Setting individual axis limits with facet wrap and scales free in ggplot2

Question

I m creating a facetted plot to view predicted vs  actual values side by side with a plot of  predicted value vs  residuals  I ll be using shiny to help explore the results of modeling efforts using different training parameters  I train the model with 85  of the data  test on the remaining 15   and repeat this 5 times  collecting actual predicted values each time  After calculating the residuals  my data frame looks like this   head results         act     pred       resid 2 52 81000 52 86750 -0 05750133 3 44 46000 42 76825  1 69175252 4 54 58667 49 00482  5 58184181 5 36 23333 35 52386  0 70947731 6 53 22667 48 79429  4 43237981 7 41 72333 41 57504  0 14829173   What I want    Side by side plot of pred vs  act and pred vs  resid The x y range limits for pred vs  act to be the same  ideally from min min results act   min results pred   to max max results act   max results pred   The x y range limits for pred vs  resid not to be affected by what I do to the actual vs  predicted plot  Plotting for x over only the predicted values and y over only the residual range is fine    In order to view both plots side by side  I melt the data   library reshape2  plot  lt - melt results  id vars    pred     Now plot   library ggplot2  p  lt - ggplot plot  aes x   pred  y   value     geom point size   2 5    theme bw   p  lt - p   facet wrap  variable  scales    free    print p    That s pretty close to what I want     What I d like is for the x and y ranges for actual vs  predicted to be the same  but I m not sure how to specify that  and I don t need that done for the predicted vs  residual plot since the ranges are completely different   I tried adding something like this for both scale x continous and scale y continuous   min xy  lt - min min plot pred   min plot value   max xy  lt - max max plot pred   max plot value    p  lt - ggplot plot  aes x   pred  y   value     geom point size   2 5    theme bw   p  lt - p   facet wrap  variable  scales    free   p  lt - p   scale x continuous limits   c min xy  max xy   p  lt - p   scale y continuous limits   c min xy  max xy    print p    But that picks up the min   of the residual values     One last idea I had is to store the value of the minimum act and pred variables before melting  and then add them to the melted data frame in order to dictate in which facet they appear   head results         act     pred       resid 2 52 81000 52 86750 -0 05750133 3 44 46000 42 76825  1 69175252 4 54 58667 49 00482  5 58184181 5 36 23333 35 52386  0 70947731  min xy  lt - min min results act   min results pred   max xy  lt - max max results act   max results pred    plot  lt - melt results  id vars    pred    plot  lt - rbind plot  data frame pred   c min xy  max xy     variable   c  act    act    value   c max xy  min xy     p  lt - ggplot plot  aes x   pred  y   value     geom point size   2 5    theme bw   p  lt - p   facet wrap  variable  scales    free    print p    That does what I want  with the exception that the points show up  too     Any suggestions for doing something like this     I saw this idea to add geom blank    but I m not sure how to specify the aes   bit and have it work properly  or what the geom point   equivalent is to the histogram use of aes y   max   count         Here s data to play with  my actual  predicted  and residual values prior to melting     gt  dput results  structure list act   c 52 81  44 46  54 5866666666667  36 2333333333333   53 2266666666667  41 7233333333333  35 2966666666667  30 6833333333333   39 25  35 8866666666667  25 1  29 0466666666667  23 2766666666667   56 3866666666667  42 92  41 57  27 92  23 16  38 0166666666667   61 8966666666667  37 41  41 6333333333333  35 9466666666667   48 9933333333333  30 5666666666667  32 08  40 3633333333333   53 2266666666667  64 6066666666667  38 5366666666667  41 7233333333333   25 78  33 4066666666667  27 8033333333333  39 3266666666667   48 9933333333333  25 2433333333333  32 67  55 17  42 92  54 5866666666667   23 16  64 6066666666667  40 7966666666667  39 0166666666667   41 6333333333333  35 8866666666667  25 1  23 2766666666667  44 46   34 2166666666667  40 8033333333333  24 5766666666667  35 73   61 8966666666667  62 1833333333333  74 6466666666667  39 4366666666667   36 6  27 1333333333333   pred   c 52 8675013282404  42 7682474758679   49 0048248585123  35 5238560262515  48 7942868566949  41 5750416040131   33 9548164913007  29 9787449128663  37 6443975781139  36 7196211666685   27 6043278172077  27 0615724310721  31 2073056885252  55 0886903524179   43 0895814712768  43 0895814712768  32 3549865881578  26 2428426737583   36 6926037128343  56 7987490221996  45 0370788180147  41 8231642271826   38 3297859332601  49 5343916620086  30 8535641206809  29 0117492750411   36 9767968381391  49 0826677983065  54 4678549541069  35 5059204731218   41 5333417555995  27 6069075391361  31 2404889715121  27 8920960978598   37 8505531149324  49 2616631533957  30 366837650159  31 1623492639066   55 0456078770405  42 772538591063  49 2419293590535  26 1963523976241   54 4080781796616  44 9796700541254  34 6996927469131  41 6227713664027   36 8449646519306  27 5318686661673  31 6641793552795  42 8198894266632   40 5769177148146  40 5769177148146  29 3807781312816  36 8579132935989   55 5617033901752  55 8097119335638  55 1041728261666  43 6094641699075   37 0674887276681  27 3876960746536   resid   c -0 0575013282403773   1 69175252413213  5 58184180815435  0 709477307081826  4 43237980997177   0 148291729320228  1 34185017536599  0 704588420467079  1 60560242188613   -0 832954500001826  -2 50432781720766  1 98509423559461  -7 93063902185855   1 29797631424874  -0 169581471276786  -1 51958147127679  -4 43498658815778   -3 08284267375831  1 32406295383237  5 09791764446704  -7 62707881801468   -0 189830893849219  -2 38311926659339  -0 541058328675241  -0 286897454014273   3 06825072495888  3 38653649519422  4 14399886836018  10 1388117125598   3 03074619354486  0 189991577733821  -1 82690753913609  2 16617769515461   -0 088762764526507  1 47611355173427  -0 268329820062384  -5 12350431682565   1 5076507360934  0 124392122959534  0 147461408936991  5 34473730761318   -3 03635239762411  10 1985884870051  -4 18300338745873  4 31697391975358   0 0105619669306023  -0 958297985263961  -2 43186866616734  -8 38751268861282   1 64011057333683  -6 36025104814794  0 226415618518729  -4 80411146461488   -1 1279132935989  6 33496327649151  6 37362139976954  19 5424938405001   -4 17279750324084  -0 467488727668119  -0 254362741320246     Names   c  act     pred    resid    row names   c 2L  3L  4L  5L  6L  7L  8L  9L   10L  11L  12L  13L  15L  16L  17L  18L  19L  20L  21L  22L  23L   24L  25L  26L  28L  29L  30L  31L  32L  33L  34L  35L  36L  37L   38L  39L  41L  42L  43L  44L  45L  46L  47L  48L  49L  50L  51L   52L  54L  55L  56L  57L  58L  59L  60L  61L  62L  63L  64L  65L    class    data frame

