title: Ggplot2 geom_line error
body: <p>I have a daaset which consists of data points over a time series for the proportion of people living in urban/rural areas for a number of countries. Sadly, not all countries have data for the same years. I have been trying to produce a simple line plot to show the different proportions of people living in different locations by year, but as each country has a different number of data points I am running into trouble.</p>
  
  <p>I think this is because some of the countries only have data for a single year and using  <code>geom_line</code> from <code>ggplot2</code> throws the following error:</p>
  
  <blockquote>
    <p>geom_path: Each group consist of only one observation. Do you need to
    adjust the group aesthetic?</p>
  </blockquote>
  
  <p>I was hoping that there would be some way to override this, or perhaps just plot a single point where a COUNTRY only has data for a single year. Does anyone know if this is possible, or indeed, if this is actually what this error means?!!?</p>
  
  <p>Any help greatly appreciated!!!</p>
  
  <p>Thanks</p>
  
  <p>Here is my data:</p>
  
  <pre><code>    structure(list(COUNTRY = structure(c(1L, 2L, 2L, 3L, 3L, 3L, 
  4L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, 7L, 7L, 7L, 
  8L, 8L, 8L, 9L, 9L, 9L, 9L, 9L, 10L, 11L, 12L, 12L, 12L, 12L, 
  12L, 12L, 12L, 12L, 13L, 13L, 13L, 13L, 14L, 14L, 14L, 14L, 1L, 
  2L, 2L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 6L, 6L, 7L, 
  7L, 7L, 7L, 7L, 7L, 8L, 8L, 8L, 9L, 9L, 9L, 9L, 9L, 10L, 11L, 
  12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 13L, 13L, 13L, 13L, 14L, 
  14L, 14L, 14L, 1L, 2L, 2L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 5L, 5L, 
  6L, 6L, 6L, 6L, 7L, 7L, 7L, 7L, 7L, 7L, 8L, 8L, 8L, 9L, 9L, 9L, 
  9L, 9L, 10L, 11L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 13L, 
  13L, 13L, 13L, 14L, 14L, 14L, 14L, 1L, 2L, 2L, 3L, 3L, 3L, 4L, 
  4L, 4L, 4L, 5L, 5L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, 7L, 7L, 7L, 8L, 
  8L, 8L, 9L, 9L, 9L, 9L, 9L, 10L, 11L, 12L, 12L, 12L, 12L, 12L, 
  12L, 12L, 12L, 13L, 13L, 13L, 13L, 14L, 14L, 14L, 14L, 1L, 2L, 
  2L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 6L, 6L, 7L, 7L, 
  7L, 7L, 7L, 7L, 8L, 8L, 8L, 9L, 9L, 9L, 9L, 9L, 10L, 11L, 12L, 
  12L, 12L, 12L, 12L, 12L, 12L, 12L, 13L, 13L, 13L, 13L, 14L, 14L, 
  14L, 14L, 1L, 2L, 2L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 5L, 5L, 6L, 
  6L, 6L, 6L, 7L, 7L, 7L, 7L, 7L, 7L, 8L, 8L, 8L, 9L, 9L, 9L, 9L, 
  9L, 10L, 11L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 13L, 13L, 
  13L, 13L, 14L, 14L, 14L, 14L, 1L, 2L, 2L, 3L, 3L, 3L, 4L, 4L, 
  4L, 4L, 5L, 5L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, 7L, 7L, 7L, 8L, 8L, 
  8L, 9L, 9L, 9L, 9L, 9L, 10L, 11L, 12L, 12L, 12L, 12L, 12L, 12L, 
  12L, 12L, 13L, 13L, 13L, 13L, 14L, 14L, 14L, 14L), class = "factor", .Label = c("Comoros", 
  "Eritrea", "Ethiopia", "Kenya", "Lesotho", "Madagascar", "Malawi", 
  "Namibia", "Rwanda", "South Africa", "Swaziland", "Tanzania", 
