308,
225.532020592308, 451.757369238554, 451.757369238554, 451.757369238554,
391.4333, 391.4333, 391.4333, 391.4333), Performance = c(0.717983998645269,
0.717983998645269, 0.717983998645269, 0.728999753129052, 0.728999753129052,
0.786965354287025, 0.786965354287025, 0.786965354287025, 0.786965354287025,
0.786965354287025, 0.850074652422915, 0.850074652422915, 0.915840124863607,
0.883139402208456, 0.835366766790403, 0.861211447058532, 0.861211447058532,
0.861211447058532, 0.861211447058532, 0.861211447058532, 0.861211447058532,
0.861211447058532, 0.861211447058532, 0.861211447058532, 0.861211447058532,
0.903336851097558, 0.903336851097558, 0.903336851097558, 0.903336851097558,
0.981191034215198, 0.981191034215198, 0.785270862340655, 0.785270862340655,
0.785270862340655, 0.804079828125457, 0.804079828125457, 0.804079828125457,
0.804079828125388), score = c(0.324701873490657, 0.324701873490657,
0.324701873490657, 0.348051447072024, 0.348051447072024, 0.528241884225376,
0.528241884225376, 0.528241884225376, 0.528241884225376, 0.528241884225376,
0.713363517626057, 0.713363517626057, 0.861245569166058, 0.792956247672247,
0.67415167385565, 0.741455966636511, 0.741455966636511, 0.741455966636511,
0.741455966636511, 0.741455966636511, 0.741455966636511, 0.741455966636511,
0.741455966636511, 0.741455966636511, 0.741455966636511, 0.836255759358446,
0.836255759358446, 0.836255759358446, 0.836255759358446, 0.972845769144406,
0.972845769144406, 0.668098499995622, 0.668098499995622, 0.668098499995622,
0.675298126509343, 0.675298126509343, 0.675298126509343, 0.67529812650932
), Q = c(0.984893346832548, 0.984893346832548, 0.984893346832548,
0.898279272093836, 0.898279272093836, 0.552069187025303, 0.552069187025303,
0.552069187025303, 0.552069187025303, 0.552069187025303, 0.305500984879433,
0.305500984879433, 0.128186286770186, 0.208744159967084, 0.354671346857167,
0.270933172866875, 0.270933172866875, 0.270933172866875, 0.270933172866875,
0.270933172866875, 0.270933172866875, 0.270933172866875, 0.270933172866875,
0.270933172866875, 0.270933172866875, 0.157445543929907, 0.157445543929907,
0.157445543929907, 0.157445543929907, 0, 0, 1, 1, 1, 0.984893346832548,
0.984893346832548, 0.984893346832548, 0.984893346832602)), row.names = c(NA,
38L), class = "data.frame")
> df1
Scor Performance score Q
1 7464.6587 0.7179840 0.3247019 0.9848933
2 7464.6587 0.7179840 0.3247019 0.9848933
3 7464.6587 0.7179840 0.3247019 0.9848933
4 6828.0311 0.7289998 0.3480514 0.8982793
5 6828.0311 0.7289998 0.3480514 0.8982793
6 4283.3306 0.7869654 0.5282419 0.5520692
7 4283.3306 0.7869654 0.5282419 0.5520692
8 4283.3306 0.7869654 0.5282419 0.5520692
9 4283.3306 0.7869654 0.5282419 0.5520692
10 4283.3306 0.7869654 0.5282419 0.5520692
11 2471.0141 0.8500747 0.7133635 0.3055010
12 2471.0141 0.8500747 0.7133635 0.3055010
13 1167.7221 0.9158401 0.8612456 0.1281863
14 1759.8356 0.8831394 0.7929562 0.2087442
15 2832.4243 0.8353668 0.6741517 0.3546713
16 2216.9350 0.8612114 0.7414560 0.2709332
17 2216.9350 0.8612114 0.7414560 0.2709332
18 2216.9350 0.8612114 0.7414560 0.2709332
19 2216.9350 0.8612114 0.7414560 0.2709332
20 2216.9350 0.8612114 0.7414560 0.2709332
21 2216.9350 0.8612114 0.7414560 0.2709332
22 2216.9350 0.8612114 0.7414560 0.2709332
23 2216.9350 0.8612114 0.7414560 0.2709332
24 2216.9350 0.8612114 0.7414560 0.2709332
25 2216.9350 0.8612114 0.7414560 0.2709332
26 1382.7824 0.9033369 0.8362558 0.1574455
27 1382.7824 0.9033369 0.8362558 0.1574455
28 1382.7824 0.9033369 0.8362558 0.1574455
29 1382.7824 0.9033369 0.8362558 0.1574455
30 225.5320 0.9811910 0.9728458 0.0000000
31 225.5320 0.9811910 0.9728458 0.0000000
32 451.7574 0.7852709 0.6680985 1.0000000
33 451.7574 0.7852709 0.6680985 1.0000000
34 451.7574 0.7852709 0.6680985 1.0000000
35 391.4333 0.8040798 0.6752981 0.9848933
36 391.4333 0.8040798 0.6752981 0.9848933
37 391.4333 0.8040798 0.6752981 0.9848933
38 391.4333 0.8040798 0.6752981 0.9848933
CodePudding user response：
You could just do:
library(dplyr)
df1 %>%
mutate(Scor = Scor / max(Scor))