First, your example didn't work because fish_ByMuestreo didn't build properly (deleting the first "structure(list(data = " bit solves this).
To solve your plotting problem, note that as constructed, the Muestreo column is numeric, whereas you seem to want to treat it as a factor. Solution: convert to factor: fish_ByMuestreo$Muestreo=factor(fish_ByMuestreo$Muestreo) On Thu, May 28, 2009 at 3:47 PM, Felipe Carrillo <mazatlanmex...@yahoo.com> wrote: > > Hi: > I need some help with the legend. I got 14 samples(Muestreo) and I > am trying to plot a smooth line for each sample. I am able to accomplish > that but the problem is that the legend only displays every other sample. How > can I force the legend to show all of my Muestreos? Thanks in advance. > > fish_ByMuestreo <- structure(list(data = structure(list(SampleDate = > structure(c(3L, > 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 16L, 16L, 16L, 7L, 7L, 7L, 7L, > 10L, 10L, 10L, 13L, 13L, 13L, 13L, 13L, 27L, 27L, 27L, 27L, 27L, > 17L, 17L, 17L, 17L, 20L, 20L, 20L, 20L, 24L, 24L, 24L, 24L, 24L, > 30L, 30L, 30L, 30L, 42L, 42L, 42L, 42L, 42L, 33L, 33L, 33L, 33L, > 36L, 36L, 36L, 36L, 36L, 39L, 39L, 39L, 39L, 39L, 39L, 14L, 14L, > 14L, 14L, 14L, 14L, 5L, 5L, 5L, 8L, 8L, 8L, 11L, 11L, 11L, 11L, > 15L, 15L, 15L, 28L, 28L, 28L, 28L, 28L, 18L, 18L, 18L, 18L, 18L, > 22L, 22L, 22L, 22L, 25L, 25L, 25L, 25L, 40L, 40L, 40L, 40L, 40L, > 31L, 31L, 31L, 31L, 37L, 37L, 37L, 37L, 1L, 1L, 1L, 1L, 1L, 3L, > 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 16L, 16L, 16L, 7L, 7L, 7L, 7L, > 10L, 10L, 10L, 13L, 13L, 13L, 13L, 13L, 27L, 27L, 27L, 27L, 27L, > 17L, 17L, 17L, 17L, 20L, 20L, 20L, 20L, 24L, 24L, 24L, 24L, 24L, > 30L, 30L, 30L, 30L, 42L, 42L, 42L, 42L, 42L, 33L, 33L, 33L, 33L, > 36L, 36L, 36L, 36L, 36L, 14L, 14L, 14L, 14L, 14L, 14L, 5L, 5L, > 5L, 8L, 8L, 8L, 11L, 11L, 11L, 11L, 15L, 15L, 15L, 28L, 28L, > 28L, 28L, 28L, 18L, 18L, 18L, 18L, 18L, 22L, 22L, 22L, 22L, 25L, > 25L, 25L, 25L, 40L, 40L, 40L, 40L, 40L, 31L, 31L, 31L, 31L, 34L, > 34L, 34L, 34L, 34L, 37L, 37L, 37L, 37L, 1L, 1L, 1L, 1L, 1L, 6L, > 6L, 6L, 6L, 6L, 6L, 9L, 9L, 9L, 12L, 12L, 12L, 21L, 21L, 21L, > 21L, 29L, 29L, 29L, 19L, 19L, 19L, 19L, 19L, 23L, 23L, 23L, 23L, > 23L, 26L, 26L, 26L, 26L, 41L, 41L, 41L, 41L, 32L, 32L, 32L, 32L, > 32L, 35L, 35L, 35L, 35L, 38L, 38L, 38L, 38L, 38L, 2L, 2L, 2L, > 2L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 16L, 16L, 16L, 7L, 7L, > 7L, 7L, 10L, 10L, 10L, 13L, 13L, 13L, 13L, 13L, 27L, 27L, 27L, > 27L, 27L, 17L, 17L, 17L, 17L, 20L, 20L, 20L, 20L, 24L, 24L, 24L, > 24L, 24L, 30L, 30L, 30L, 30L, 42L, 42L, 42L, 42L, 42L, 33L, 33L, > 33L, 33L, 36L, 36L, 36L, 36L, 36L, 39L, 39L, 39L, 39L, 39L, 39L, > 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 16L, 16L, 16L, 7L, 7L, 7L, > 