CODEWITHSUNDEEP
rdataframeunique
Corey
Corey

Reputation: 435

make.unique repeating "unique" values in R

I am having an issue creating unique IDs with make.unique in R. In the output below, instead of make.unique creating AK rows, AK.1, AK.2, AK.3, AK.4, AK.5, AK.6, AK.7, AK.8, AK.9, it seems to not get past AK.2. I'm guessing there might be an issue with how names are grouped before attempting to make unique IDs, or the use of summarize. I've played around with the order that these columns are created, but can't figure out what is going on.

   UniqueID  name  start  end    total_0_5   total_over_5  total_5_19   n    ratio_5_19  ratio_0_5
1  AB        AB    -4490  -3220  14.2500000  79.75000      18.2500000   94   0.22884013  0.17868339
2  AG        AG    -15540 -7050  3.5000000   2.50000       0.5000000    6    0.20000000  1.40000000
3  AI        AI    -3220  -2385  0.7500000   7.25000       1.0000000    8    0.13793103  0.10344828
4  AK        AK    -4730  -4540  0.0000000   5.00000       1.0000000    5    0.20000000  0.00000000
5  AK.1      AK    -4730  -4235  0.0000000   9.00000       2.6666667    9    0.29629630  0.00000000
6  AK.2      AK    -4730  -4050  0.0000000   15.00000      2.0000000    15   0.13333333  0.00000000
7  AK        AK    -4490  -4235  1.0000000   18.00000      2.8888889    19   0.16049383  0.05555556
8  AK.1      AK    -4490  -3750  1.0000000   8.00000       1.0000000    9    0.12500000  0.12500000
9  AK        AK    -4235  -4050  0.0000000   26.00000      0.0000000    26   0.00000000  0.00000000
10 AK.2      AK    -4235  -3750  0.0000000   16.00000      3.8888889    16   0.24305556  0.00000000
11 AK.1      AK    -4050  -3750  0.0000000   23.00000      5.6666667    23   0.24637681  0.00000000
12 AK        AK    -3900  -3750  0.0000000   9.00000       2.0000000    9    0.22222222  0.00000000

I've included the surrounding code in case that is what is introducing errors.

dfsummary <- df %>%
  group_by(name, start, end) %>%
  add_tally() %>%
  summarise(total_0_5 = sum(percent_0_5), total_over_5 = sum(over_5_values), total_5_19 = sum(percent_5_19), n = mean(n)) %>%
  mutate(UniqueID = make.unique(name)) %>%
  rowwise() %>%
  mutate(ratio_5_19 = total_5_19 / total_over_5, ratio_0_5 = total_0_5 / total_over_5) %>%
  select(UniqueID, everything()) %>%
  filter(n > 4)

Here's the data for df. I would have cut it down smaller, but I wanted to make sure there was enough information for the summarize functions to work. 