  "Zambia", "Zimbabwe")), Year = structure(c(5L, 12L, 4L, 25L, 
  16L, 9L, 22L, 13L, 7L, 2L, 23L, 15L, 22L, 14L, 6L, 1L, 24L, 15L, 
  9L, 1L, 13L, 6L, 19L, 9L, 1L, 24L, 21L, 16L, 9L, 1L, 7L, 19L, 
  24L, 13L, 8L, 5L, 1L, 18L, 10L, 4L, 20L, 11L, 5L, 1L, 24L, 17L, 
  8L, 3L, 5L, 12L, 4L, 25L, 16L, 9L, 22L, 13L, 7L, 2L, 23L, 15L, 
  22L, 14L, 6L, 1L, 24L, 15L, 9L, 1L, 13L, 6L, 19L, 9L, 1L, 24L, 
  21L, 16L, 9L, 1L, 7L, 19L, 24L, 13L, 8L, 5L, 1L, 18L, 10L, 4L, 
  20L, 11L, 5L, 1L, 24L, 17L, 8L, 3L, 5L, 12L, 4L, 25L, 16L, 9L, 
  22L, 13L, 7L, 2L, 23L, 15L, 22L, 14L, 6L, 1L, 24L, 15L, 9L, 1L, 
  13L, 6L, 19L, 9L, 1L, 24L, 21L, 16L, 9L, 1L, 7L, 19L, 24L, 13L, 
  8L, 5L, 1L, 18L, 10L, 4L, 20L, 11L, 5L, 1L, 24L, 17L, 8L, 3L, 
  5L, 12L, 4L, 25L, 16L, 9L, 22L, 13L, 7L, 2L, 23L, 15L, 22L, 14L, 
  6L, 1L, 24L, 15L, 9L, 1L, 13L, 6L, 19L, 9L, 1L, 24L, 21L, 16L, 
  9L, 1L, 7L, 19L, 24L, 13L, 8L, 5L, 1L, 18L, 10L, 4L, 20L, 11L, 
  5L, 1L, 24L, 17L, 8L, 3L, 5L, 12L, 4L, 25L, 16L, 9L, 22L, 13L, 
  7L, 2L, 23L, 15L, 22L, 14L, 6L, 1L, 24L, 15L, 9L, 1L, 13L, 6L, 
  19L, 9L, 1L, 24L, 21L, 16L, 9L, 1L, 7L, 19L, 24L, 13L, 8L, 5L, 
  1L, 18L, 10L, 4L, 20L, 11L, 5L, 1L, 24L, 17L, 8L, 3L, 5L, 12L, 
  4L, 25L, 16L, 9L, 22L, 13L, 7L, 2L, 23L, 15L, 22L, 14L, 6L, 1L, 
  24L, 15L, 9L, 1L, 13L, 6L, 19L, 9L, 1L, 24L, 21L, 16L, 9L, 1L, 
  7L, 19L, 24L, 13L, 8L, 5L, 1L, 18L, 10L, 4L, 20L, 11L, 5L, 1L, 
  24L, 17L, 8L, 3L, 5L, 12L, 4L, 25L, 16L, 9L, 22L, 13L, 7L, 2L, 
  23L, 15L, 22L, 14L, 6L, 1L, 24L, 15L, 9L, 1L, 13L, 6L, 19L, 9L, 
  1L, 24L, 21L, 16L, 9L, 1L, 7L, 19L, 24L, 13L, 8L, 5L, 1L, 18L, 
  10L, 4L, 20L, 11L, 5L, 1L, 24L, 17L, 8L, 3L), class = "factor", .Label = c("1992", 
  "1993", "1994", "1995", "1996", "1997", "1998", "1999", "2000", 
  "2000/1", "2001/2", "2002", "2003", "2003/4", "2004", "2005", 
  "2005/6", "2006", "2006/7", "2007", "2007/8", "2008/9", "2009", 
  "2010", "2011")), location = structure(c(1L, 1L, 1L, 1L, 1L, 
  1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
  1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
  1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 
  2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
  2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
  2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 
  3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
  3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
  3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 
  4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
  4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
  4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 
  5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 
  5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 
  5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 
  6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 
  6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 
  6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, 7L, 7L, 
  7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 