7L, 10L, 10L, 10L, 13L, 13L, 13L, 13L, 13L, 27L, 27L, 27L, 27L, > 27L, 17L, 17L, 17L, 17L, 20L, 20L, 20L, 20L, 24L, 24L, 24L, 24L, > 24L, 30L, 30L, 30L, 30L, 42L, 42L, 42L, 42L, 42L, 33L, 33L, 33L, > 33L, 36L, 36L, 36L, 36L, 36L, 39L, 39L, 39L, 39L, 39L, 39L), .Label = > c("10/2/2002", > "10/4/2002", "6/23/2002", "6/30/2002", "7/10/2002", "7/12/2002", > "7/14/2002", "7/17/2002", "7/19/2002", "7/21/2002", "7/24/2002", > "7/26/2002", "7/28/2002", "7/3/2002", "7/31/2002", "7/7/2002", > "8/11/2002", "8/14/2002", "8/16/2002", "8/18/2002", "8/2/2002", > "8/21/2002", "8/23/2002", "8/25/2002", "8/28/2002", "8/30/2002", > "8/4/2002", "8/7/2002", "8/9/2002", "9/1/2002", "9/11/2002", > "9/13/2002", "9/15/2002", "9/18/2002", "9/20/2002", "9/22/2002", > "9/25/2002", "9/27/2002", "9/29/2002", "9/4/2002", "9/6/2002", > "9/8/2002"), class = "factor"), PondName = 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, 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, > 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, 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, 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, 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, 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, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, > 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L), .Label = c("Pond01", > "Pond02", "Pond03", "Pond04", "Pond05", "Pond06", "Pond07"), class = > "factor"), > Muestreo = c(1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, > 3L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 7L, 7L, > 7L, 7L, 7L, 8L, 8L, 8L, 8L, 9L, 9L, 9L, 9L, 10L, 10L, 10L, > 10L, 10L, 11L, 11L, 11L, 11L, 12L, 12L, 12L, 12L, 12L, 13L, > 13L, 13L, 13L, 14L, 14L, 14L, 14L, 14L, 15L, 15L, 15L, 15L, > 15L, 15L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, > 4L, 4L, 4L, 4L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, > 7L, 7L, 8L, 8L, 8L, 8L, 9L, 9L, 9L, 9L, 10L, 10L, 10L, 10L, > 10L, 11L, 11L, 11L, 11L, 13L, 13L, 13L, 13L, 14L, 14L, 14L, > 14L, 14L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, > 4L, 4L, 4L, 4L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, > 7L, 7L, 8L, 8L, 8L, 8L, 9L, 9L, 9L, 9L, 10L, 10L, 10L, 10L, > 10L, 11L, 11L, 11L, 11L, 12L, 12L, 12L, 12L, 12L, 13L, 13L, > 13L, 13L, 14L, 14L, 14L, 14L, 14L, 1L, 1L, 1L, 1L, 1L, 1L, > 2L, 2L, 2L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 6L, 6L, > 6L, 6L, 6L, 7L, 7L, 7L, 7L, 7L, 8L, 8L, 8L, 8L, 9L, 9L, 9L, > 9L, 10L, 10L, 10L, 10L, 10L, 11L, 11L, 11L, 11L, 12L, 12L, > 12L, 12L, 12L, 13L, 13L, 13L, 13L, 14L, 14L, 14L, 14L, 14L, > 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 4L, 4L, 4L, > 4L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, 7L, 7L, 8L, > 8L, 8L, 