structure(list(name = c("A", "A", "B", "B", "C", "D", "E", "F", 
"G", "G", "H", "I", "J", "K", "L", "L", "L", "L", "L", "L", "M", 
"M", "N", "N", "O", "P", "P", "Q", "Q", "Q", "Q", "Q", "R", "R", 
"S", "S", "T", "T", "U", "V", "V", "V", "W", "W", "N", "N", "N", 
"N", "N", "X", "X", "X", "X", "X", "X", "X", "X", "X", "X", "X", 
"Y", "Y", "Z", "AA", "AA", "AB", "AB", "AB", "AB", "AB", "AB", 
"AB", "AB", "AB", "AB", "AB", "AB", "AB", "AB", "AB", "AB", "AB", 
"AB", "AB", "AB", "AB", "AB", "AB", "AB", "AB", "AB", "AB", "AB", 
"AB", "AB", "AB", "AB", "AB", "AB", "AB", "AB", "AB", "AB", "AB", 
"AB", "AB", "AB", "AB", "AB", "AB", "AB", "AB", "AB", "AB", "AB", 
"AB", "AB", "AB", "AB", "AB", "AB", "AB", "AB", "AB", "AB", "AB", 
"AB", "AB", "AB", "AB", "AB", "AB", "AB", "AB", "AB", "AB", "AB", 
"AB", "AB", "AB", "AB", "AB", "AB", "AB", "AB", "AB", "AB", "AB", 
"AB", "AB", "AB", "AB", "AB", "AB", "AB", "AB", "AB", "AB", "AB", 
"AC", "AD", "AD", "AD", "AE", "AF", "AF", "AB", "AG", "AG", "AG", 
"AG", "AG", "AG", "AH", "AI", "AI", "AI", "AI", "AI", "AI", "AI", 
"AI", "AJ", "AK", "AK", "AK", "AK", "AK", "AK", "AK", "AK", "AK", 
"AK", "AK", "AK", "AK", "AK", "AK", "AK", "AK", "AK", "AK", "AK", 
"AK", "AK", "AK", "AK", "AK", "AK", "AK", "AK", "AK", "AK", "AK", 
"AK", "AK", "AK", "AK", "AK", "AK", "AK", "AK", "AK", "AK", "AK", 
"AK", "AK", "AK", "AK", "AK", "AK", "AK", "AK", "AK", "AK", "AK", 
"AK", "AK", "AK", "AK", "AK", "AK", "AK", "AK", "AK", "AK", "AK", 
"AK", "AK", "AK", "AK", "AK", "AK", "AK", "AK", "AK", "AK", "AK", 
"AK", "AK", "AK", "AK", "AK", "AK", "AK", "AK", "AK", "AK", "AK", 
"AK", "AK", "AK", "AK", "AK", "AK", "AK", "AK", "AK", "AK", "AK", 
"AK", "AK", "AK", "AK", "AK", "AK", "AK", "AK", "AK", "AK", "AK", 
"AK", "AK", "AK", "AK", "AK", "AK", "AK", "AK", "AK", "AK", "AK", 
"AK", "AK", "AK", "AK", "AK", "AK", "AK", "AK", "AK", "AK", "AK", 
"AK", "AK", "AK", "AK", "AK", "AK", "AK", "AK", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", 
"AL", "AL", "AL", "AL", "AM", "AM", "AM", "AM", "AM", "AM", "AM", 
"AM", "AM", "AM", "AM", "AM", "AM", "AM", "AM", "AM", "AM", "AM", 
"AM", "AM", "AM", "AM", "AM", "AM", "AM", "AM", "AM", "AM", "AM", 
"AM", "AM", "AM", "AM", "AM", "AM", "AM", "AM", "AM", "AM", "AM", 
"AM", "AM", "AM", "AM", "AN", "AN", "AN", "AN", "AN", "AN", "AN", 
"AN", "AN", "AN", "AN", "AN", "AN", "AO", "AO", "AO", "AO", "AO", 
"AO", "AO", "AO", "AO", "AO", "AO", "AO", "AO", "AO", "AO", "AO", 
"AO", "AO", "AO", "AO", "AO", "AO", "AO", "AO", "AO", "AO", "AO", 
"AO", "AP", "AP", "AP", "AP", "AP", "AP", "AP", "AP", "AP", "AP", 
"AP", "AP", "AP", "AP", "AP", "AP", "AP", "AP", "AP", "AP", "AP", 
"AP", "AP", "AP", "AP", "AP", "AP", "AP", "AP", "AQ", "AQ", "AQ", 
"AQ", "AQ", "AQ", "AQ", "AQ", "AR", "AR", "AR", "AR", "AR", "AR", 
"AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", 
"AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", 
"AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", 
"AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", 
"AR", "AR", "AR", "AR", "AR", "AS", "AS", "AS", "AS", "AS", "AS", 
"AS", "AS", "AS", "AS", "AS", "AS", "AS", "AS", "AS", "AS", "AS", 
"AS", "AS", "AS", "AS", "AS", "AS", "AS", "AS", "AS", "AS", "AS", 
"AS", "AS", "AS", "AS", "AS", "AS", "AS", "AS", "AS", "AS", "AT", 
"AT", "AT", "AT", "AT", "AT", "AT", "AT", "AT", "AT", "AT", "AT", 
"AT", "AT", "AT", "AT", "AT", "AT", "AT", "AT", "AT", "AT", "AT", 
"AT", "AT", "AT", "AT", "AT", "AT", "AT", "AT", "AT", "AU", "AU", 
"AU", "AU", "AU", "AU", "AU", "AU", "AV", "AV", "AV", "AV", "AV", 
"AV", "AV", "AV", "AV", "AV", "AV", "AV", "AV", "AV", "AV", "AV", 
"AV", "AV", "AV", "AV", "AV", "AV", "AV", "AW", "AW", "AW", "AW", 
"AW", "AW", "AW", "AW", "AW", "AW", "AW", "AW", "AW", "AW", "AW", 
"AW", "AW", "AW", "AX", "AX", "AX", "AX", "AX", "AX", "AX", "AX", 
"AX", "AX", "AX", "AX", "AX", "AY", "AY", "AY", "AY", "AY", "AY", 
"AY", "AY", "AY", "AY", "AY", "AY", "AY", "AY", "AY", "AY", "AY", 