User · Accepted Answer

Here s some code with a dummy geom blank layer   range act  lt - range range results act   range results pred    d  lt - reshape2  melt results  id vars    pred    dummy  lt - data frame pred   range act  value   range act                      variable    act   stringsAsFactors FALSE   ggplot d  aes x   pred  y   value       facet wrap  variable  scales    free       geom point size   2 5       geom blank data dummy       theme bw

User · Answer

You can also specify the range with the coord cartesian command to set the y-axis range that you want  an like in the previous post use scales   free x   p  lt - ggplot plot  aes x   pred  y   value          geom point size   2 5         theme bw         coord cartesian ylim   c -20  80   p  lt - p   facet wrap  variable  scales    free x   p

User · Answer

I am not sure I understand what you want  but based on what I understood  the x scale seems to be the same  it is the y scale that is not the same  and that is because you specified scales   free   you can specify scales    free x  to only allow x to be free  in this case it is the same as pred has the same range by definition   p  lt - ggplot plot  aes x   pred  y   value     geom point size   2 5    theme bw   p  lt - p   facet wrap  variable  scales    free x     worked for me  see the picture    I think you were making it too difficult - I do seem to remember one time defining the limits based on a formula with min and max and if faceted I think it used only those values  but I can t find the code

[r] Setting individual axis limits with facet_wrap and scales = "free" in ggplot2

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