8L, 9L, 9L, 9L, 9L, 10L, 10L, 10L, 10L, 10L, 11L, > 11L, 11L, 11L, 12L, 12L, 12L, 12L, 12L, 13L, 13L, 13L, 13L, > 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 4L, 4L, 4L, > 4L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, 7L, 7L, 8L, > 8L, 8L, 8L, 9L, 9L, 9L, 9L, 10L, 10L, 10L, 10L, 10L, 11L, > 11L, 11L, 11L, 12L, 12L, 12L, 12L, 12L, 13L, 13L, 13L, 13L, > 14L, 14L, 14L, 14L, 14L, 15L, 15L, 15L, 15L, 15L, 15L, 1L, > 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, > 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, 7L, 7L, 8L, 8L, > 8L, 8L, 9L, 9L, 9L, 9L, 10L, 10L, 10L, 10L, 10L, 11L, 11L, > 11L, 11L, 12L, 12L, 12L, 12L, 12L, 13L, 13L, 13L, 13L, 14L, > 14L, 14L, 14L, 14L, 15L, 15L, 15L, 15L, 15L, 15L), BodyWeight.g. = c(1, > 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 3, 4, 4.5, 5, > 7, 6, 7, 6, 7, 8, 7, 8, 7, 9, 8, 9, 8, 9, 11, 11, 10, 12, > 11, 10, 12, 10.5, 14, 14, 13, 13.5, 17, 16, 14, 15, 14, 17, > 16, 17, 15.5, 18, 18, 18, 17, 18, 19, 21, 21, 21, 25, 22, > 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 3, 4, 4.5, > 5, 7, 6, 7, 6, 7, 8, 7, 8, 7, 9, 8, 9, 8, 9, 11, 11, 10, > 12, 11, 10, 12, 10.5, 14, 14, 13, 13.5, 17, 16, 17, 15.5, > 18, 18, 18, 17, 18, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, > 2, 2, 2, 3, 4, 4.5, 5, 7, 6, 7, 6, 7, 8, 7, 8, 7, 9, 8, 9, > 8, 9, 11, 11, 10, 11, 10, 12, 10.5, 12, 14, 14, 13, 13.5, > 17, 16, 14, 15, 14, 17, 16, 17, 15.5, 18, 18, 18, 17, 18, > 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 3, 4, 4.5, > 5, 7, 6, 7, 6, 7, 8, 7, 8, 7, 9, 8, 9, 8, 9, 11, 11, 10, > 12, 11, 10, 12, 10.5, 14, 14, 13, 13.5, 17, 16, 14, 15, 14, > 17, 16, 17, 15.5, 18, 18, 18, 17, 18, 1, 1, 1, 1, 1, 1, 1, > 1, 1, 1, 1, 1, 2, 2, 2, 2, 3, 4, 4.5, 5, 7, 6, 7, 6, 7, 8, > 7, 8, 7, 9, 8, 9, 8, 9, 11, 11, 10, 12, 11, 10, 12, 10.5, > 14, 14, 13, 13.5, 17, 16, 14, 15, 14, 17, 16, 17, 15.5, 1, > 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 3, 4, 4.5, 5, > 7, 6, 7, 6, 7, 8, 7, 8, 7, 9, 8, 9, 8, 9, 11, 11, 10, 12, > 11, 10, 12, 10.5, 14, 14, 13, 13.5, 17, 16, 14, 15, 14, 17, > 16, 17, 15.5, 18, 18, 18, 17, 18, 19, 21, 21, 21, 25, 22, > 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 3, 4, 4.5, > 5, 7, 6, 7, 6, 7, 8, 7, 8, 7, 9, 8, 9, 8, 9, 11, 11, 10, > 12, 11, 10, 12, 10.5, 14, 14, 13, 13.5, 17, 16, 14, 15, 14, > 17, 16, 17, 15.5, 18, 18, 18, 17, 18, 19, 21, 21, 21, 25, > 22), Length.mm. = c(2L, 2L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, > 2L, 2L, 3L, 4L, 5L, 3L, 4L, 5L, 5L, 6L, 6L, 7L, 5L, 6L, 7L, > 8L, 8L, 9L, 8L, 8L, 9L, 9L, 8L, 9L, 10L, 11L, 10L, 10L, 11L, > 12L, 11L, 12L, 12L, 13L, 14L, 12L, 13L, 14L, 15L, 16L, 15L, > 14L, 15L, 16L, 16L, 15L, 16L, 17L, 16L, 17L, 16L, 17L, 18L, > 19L, 17L, 18L, 2L, 2L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 