"AY", "AY", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", 
"AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", 
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"BB", "BB", "BB", "BB", "BB", "BB", "BB", "BB", "BB", "BB", "BB", 
"BB", "BB", "BB", "BB", "BB", "BB", "BB", "BB", "BB", "BB", "BB", 
"BB", "BB", "BB", "BB", "BB", "BB", "BB", "BB", "BB", "BB", "BB", 
"BB", "BB", "BB", "BB", "BB", "BB", "BB", "BB", "BB", "BB", "BB", 
"BB", "BB", "BB", "BB", "BB", "BB", "BC", "BC", "BC", "BC", "BC", 
"BC", "BC", "BC", "BC", "BC", "BC", "BC", "BD", "BD", "BD", "BD", 
"BD", "BD", "BE", "BE", "BE", "BE", "BE", "BE", "BE", "BE", "BF", 
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-4050, -4050, -3750, -3750, -3750, -3750, -3750, -4050, -3750, 
-4050, -4050, -4050, -4050, -3750, -4050, -4050, -4050, -3750, 
-4050, -4235, -4050, -4050, -4235, -3750, -4050, -3750, -4050, 
-4050, -4050, -4050, -4050, -4235, -3750, -3750, -4235, -4235, 
-4235, -4540, -4540, -4050, -3750, -4235, -4235, -4235, -4235, 
-4235, -4050, -4050, -4235, -4235, -4050, -4050, -4540, -4050, 
-4235, -4235, -4050, -4235, -4235, -4050, -4235, -4540, -4235, 
-3900, -3220, -3220, -3220, -3220, -3220, -3220, -3220, -3220, 
-3220, -3220, -3220, -3220, -3220, -3220, -3220, -3220, -3220, 
-3220, -3220, -3220, -3220, -3220, -3220, -3220, -3220, -3220, 
-3220, -3220, -3220, -4235, -4235, -3643, -4235, -4395, -4235, 
-4235, -4235, -4235, -4235, -4235, -4235, -3643, -3220, -3220, 
-3643, -4235, -3643, -3643, -4235, -3643, -4235, -4235, -3220, 
-3220, -3220, -3643, -4395, -4235, -4235, -4235, -4235, -4235, 
-4235, -3643, -4395, -4235, -4235, -4395, -4235, -4235, -3220, 
-4235, -4235, -3220, -3220, -3220, -4050, -4050, -3900, -3900, 
-3900, -3900, -3900, -3900, -3900, -3900, -4050, -4050, -4050, 
-3900, -3900, -3900, -4395, -4490, -4490, -4395, -4395, -4395, 
-4395, -4395, -4395, -4395, -4395, -4395, -4395, -4395, -4395, 
-4395, -4395, -4395, -4395, -4395, -4395, -4395, -4860, -4860, 
-5270, -4860, -4860, -4860, -4860, -4860, -4860, -4860, -4860, 
-4860, -4860, -4860, -4860, -4860, -4860, -4860, -4860, -4860, 
-4860, -4860, -4860, -4860, -4860, -4860, -4860, -4860, -4860, 
-5100, -5100, -5100, -5100, -5100, -5100, -5270, -4860, -3420, 
-4490, -4490, -4490, -4490, -4490, -4490, -4490, -4490, -4490, 
-4490, -4490, -4490, -4490, -4490, -4490, -4490, -4490, -4490, 
-3420, -3420, -3420, -3420, -3420, -3420, -3420, -3420, -3420, 
-3420, -3420, -3420, -3420, -4490, -4490, -4490, -3420, -3900, 
-3420, -3900, -3420, -3900, -3420, -3900, -3420, -3420, -3420, 
-3420, -3420, -4490, -3420, -3420, -3420, -3420, -3420, -3420, 
-3220, -3220, -3220, -3220, -3220, -3220, -3220, -3220, -3220, 
-3220, -3220, -3220, -3220, -3220, -3220, -3420, -3220, -3220, 
-3220, -3220, -3220, -3220, -3220, -3220, -3220, -3220, -3220, 
-3220, -3220, -3420, -3420, -3420, -3220, -3643, -4395, -3420, 
-3900, -3643, -4050, -3900, -3900, -3900, -3900, -3900, -3900, 
-3900, -3900, -3900, -3900, -3900, -3900, -3900, -3900, -3900, 
-3900, -3900, -3900, -3900, -3900, -3900, -3900, -3900, -3900, 
-3900, -3900, -3900, -3900, -3900, -3900, -3900, -3900, -3900, 
-3900, -3900, -3900, -3900, -3900, -3900, -3220, -3420, -3220, 
-4050, -3420, -4050, -4050, -3900, -4050, -4050, -3420, -4050, 
-3370, -4050, -4050, -3420, -4050, -3420, -3420, -3750, -3750, 
-4050, -3525, -4395, -4395, -4395, -4395, -4395, -4050, -4730, 
-4050, -4950, -4950, -4950, -4950, -4050, -4730, -4730, -4730, 
-4860, -4860, -4050, -3900, -3900, -3900, -3900, -3900, -4050, 
-4050, -3900, -3900, -3900, -3900, -4050, -5270, -4490, -4395, 
-4395, -4730, -4395, -4860, -4730, -4540, -4540, -4860, -5270, 
-5270, -4490, -4860, -4395, -4395, -4395, -4395, -4540, -4395, 
-5270, -4860, -5270, -5270, -5270, -5270, -5270, -5270, -4860, 
-4860, -4730, -4860, -4490, -5270, -5270, -4860, -4860, -4860, 
-4860, -4860, -4860, -4730, -4730, -4860, -4540, -4540, -4860, 