  7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 
  7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L), .Label = c("Urban", 
  "Rural", "Total", "Capital.City", "Other.Cities.towns", "Urban.Non.slum", 
  "Urban.Slum"), class = "factor"), percent = c(63.0434782608696, 
  93.8, 87, 79.5642604795185, 65.4240807416892, 63.0791092522326, 
  90.448386469558, 85.9419999774024, 92.7603614781794, 84.0437368780105, 
  89.9792286718626, 91.0916571421351, 87.1132950026762, 73.8624315865239, 
  60.8311005575454, 66.7, 96, 86.8, 90.6243926153181, 90.6911141749493, 
  90.7602286016099, 93.0377175475414, 86.073106379954, 84.253722056373, 
  77.8178199148702, 97.3, 91.8332260789258, 89.612164524266, 89.9070989918367, 
  94.9, 85.1351949905457, 94.8358752154967, 92.9, 89.656599879838, 
  90.2634019334124, 94.4, 91.6241263241579, 76.7337303943862, 68.4233513070184, 
  74.15601627144, 88.4802888646634, 85.4643913454376, 89.7457528950664, 
  81.3025210084024, 83.0579155525397, 71.5857386620092, 86.2324062094295, 
  87.687478493975, 63.5379061371841, 78.5, 40.7, 51.7763728811622, 
  32.2441768813334, 22.3138981723172, 83.3699691175754, 69.6742912391579, 
  76.0526239692028, 83.7290062290807, 77.4758329101792, 83.8081963934296, 
  67.5805226154664, 55.8951299980461, 41.9921451192584, 52.2, 92.5, 
  77.6, 82.0322170392223, 85.2850090044269, 70.8031150919282, 47.108593681531, 
  82.2215412952297, 78.3643348536815, 74.4253468485616, 94.8, 90.1711142192198, 
  85.0338348718722, 86.3134329333052, 90.4, 79.2813256726705, 90.7077549957666, 
  82.5, 77.7236217339155, 75.3278238729086, 77.7, 78.4592126267142, 
  67.1145693585691, 55.3459024734839, 57.8463881286199, 83.5604620304044, 
  83.9259722574938, 84.4589780509803, 73.3992444632325, 77.544833952707, 
  63.0503715222555, 75.6808008503601, 85.6943513045284, 63.4, 84.2, 
  51, 55.7151220012609, 34.9, 26.6, 85, 72.5, 79.2, 83.8, 80.3, 
  84.9, 69.6, 59, 46, 54, 93, 78.7, 83.2, 85.9, 76.7, 57.5, 83.8, 
  80.4, 75.6, 95, 90.4, 85.6, 86.9, 90.6, 82.2, 91.5, 84.5, 79.9, 
  78.1, 80.9, 81.2, 68.1, 56.8, 59.6, 84.9, 84.4, 86.5, 77, 79.1337842548663, 
  65.6, 79.1, 86.3, 68.421052631579, 96.1, 93.3, 93.461209969107, 
  82.2712525836501, 88.2708936990495, 87.6298001816506, 87.6386027991385, 
  93.1818181818183, 86.6666666666668, 88.1030398041979, 90.4761904761904, 
  83.4297434324662, 86.3744073211853, 83.6107223166148, 78.3, NA, 
  72.8, 80.952380952381, 87.5, 96.9073193030442, 99.1348508752745, 
  85.5297651573129, 86.4793919321843, 79.4520547945208, 98.2, 92.4613307718678, 
  85.4590408924955, 83.9378238341966, 92.1, 81.1594202898552, 96.0232554251852, 
  NA, 88.0377726639494, 83.690767555447, 93.4, 90.0349966633017, 
  71.2508707571865, 72, 79.4082828804656, 91.8032786885246, 84.5238095238095, 
  87.8787878787881, 75.6097560975609, 81.0643061692494, 68.4708412135189, 
  84.9056603773584, 89.5522388059702, 61.6438356164384, 91.7, 79.5, 
  77.0004220956012, 61.061381883032, 58.756042602018, 91.2594694272412, 