2L, > 2L, 3L, 4L, 5L, 3L, 4L, 5L, 5L, 6L, 6L, 7L, 5L, 6L, 7L, 8L, > 8L, 9L, 8L, 8L, 9L, 9L, 8L, 9L, 10L, 11L, 10L, 10L, 11L, > 12L, 11L, 12L, 12L, 13L, 14L, 12L, 14L, 15L, 16L, 16L, 15L, > 16L, 17L, 16L, 17L, 2L, 2L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, > 2L, 2L, 3L, 4L, 5L, 3L, 4L, 5L, 5L, 6L, 6L, 7L, 5L, 6L, 7L, > 8L, 8L, 9L, 8L, 8L, 9L, 9L, 8L, 9L, 10L, 11L, 10L, 11L, 12L, > 11L, 12L, 10L, 12L, 13L, 14L, 12L, 13L, 14L, 15L, 16L, 15L, > 14L, 15L, 16L, 16L, 15L, 16L, 17L, 16L, 17L, 2L, 2L, 3L, > 2L, 2L, 2L, 2L, 2L, 2L, 3L, 2L, 2L, 3L, 4L, 5L, 3L, 4L, 5L, > 5L, 6L, 6L, 7L, 5L, 6L, 7L, 8L, 8L, 9L, 8L, 8L, 9L, 9L, 8L, > 9L, 10L, 11L, 10L, 10L, 11L, 12L, 11L, 12L, 12L, 13L, 14L, > 12L, 13L, 14L, 15L, 16L, 15L, 14L, 15L, 16L, 16L, 15L, 16L, > 17L, 16L, 17L, 2L, 2L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 2L, > 2L, 3L, 4L, 5L, 3L, 4L, 5L, 5L, 6L, 6L, 7L, 5L, 6L, 7L, 8L, > 8L, 9L, 8L, 8L, 9L, 9L, 8L, 9L, 10L, 11L, 10L, 10L, 11L, > 12L, 11L, 12L, 12L, 13L, 14L, 12L, 13L, 14L, 15L, 16L, 15L, > 14L, 15L, 16L, 16L, 2L, 2L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, > 2L, 2L, 3L, 4L, 5L, 3L, 4L, 5L, 5L, 6L, 6L, 7L, 5L, 6L, 7L, > 8L, 8L, 9L, 8L, 8L, 9L, 9L, 8L, 9L, 10L, 11L, 10L, 10L, 11L, > 12L, 11L, 12L, 12L, 13L, 14L, 12L, 13L, 14L, 15L, 16L, 15L, > 14L, 15L, 16L, 16L, 15L, 16L, 17L, 16L, 17L, 16L, 17L, 18L, > 19L, 17L, 18L, 2L, 2L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 2L, > 2L, 3L, 4L, 5L, 3L, 4L, 5L, 5L, 6L, 6L, 7L, 5L, 6L, 7L, 8L, > 8L, 9L, 8L, 8L, 9L, 9L, 8L, 9L, 10L, 11L, 10L, 10L, 11L, > 12L, 11L, 12L, 12L, 13L, 14L, 12L, 13L, 14L, 15L, 16L, 15L, > 14L, 15L, 16L, 16L, 15L, 16L, 17L, 16L, 17L, 16L, 17L, 18L, > 19L, 17L, 18L)), .Names = c("SampleDate", "PondName", "Muestreo", > "BodyWeight.g.", "Length.mm."), class = "data.frame", row.names = c("1", > "2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13", > "14", "15", "16", "17", "18", "19", "20", "21", "22", "23", "24", > "25", "26", "27", "28", "29", "30", "31", "32", "33", "34", "35", > "36", "37", "38", "39", "40", "41", "42", "43", "44", "45", "46", > "47", "48", "49", "50", "51", "52", "53", "54", "55", "56", "57", > "58", "59", "60", "61", "62", "63", "64", "65", "66", "67", "68", > "69", "70", "71", "72", "73", "74", "75", "76", "77", "78", "79", > "80", "81", "82", "83", "84", "85", "86", "87", "88", "89", "90", > "91", "92", "93", "94", "95", "96", "97", "98", "99", "100", > "101", "102", "103", "104", "105", "106", "107", "108", "109", > "110", "111", "112", "113", "114", "115", "116", "117", "118", > "119", "120", "121", "122", "123", "124", "125", "126", "127", > "128", "129", "130", "131", "132", "133", "134", "135", "136", > "137", "138", "139", "140", "141", "142", "143", "144", "145", > "146", "147", "148", "149", "150", "151", "152", "153", "154", > "155", "156", "157", "158", "159", "160", "161", "162", "163", > "164", "165", "166", "167", "168", "169", "170", "171", "172", > "173", "174", "175", "176", "177", "178", "179", "180", "181", > "182", "183", "184", "185", "186", "187", "188", "189", "190", > "191", "192", "193", "194", "195", "196", "197", "198", "199", > "200", "201", "202", "203", "204", "205", "206", "207", "208", > "209", "210", "211", "212", "213", "214", "215", "216", "217", > "218", "219", "220", "221", "222", "223", "224", "225", "226", > "227", "228", "229", "230", "231", "232", "233", "234", "235", > "236", "237", "238", "239", "240", "241", "242", "243", "244", > "245", "246", "247", "248", "249", "250", "251", "252", "253", > "254", "255", "256", "257", "258", "259", "260", "261", "262", > "263", "264", "265", "266", "267", "268", "269", "270", "271", > "272", "273", "274", "275", "276", "277", "278", "279", "280", > "281", "282", "283", "284", "285", "286", "287", "288", "289", > "290", "291", "292", "293", "294", "295", "296", "297", "298", > "299", "300", "301", "302", "303", "304", "305", "306", "307", > "308", "309", "310", "311", "312", "313", "314", "315", "316", > "317", "318", "319", "320", "321", "322", "323", "324", "325", > "326", "327", "328", "329", "330", "331", "332", "333", "334", > "335", "336", "337", "338", "339", "340", "341", "342", "343", > "344", "345", "346", "347", "348", "349", "350", "351", "352", > "353", "354", "355", "356", "357", "358", "359", "360", "361", > "362", "363", "364", "365", "366", "367", "368", "369", "370", > "371", "372", "373", "374", "375", "376", "377", "378", "379", > "380", "381", "382", "383", "384", "385", "386", "387", "388", > "389", "390", "391", "392", "393", "394", "395", "396", "397", > "398", "399", "400", "401", "402", "403", "404", "405", "406", > "407", "408", "409", "410", "411", "412", "413", "414", "415", > "416", "417", "418", "419", "420", "421", "422", "423", "424", > "425", "426", "427", "428")) > library(ggplot2) > fishplot <- > qplot(PondName,BodyWeight.g.,data=fish_ByMuestreo,colour=Muestreo,position="jitter") > + > stat_summary(aes(group=Muestreo),fun.data="mean_cl_normal",colour="green",geom="smooth",fill=NA) > + > opts(title="Average weight(grs) by Pond") > print(fishplot) > > > Felipe D. Carrillo > Supervisory Fishery Biologist > Department of the Interior > US Fish & Wildlife Service > California, USA > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > -- Mike Lawrence Graduate Student Department of Psychology Dalhousie University Looking to arrange a meeting? Check my public calendar: http://tr.im/mikes_public_calendar ~ Certainty is folly... I think. ~ ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.