-4730, -4730, -4860, -5270, -5270, -5270, -5270, -5270, -5270, 
-5270, -4730, -4540, -4490, -5270, -4860, -4860, -5100, -4395, 
-4730, -4730, -4540, -4540, -4730, -4540, -4860, -4490, -4490, 
-4490, -4490, -4490, -4395, -3900, -3900, -3900, -3900, -3220, 
-3900, -3220, -3900, -4050, -3220, -3900, -3900, -2990, -2385, 
-2385, -3220, -3220, -3420, -3420, -3220, -3220, -3220, -3220, 
-3220, -3220, -3220, -3220, -3220, -3220, -3220, -3220, -3220, 
-3220, -3065, -3220, -3220, -3220, -3220, -3220, -3220, -3220, 
-3220, -3220, -3220, -3220, -3220, -3220, -3220, -3220, -3220, 
-3220, -3220, -3220, -3220, -3130, -3220, -3130, -3130, -3130, 
-3130, -3130, -3130, -3130, -3220, -3220, -3220, -3220, -3220, 
-3900, -3900, -3900, -3900, -4730, -4860, -4730, -4860, -4730, 
-4860, -4730, -4860, -4730, -4730, -4730, -4730, -4860, -5270
), percent_0_5 = c(0, 0, 0, 0, 0, 0, 0.75, 0, 0, 0, 0, 1, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0.75, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.75, 1, 0, 
0, 0, 0, 0, 0.75, 0, 1, 0, 0, 0, 1, 1, 0, 0.75, 0, 0, 0, 0, 0, 
0, 0, 0.75, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.75, 0, 0.75, 0.75, 
0, 0, 0, 0, 0, 0, 0.75, 0, 0, 0.75, 0.75, 0.75, 0.75, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.75, 0, 0, 0, 0, 0, 0, 0.75, 0, 
0, 0.75, 0, 0, 0, 0, 0, 0, 0, 0.75, 0, 0, 0, 0, 0, 0, 0, 0, 0.75, 
0.75, 0, 0.75, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.75, 0.75, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0.75, 0.75, 0, 0, 0, 0, 0, 0, 0.75, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 1, 0.4, 0.4, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0.4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.4, 0, 0, 
0, 0.4, 1, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.4, 0.4, 0, 0, 0, 0, 
0, 0, 0, 0, 0.4, 0, 0, 0, 0, 0, 0.4, 0, 0.4, 0, 0, 0, 0, 0.4, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0.4, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 1, 0, 0, 0, 0.4, 0, 0, 0, 0.4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.8, 0.833333333, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.4, 
0, 0, 0, 0, 0, 0.4, 0, 0.4, 0, 0, 0, 0.4, 0, 0, 0.4, 0, 0, 0.4, 
0, 0, 0, 0, 0.4, 0.4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.4, 
1, 0.4, 0.4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.4, 0, 0, 0, 0, 0, 
0, 0.4, 0, 0.4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0.333333333, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.4, 
0, 1, 0, 0, 0, 0, 0, 0.4, 0, 0, 0, 0, 0, 0.833333333, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.5, 0, 0, 0, 0, 0, 0.266666667, 
0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0.4, 0.4, 0, 0, 0, 0, 0.4, 0, 0, 0, 0.4, 
0, 0, 0, 0, 0.4, 0.4, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0.4, 0, 0, 
0, 0.4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.4, 0, 0), over_5_values = c(1, 
1, 1, 1, 1, 1, 0.25, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0.25, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 0.25, 0, 1, 1, 1, 1, 1, 0.25, 1, 0, 
1, 1, 1, 0, 0, 1, 0.25, 1, 1, 1, 1, 1, 1, 1, 0.25, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 0.25, 1, 0.25, 0.25, 1, 1, 1, 1, 1, 1, 0.25, 
1, 1, 0.25, 0.25, 0.25, 0.25, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 0.25, 1, 1, 1, 1, 1, 1, 0.25, 1, 1, 0.25, 1, 1, 1, 1, 1, 
1, 1, 0.25, 1, 1, 1, 1, 1, 1, 1, 1, 0.25, 0.25, 1, 0.25, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 0.25, 0.25, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
0, 0, 1, 0.25, 0.25, 1, 1, 1, 1, 1, 1, 0.25, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 0, 
1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 
1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 
0, 1, 1, 1, 1, 0, 0.6, 0.6, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0.6, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0.6, 1, 1, 1, 0.6, 0, 1, 1, 1, 
