Add unique title over multiple plots

General
1

Hello,

I have a large dataset that I'm creating multiple plots from. I want to add the Station ID to each plot so I know what I'm looking at, and I'm using the below code:

dt %>%
  group_by(Station) %>% 
  group_nest() %>% 
  mutate(plot = map(data, ~ {
    ggplot(.x) +
      geom_line(aes(x=Fluorescence, y=Depth), color="purple") +
      geom_line(aes(x=Temp, y=Depth), color="blue") +
      scale_y_reverse() +
      labs(title=Station)
  })) %>% 
  pull(plot)

However, no title is added to the plot using the labs(title=Station) syntax. Anyone have an idea about how to add this? Here is a subset of data:

structure(list(Station = c("EAS_12", "EAS_12", "EAS_12", "EAS_12", 
"EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", 
"EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", 
"EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", 
"EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", 
"EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", 
"EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", 
"EAS_12", "EAS_12", "EAS_12", "EAS_12"), Depth = 1:50, Temp = c(18.7746, 
18.7687, 18.7533, 18.7416, 18.6882, 18.6107, 18.3693, 18.3448, 
17.8788, 17.0901, 15.5886, 14.6714, 13.7687, 12.371, 11.6705, 
10.1561, 9.258, 8.151, 7.7893, 7.4675, 7.4963, 7.2801, 7.1542, 
7.1116, 6.9228, 6.7876, 6.7372, 6.6441, 6.443, 6.167, 5.994, 
5.8535, 5.6925, 5.4511, 5.2827, 5.1845, 4.9938, 4.8475, 4.7535, 
4.6618, 4.6086, 4.5548, 4.5011, 4.4661, 4.4233, 4.3953, 4.3757, 
4.3609, 4.3505, 4.3418), Fluorescence = c(0.0998, 0.0939, 0.0909, 
0.091, 0.0989, 0.1075, 0.1282, 0.1417, 0.1566, 0.2026, 0.2179, 
0.2412, 0.2605, 0.258, 0.2564, 0.262, 0.2726, 0.2803, 0.2846, 
0.3062, 0.3469, 0.3847, 0.4445, 0.5143, 0.5915, 0.7267, 0.7376, 
0.8145, 0.8491, 0.8945, 1.1276, 1.3216, 1.354, 1.3705, 1.3584, 
1.3346, 1.2982, 1.3072, 1.3063, 1.2965, 1.3085, 1.3167, 1.3204, 
1.2697, 1.1402, 0.9836, 0.8965, 0.8197, 0.7904, 0.7429)), row.names = c(NA, 
50L), class = "data.frame")
1 Like
2

Code didn't come through on your post

4

I know, somehow it published before I was ready! Pushes some keys on accident. I've updated it now!

5

There's only one station, so group_by doesn't do anything and the endpoint outputs a single chart of a single station. That much works. Could you explain in more detail the purpose for doing this all at once? Analysis, presentation?

6

Yes, I have to analyze this data visually and not mathematically. I can post a larger part of my dataset in the comments so you can see two stations, if it works. I'll try that.