  85.20149612163, 92.4956062313464, 82.622382662868, 91.4036416540165, 
  91.6169313256523, 89.2957214499669, 67.6757501795213, 48.1479760952102, 
  NA, NA, 94.2, 94.3553068539161, 91.8799748693178, 89.3739230258784, 
  92.1418739343887, 86.4757947454868, 81.0102236379536, 77.0100025126874, 
  NA, 91.3720851411616, 92.2, 92.5003150086683, 97.8260869565219, 
  87.1461797069698, 93.5168077834096, NA, 90.1780793791367, 92.9758067301415, 
  94.9, 91.8829499602467, 81.749280834314, 65.1853441661798, 69.0503609949116, 
  87.2562445664681, 85.8298270239758, 90.6673511683335, 83.2861189801694, 
  84.9006282245266, 73.65452177457, 87.3075692692965, 85.5310215524833, 
  83.3333333333333, NA, NA, 98.5990187756088, 84.4640706359058, 
  NA, 93.9158337759274, 91.5744358611439, 100, NA, NA, NA, 88.7824144772468, 
  85.1972665683085, 89.54493171236, NA, NA, 89.8, NA, 100, 97.6261376125643, 
  96.3196943955923, 92.0952338262334, 87.9266080431752, 80.9429968520701, 
  NA, NA, 92.8, 95.2886158200472, 100, 86.4199793410402, NA, NA, 
  89.9001648604344, NA, NA, 91.5033109800214, 83.8918470610424, 
  73.9339911532972, 88.6921281548131, 94.309068022859, 85.3299585067346, 
  93.7362934447331, 86.5384615384618, 83.7424288707868, NA, 86.3836615391687, 
  88.1866796344726, 58.1081081081081, NA, NA, 75.7976468146464, 
  62.1289432084197, NA, 88.1488735873722, 84.2108238885019, 89.8335978405451, 
  NA, NA, NA, 86.9222656846515, 70.3584041024493, 70.9023609260137, 
  NA, NA, 85.9, NA, 89.8689917369566, 90.3864925686512, 92.628169473785, 
  80.9468895007753, 78.7885741638367, 75.4005791241575, NA, NA, 
  88.4, 87.7139456942162, 92.3809523809525, 83.7645232075473, NA, 
  NA, 89.567507133125, NA, NA, 91.6433898994358, 73.6225283043976, 
  65.9223049858496, 72.3148320483822, 86.2596215693035, 85.6224026570651, 
  87.4940330171337, 78.7499999999997, 81.9949404453665, NA, 84.5563115043796, 
  87.0190820047277)), .Names = c("COUNTRY", "Year", "location", 
  "percent"), row.names = c(NA, -336L), class = "data.frame")
  </code></pre>
  
  <p>I want to produce a simple plot with ggplot2 that is facetted by COUNTRY. I can do this fine using <code>geom_point</code>:</p>
  
  <pre><code>ggplot(meas_melt, aes(Year, percent, colour=location))+ geom_point() + facet_wrap(~COUNTRY)
  </code></pre>
  
  <p>However, if I try and produce a line plot with geom_line (<code>ggplot(meas_melt, aes(Year, percent, colour=location))+ geom_line() + facet_wrap(~COUNTRY)</code>)</p>
  
  <p>I get the following error: </p>
  
  <blockquote>
    <p>geom_path: Each group consist of only one observation. Do you need to
    adjust the group aesthetic?</p>
  </blockquote>
  
  <p>I had thought that this could be because a couple of the countries have only one year's worth of data so I subsetted the date to remove these three countries like so:</p>
  
  <pre><code>ggplot(meas_melt, aes(Year, percent, colour=location))+ geom_line(data=meas_melt[!meas_melt$COUNTRY %in% c('Comoros','South Africa','Swaziland'),]) + facet_wrap(~COUNTRY)
  </code></pre>
  
  <p>However, I get the same error!</p>