1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 0.6, 0.6, 1, 1, 1, 1, 1, 1, 1, 1, 0.6, 1, 1, 
1, 1, 1, 0.6, 1, 0.6, 1, 1, 1, 1, 0.6, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 0.6, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 0.6, 1, 
1, 1, 0.6, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 0, 0, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 0.2, 0.166666667, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0.6, 1, 1, 1, 1, 1, 0.6, 1, 
0.6, 1, 1, 1, 0.6, 1, 1, 0.6, 1, 1, 0.6, 1, 1, 1, 1, 0.6, 0.6, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0.6, 0, 0.6, 0.6, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 0.6, 1, 1, 1, 1, 1, 1, 0.6, 1, 0.6, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0.666666667, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0.6, 1, 0, 1, 1, 1, 1, 1, 0.6, 
1, 1, 1, 1, 1, 0.166666667, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 0.5, 1, 1, 1, 1, 1, 0.733333333, 1, 1, 1, 1, 1, 1, 1, 0, 
0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
0.6, 0.6, 1, 1, 1, 1, 0.6, 1, 1, 1, 0.6, 1, 1, 1, 1, 0.6, 0.6, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 
1, 1, 1, 0, 1, 1, 1, 1, 1, 0.6, 1, 1, 1, 0.6, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 0.6, 1, 1), percent_5_19 = c(0, 0, 0, 1, 0, 
0, 0.25, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 
0, 0.75, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.25, 0, 0, 1, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0.25, 0, 1, 0, 0, 0, 0, 0.25, 0, 0, 0, 0, 0, 
0, 0, 0, 0.25, 0, 0, 0, 0, 0, 1, 1, 0.25, 1, 0, 0, 0, 0, 0, 0, 
1, 0, 0, 0, 0.25, 1, 0.25, 0.25, 0, 1, 0, 0, 0, 0, 0.25, 1, 0, 
0.25, 0.25, 0.25, 0.25, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0.25, 1, 0, 0, 0, 0, 0, 0.25, 0, 0, 0.25, 0, 0, 0, 0, 0, 0, 0, 
0.25, 0, 0, 0, 0, 0, 0.75, 0, 0, 0.25, 0.25, 1, 0.25, 0, 0, 0, 
1, 0, 1, 0, 0, 0.75, 0.25, 0.25, 0, 1, 0, 0, 0.75, 0, 0, 0, 0, 
0, 0, 0, 0, 0.25, 0.25, 0, 0, 0, 0, 0, 0, 0.25, 0, 0.75, 0, 0, 
1, 0, 0, 0, 0, 0, 0, 0, 0.666666667, 1, 0, 0, 1, 0, 0, 0, 0.888888889, 
1, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 
0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.888888889, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0.666666667, 0, 0, 1, 
1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.333333333, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0.6, 0.6, 0, 0, 0, 0, 0.666666667, 0, 0, 0, 0, 0.6, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0.6, 0, 0, 0, 0.6, 0, 0, 0, 0, 1, 0, 
0, 0, 1, 0, 0, 0, 0, 1, 1, 0, 1, 1, 0, 0, 1, 0, 0, 1, 0, 0, 0, 
0, 0, 0, 0, 0.6, 0.6, 0, 0, 0.333333333, 0, 0, 0, 0, 0, 0.6, 
0.333333333, 0, 0, 0, 0, 0.6, 1, 0.6, 0, 0, 1, 0, 0.6, 0, 0, 
0, 0, 0, 0, 0.333333333, 0, 0, 0.6, 0, 0, 0, 0, 0, 0.666666667, 
0.666666667, 0, 0, 0, 0, 0, 0, 0, 0, 0.6, 0, 0, 0, 0.6, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 
1, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0.2, 
0.166666667, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 
0, 0, 0, 0, 0, 0.6, 0, 0, 0, 0, 0, 0.6, 0, 0.6, 0, 0, 0, 0.6, 
0, 0, 0.6, 0, 0, 0.6, 0, 0, 0, 0, 0.6, 0.6, 0, 0, 0, 0, 0, 1, 
0, 0, 0, 0, 0, 0, 0.6, 0, 0.6, 0.6, 0, 0, 0, 0, 1, 1, 0, 0, 0, 
0, 0.6, 0, 0, 0, 0, 1, 0, 0.6, 0, 0.6, 0, 0.333333333, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0.333333333, 0, 0, 0, 0, 0, 0, 0, 0, 0.666666667, 
0, 0, 0, 0.666666667, 0, 0, 0, 0, 0, 0, 0.6, 0, 0, 0, 0, 1, 0, 
0.333333333, 0.6, 0, 0, 0, 0, 0, 0.166666667, 0, 0, 0, 0, 1, 
0, 0.333333333, 0.666666667, 0, 0, 0, 0, 0, 0.5, 0, 0, 1, 0, 
0, 0.733333333, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.6, 0.6, 0, 0, 0, 
0, 0.6, 0, 0, 0, 0.6, 0, 0, 0, 0, 0.6, 0.6, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0.6, 0, 0, 0, 0.6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0.6, 0, 0)), class = c("tbl_df", "tbl", "data.frame"), row.names = c(NA, 
-824L))