structure(list(Station = c("EAS_12", "EAS_12", "EAS_12", "EAS_12", 
"EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", 
"EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", 
"EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", 
"EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", 
"EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", 
"EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", 
"EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", 
"EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", 
"EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", 
"EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", 
"EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", 
"EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", 
"EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", 
"EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", 
"EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", 
"EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", 
"EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", 
"EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", 
"EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", 
"EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", 
"EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", "EAS_12", 
"EAS_12", "EAS_12", "EAS_17", "EAS_17", "EAS_17", "EAS_17", "EAS_17", 
"EAS_17", "EAS_17", "EAS_17", "EAS_17", "EAS_17", "EAS_17", "EAS_17", 
"EAS_17", "EAS_17", "EAS_17", "EAS_17", "EAS_17", "EAS_17", "EAS_17", 
"EAS_17", "EAS_17", "EAS_17", "EAS_17", "EAS_17", "EAS_17", "EAS_17", 
"EAS_17", "EAS_17", "EAS_17", "EAS_17", "EAS_17", "EAS_17", "EAS_17", 
"EAS_17", "EAS_17", "EAS_17", "EAS_17", "EAS_17", "EAS_17", "EAS_17", 
"EAS_17", "EAS_17", "EAS_17", "EAS_17", "EAS_17", "EAS_17", "EAS_17", 
"EAS_17", "EAS_17", "EAS_17", "EAS_17", "EAS_17", "EAS_17", "EAS_17", 
"EAS_17", "EAS_17", "EAS_17", "EAS_17", "EAS_17", "EAS_17", "EAS_17", 
"EAS_17", "EAS_17", "EAS_17", "EAS_17", "EAS_17", "EAS_17", "EAS_17", 
"EAS_17", "EAS_17", "EAS_17", "EAS_17", "EAS_17", "EAS_17", "EAS_17", 
"EAS_17", "EAS_17", "EAS_17", "EAS_17", "EAS_17", "EAS_17", "EAS_17", 
"EAS_17", "EAS_17", "EAS_17", "EAS_17", "EAS_17", "EAS_17", "EAS_17", 
"EAS_17", "EAS_17", "EAS_17", "EAS_17", "EAS_17", "EAS_17", "EAS_17", 
"EAS_17", "EAS_17", "EAS_17", "EAS_17", "EAS_17", "EAS_17", "EAS_17", 
"EAS_17", "EAS_17", "EAS_17", "EAS_17", "EAS_17", "EAS_17", "EAS_17", 
"EAS_17", "EAS_17", "EAS_17", "EAS_17", "EAS_17", "EAS_17", "EAS_17", 
"EAS_17", "EAS_17", "EAS_17", "EAS_17", "EAS_17", "EAS_17", "EAS_17", 
"EAS_17", "EAS_17", "EAS_17", "EAS_17", "EAS_17", "EAS_17", "EAS_17", 
"EAS_17", "EAS_17", "EAS_17", "EAS_17", "EAS_17", "EAS_17", "EAS_17", 
"EAS_17", "EAS_17", "EAS_17", "EAS_17", "EAS_17", "EAS_17", "EAS_17", 
"EAS_17", "EAS_17"), Depth = c(1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 
9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 
22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 32L, 33L, 34L, 
35L, 36L, 37L, 38L, 39L, 40L, 41L, 42L, 43L, 44L, 45L, 46L, 47L, 
48L, 49L, 50L, 51L, 52L, 53L, 54L, 55L, 56L, 57L, 58L, 59L, 60L, 
61L, 62L, 63L, 64L, 65L, 66L, 67L, 68L, 69L, 70L, 71L, 72L, 73L, 
74L, 75L, 76L, 77L, 78L, 79L, 80L, 81L, 82L, 83L, 84L, 85L, 86L, 