Upvotes: 0

Views: 54

Answers (1)

Ronak Shah
Ronak Shah

Reputation: 388862

I think you need to ungroup before using make.unique. Remember that your data is still grouped by name and start at the make.unique step. summarise drops only the last group from group_by function. 

library(dplyr)

df %>%
  group_by(name, start, end) %>%
  add_tally() %>%
  summarise(total_0_5 = sum(percent_0_5), total_over_5 = sum(over_5_values), 
            total_5_19 = sum(percent_5_19), n = mean(n)) %>%
  ungroup() %>%
  mutate(UniqueID = make.unique(name)) %>%
  rowwise() %>%
  mutate(ratio_5_19 = total_5_19 / total_over_5, 
         ratio_0_5 = total_0_5 / total_over_5) %>%
  select(UniqueID, everything()) %>%
  filter(n > 4)

#   UniqueID name   start   end total_0_5 total_over_5 total_5_19     n ratio_5_19 ratio_0_5
#   <chr>    <chr>  <dbl> <dbl>     <dbl>        <dbl>      <dbl> <dbl>      <dbl>     <dbl>
# 1 AB       AB     -4490 -3220     14.2         79.8       18.2     94      0.229    0.179 
# 2 AG       AG    -15540 -7050      3.5          2.5        0.5      6      0.2      1.4   
# 3 AI       AI     -3220 -2385      0.75         7.25       1        8      0.138    0.103 
# 4 AK       AK     -4730 -4540      0            5          1        5      0.2      0     
# 5 AK.1     AK     -4730 -4235      0            9          2.67     9      0.296    0     
# 6 AK.2     AK     -4730 -4050      0           15          2       15      0.133    0     
# 7 AK.5     AK     -4490 -4235      1           18          2.89    19      0.160    0.0556
# 8 AK.6     AK     -4490 -3750      1            8          1        9      0.125    0.125 
# 9 AK.7     AK     -4235 -4050      0           26          0       26      0        0     
#10 AK.9     AK     -4235 -3750      0           16          3.89    16      0.243    0     
# … with 33 more rows

Upvotes: 2

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