87L, 88L, 89L, 90L, 91L, 92L, 93L, 94L, 95L, 96L, 97L, 98L, 99L, 
100L, 101L, 102L, 103L, 104L, 105L, 106L, 107L, 108L, 109L, 110L, 
111L, 112L, 113L, 114L, 115L, 116L, 117L, 118L, 119L, 120L, 121L, 
122L, 123L, 124L, 125L, 126L, 127L, 128L, 129L, 130L, 131L, 132L, 
133L, 134L, 135L, 136L, 137L, 138L, 139L, 140L, 141L, 142L, 143L, 
144L, 145L, 146L, 147L, 148L, 149L, 150L, 151L, 152L, 153L, 1L, 
2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 
16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 
29L, 30L, 31L, 32L, 33L, 34L, 35L, 36L, 37L, 38L, 39L, 40L, 41L, 
42L, 43L, 44L, 45L, 46L, 47L, 48L, 49L, 50L, 51L, 52L, 53L, 54L, 
55L, 56L, 57L, 58L, 59L, 60L, 61L, 62L, 63L, 64L, 65L, 66L, 67L, 
68L, 69L, 70L, 71L, 72L, 73L, 74L, 75L, 76L, 77L, 78L, 79L, 80L, 
81L, 82L, 83L, 84L, 85L, 86L, 87L, 88L, 89L, 90L, 91L, 92L, 93L, 
94L, 95L, 96L, 97L, 98L, 99L, 100L, 101L, 102L, 103L, 104L, 105L, 
106L, 107L, 108L, 109L, 110L, 111L, 112L, 113L, 114L, 115L, 116L, 
117L, 118L, 119L, 120L, 121L, 122L, 123L, 124L, 125L, 126L, 127L, 
128L, 129L, 130L, 131L, 132L, 133L, 134L, 135L, 136L, 137L, 138L, 
139L, 140L, 141L, 142L, 143L, 144L, 145L, 146L, 147L), Temp = c(18.7746, 
18.7687, 18.7533, 18.7416, 18.6882, 18.6107, 18.3693, 18.3448, 
17.8788, 17.0901, 15.5886, 14.6714, 13.7687, 12.371, 11.6705, 
10.1561, 9.258, 8.151, 7.7893, 7.4675, 7.4963, 7.2801, 7.1542, 
7.1116, 6.9228, 6.7876, 6.7372, 6.6441, 6.443, 6.167, 5.994, 
5.8535, 5.6925, 5.4511, 5.2827, 5.1845, 4.9938, 4.8475, 4.7535, 
4.6618, 4.6086, 4.5548, 4.5011, 4.4661, 4.4233, 4.3953, 4.3757, 
4.3609, 4.3505, 4.3418, 4.3272, 4.3139, 4.3064, 4.3029, 4.2898, 
4.2713, 4.2593, 4.2475, 4.2317, 4.2251, 4.2171, 4.2073, 4.197, 
4.191, 4.1843, 4.1799, 4.1734, 4.1674, 4.1632, 4.1612, 4.1591, 
4.1545, 4.1492, 4.1397, 4.1379, 4.1348, 4.1292, 4.1193, 4.1184, 
4.119, 4.1183, 4.1143, 4.1077, 4.1, 4.0952, 4.0908, 4.0886, 4.0888, 
4.0892, 4.0895, 4.0914, 4.0911, 4.0903, 4.0912, 4.0946, 4.0971, 
4.0983, 4.1003, 4.1009, 4.1003, 4.0995, 4.0998, 4.1007, 4.1004, 
4.1008, 4.101, 4.1014, 4.1015, 4.1019, 4.1032, 4.1044, 4.1051, 
4.1046, 4.103, 4.1029, 4.1036, 4.1019, 4.1006, 4.0989, 4.0987, 
4.1029, 4.0996, 4.1011, 4.1037, 4.1052, 4.1084, 4.1079, 4.1086, 
4.1084, 4.1079, 4.1075, 4.1082, 4.1081, 4.1083, 4.1124, 4.1117, 
4.1099, 4.1125, 4.1127, 4.1154, 4.1143, 4.1126, 4.108, 4.1098, 
4.11, 4.1121, 4.1116, 4.1145, 4.1172, 4.1181, 4.1161, 4.1171, 
4.121, 18.4878, 18.4746, 18.5229, 18.4212, 18.3943, 18.3733, 
18.3411, 18.2176, 17.9414, 17.4555, 16.18, 14.9804, 13.3937, 
11.7636, 11.0921, 10.6699, 10.0843, 8.9736, 7.9892, 7.4913, 7.2617, 
7.0871, 7.0128, 6.9221, 6.7599, 6.6341, 6.5136, 6.3712, 6.2801, 
6.1685, 6.0082, 5.8485, 5.729, 5.6333, 5.4717, 5.3026, 5.1632, 
5.0257, 4.8574, 4.7827, 4.6718, 4.5718, 4.4484, 4.4005, 4.3672, 
4.3324, 4.3162, 4.2812, 4.2771, 4.2558, 4.2397, 4.2307, 4.2189, 
4.2094, 4.2058, 4.1876, 4.1743, 4.1672, 4.1638, 4.1584, 4.1462, 
4.1373, 4.1344, 4.1246, 4.1161, 4.1117, 4.1096, 4.1074, 4.105, 
4.1028, 4.0992, 4.0971, 4.0942, 4.0902, 4.0828, 4.0726, 4.0583, 
4.0353, 4.0144, 4.0104, 4.0104, 4.0097, 4.0067, 4.0029, 4.0006, 
3.9981, 3.9951, 3.9893, 3.9873, 3.9843, 3.982, 3.9804, 3.9796, 
3.9788, 3.9784, 3.9781, 3.9779, 3.9774, 3.9757, 3.9733, 3.9727, 
3.9731, 3.9735, 3.9724, 3.9721, 3.9696, 3.9658, 3.9664, 3.9663, 
3.9662, 3.9662, 3.966, 3.9656, 3.9655, 3.9652, 3.9649, 3.9647, 
3.9637, 3.9637, 3.9631, 3.9626, 3.9623, 3.9621, 3.9619, 3.9617, 
3.9609, 3.9604, 3.959, 3.957, 3.9557, 3.9553, 3.9545, 3.9544, 
3.9529, 3.9526, 3.9525, 3.9523, 3.9521, 3.9517, 3.9503, 3.9491, 
3.9487, 3.9489, 3.949, 3.9495, 3.9503, 3.9511), Fluorescence = c(0.0998, 
0.0939, 0.0909, 0.091, 0.0989, 0.1075, 0.1282, 0.1417, 0.1566, 
0.2026, 0.2179, 0.2412, 0.2605, 0.258, 0.2564, 0.262, 0.2726, 
0.2803, 0.2846, 0.3062, 0.3469, 0.3847, 0.4445, 0.5143, 0.5915, 
0.7267, 0.7376, 0.8145, 0.8491, 0.8945, 1.1276, 1.3216, 1.354, 
1.3705, 1.3584, 1.3346, 1.2982, 1.3072, 1.3063, 1.2965, 1.3085, 
1.3167, 1.3204, 1.2697, 1.1402, 0.9836, 0.8965, 0.8197, 0.7904, 
0.7429, 0.7245, 0.6713, 0.6399, 0.6327, 0.6302, 0.5921, 0.5646, 
0.5363, 0.5246, 0.5061, 0.4819, 0.4668, 0.4509, 0.4248, 0.4187, 
0.385, 0.3739, 0.357, 0.3326, 0.3205, 0.3112, 0.2998, 0.2895, 
0.2901, 0.2731, 0.2678, 0.2566, 0.2582, 0.2404, 0.2373, 0.2334, 
0.2409, 0.234, 0.2271, 0.2218, 0.2067, 0.1907, 0.1892, 0.1792, 
0.1785, 0.1732, 0.1674, 0.1556, 0.1514, 0.1583, 0.1509, 0.1456, 
0.1414, 0.1301, 0.1235, 0.1251, 0.121, 0.1286, 0.1211, 0.1201, 
0.1201, 0.1201, 0.1201, 0.1201, 0.1201, 0.1201, 0.1201, 0.1089, 
0.1145, 0.1148, 0.1148, 0.12, 0.1264, 0.1093, 0.1157, 0.1266, 
0.1254, 0.1203, 0.1201, 0.1201, 0.113, 0.12, 0.1164, 0.1089, 
0.1133, 0.1145, 0.11, 0.1144, 0.1045, 0.1203, 0.1084, 0.1095, 
0.1095, 0.1095, 0.1095, 0.1218, 0.1082, 0.1095, 0.1095, 0.1095, 
0.1151, 0.1085, 0.1095, 0.1095, 0.1095, 0.1095, 0.1095, 0.107, 
0.4115, 0.3964, 0.1546, 0.1507, 0.1867, 0.2032, 0.2149, 0.244, 
0.2586, 0.2727, 0.3049, 0.34, 0.3468, 0.3505, 0.3581, 0.4198, 
0.4707, 0.5629, 0.6207, 0.6685, 0.7198, 0.7748, 0.8386, 0.8803, 
0.9263, 1.0225, 1.1155, 1.3231, 1.6569, 1.892, 1.935, 1.8194, 
1.66, 1.7276, 1.8128, 1.8603, 1.8191, 1.8115, 1.7708, 1.6854, 
1.682, 1.6613, 1.5363, 1.2808, 1.2094, 1.1176, 1.0056, 0.9536, 
0.8461, 0.8086, 0.7379, 0.6824, 0.641, 0.6038, 0.5917, 0.5715, 
0.5303, 0.5015, 0.4696, 0.4493, 0.4321, 0.4187, 0.412, 0.3905, 
0.3695, 0.3553, 0.3346, 0.3378, 0.3326, 0.3381, 0.3151, 0.3166, 
0.3114, 0.2975, 0.2907, 0.2901, 0.2738, 0.2628, 0.2519, 0.2355, 
0.2179, 0.2147, 0.2157, 0.2111, 0.2002, 0.1998, 0.1875, 0.177, 
0.1738, 0.1644, 0.1626, 0.1486, 0.1516, 0.152, 0.157, 0.1416, 
0.1519, 0.1355, 0.1416, 0.1414, 0.1414, 0.1235, 0.1316, 0.1307, 
0.1307, 0.1307, 0.1434, 0.109, 0.1083, 0.113, 0.1102, 0.1095, 
0.1095, 0.1095, 0.1095, 0.1095, 0.1095, 0.1095, 0.1095, 0.1048, 
0.1042, 0.0994, 0.0989, 0.104, 0.0991, 0.0989, 0.0989, 0.0989, 
0.0989, 0.0931, 0.0936, 0.0876, 0.0943, 0.0872, 0.0883, 0.0883, 
0.0972, 0.0896, 0.0883, 0.0883, 0.0883, 0.0883, 0.0883, 0.0883, 
0.0883, 0.0883, 0.0838)), na.action = structure(c(`4310` = 4310L), class = "omit"), row.names = c(NA, 
300L), class = "data.frame")
7

I found an alternative way to do it using the split and purrr:map2, should anyone need this in the future:

dt %>%
  split(list(.$Station)) %>%
  purrr::map2(.y = names(.),
             ~ ggplot(.) +
               geom_line(aes(x=Fluorescence, y=Depth), color="purple") +
               geom_line(aes(x=Temp, y=Depth), color="blue") +
               scale_y_reverse() +
               labs(title=.y))
1 Like
8

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