Databases
StackOverflow2013
Postsdbo
POR ggplot2 facetting - Error: No Layers in Plot
 

Note that there are some explanatory texts on larger screens.

plurals
  1. POR ggplot2 facetting - Error: No Layers in Plot
    primarykey
    data
    text
    <p>I've been struggling with for a couple of hours but I'm sure it's dead simple.</p> <p>I have a dataset that you can reproduce by copying and pasting from the jumble at the bottom here.</p> <p>It starts off looking like this</p> <pre><code>&gt; head(mydata) POSITION W_MEAN T_MEAN W_STDEV T_STDEV COUNT POSCAT 1 1 108.36 109.37 5.02 4.61 117 START 2 2 107.31 109.32 4.50 3.67 167 START 3 3 108.82 109.72 4.62 4.70 162 START 4 4 109.73 111.17 3.90 3.29 154 START 5 5 109.69 111.16 4.31 4.41 163 START 6 6 110.23 111.69 4.71 3.68 159 START </code></pre> <p>POSCAT is category I've assigned according to position. 1-40 = START, 41-120 = MIDDLE and 121+ = END.</p> <p>I've produced a nice histogram for the whole dataframe using </p> <pre><code>m &lt;- ggplot(mydata, aes(x=T_MEAN)) m + geom_histogram(aes(y = ..density..)) + geom_density() </code></pre> <p>But I want to facet the histogram on START, MIDDLE and END using POSCAT, so I've tried this</p> <pre><code>m &lt;- ggplot(mydata, aes(x=T_MEAN)) m + geom_histogram(aes(y = ..density..)) + geom_density() m + facet_grid(~ POSCAT) </code></pre> <p>And it gives me this error</p> <blockquote> <p>Error: No Layers in Plot</p> </blockquote> <p>What am I doing wrong?</p> <p>Thanks for the help!</p> <blockquote> <p>mydata &lt;- structure(list(POSITION = 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), W_MEAN = c(108.36, 107.31, 108.82, 109.73, 109.69, 110.23, 109.64, 109.69, 110.81, 109.89, 110.41, 110.34, 110.68, 110.39, 111.18, 110.59, 110.69, 110.5, 111.5, 111.33, 111.05, 111.78, 111.59, 111.94, 111.4, 112.09, 111.74, 112.23, 112.08, 112.68, 112.73, 112.72, 112.11, 112.36, 112.25, 112.65, 112.57, 112.86, 112.33, 112.74, 113.29, 112.47, 112.78, 112.18, 112.24, 112.8, 112.92, 112.36, 112.88, 112.86, 112.78, 113.14, 112.97, 112.84, 112.41, 112.94, 112.52, 112.63, 113.19, 112.71, 112.89, 112.83, 113.15, 112.51, 112.81, 112.72, 112.2, 113.04, 111.49, 113.06, 112.48, 112.82, 112, 112.62, 112.24, 112.8, 112.41, 112.67, 112.75, 111.21, 112.52, 111.88, 112.58, 111.08, 112.58, 112.67, 112.15, 113.01, 111.97, 112.32, 112.06, 112.52, 112.11, 112.38, 111.57, 112.33, 112.03, 111.97, 111.99, 111.94, 112.29, 111.43, 111.72, 111.73, 112.08, 111.45, 111.56, 111.79, 111.07, 111.35, 111.29, 111.35, 110.93, 110.87, 110.64, 110.74, 110.52, 110.39, 110.14, 109.91, 110.95, 110.85, 111.08, 110.49, 110.81, 109.8, 110.34, 110.14, 109.95, 110.46, 110.5, 110.53, 110.74, 110.39, 109.5, 110.28, 110.46, 110.57, 110.22, 110.42, 110.2, 110.16, 110.04, 110.52, 110.79, 109.43, 110.55, 110.35, 110.66, 110.05, 110.73, 110.48, 110.73, 109.8, 110.95, 110.33, 110.26, 110.7, 110.5, 110.28, 110.39, 110.73, 109.96), T_MEAN = c(109.37, 109.32, 109.72, 111.17, 111.16, 111.69, 111.6, 111.59, 112.07, 111.78, 112.01, 112.16, 112.43, 112.23, 112.17, 112.6, 112.48, 112.45, 113.4, 113.02, 113.08, 113.2, 113.41, 113.38, 113.41, 113.64, 113.5, 114.1, 113.97, 114.22, 114.42, 114.37, 114.06, 114.07, 114.06, 114.25, 114.18, 114.57, 114.4, 114.25, 114.97, 114.4, 114.64, 114.29, 114.3, 114.5, 114.5, 114.45, 114.48, 114.89, 114.46, 114.77, 114.76, 114.3, 114.47, 114.4, 114.61, 114.25, 114.5, 114.73, 114.73, 114.42, 114.34, 114.52, 114.39, 114.43, 114.02, 114.23, 113.8, 114.4, 114.17, 114.35, 114.03, 114.29, 114.44, 114.19, 114.27, 114.22, 114.25, 113.4, 113.84, 113.99, 113.82, 113.32, 113.93, 114.26, 114.04, 114.4, 114.06, 113.96, 113.97, 114.05, 113.72, 113.94, 113.51, 113.97, 113.64, 113.54, 113.57, 113.78, 113.59, 113.01, 113.5, 113.43, 113.44, 113.02, 113.4, 113.36, 112.97, 112.65, 112.95, 112.99, 112.51, 112.45, 112.26, 112.51, 112.09, 111.86, 111.8, 111.68, 112.46, 112.33, 112.67, 112.02, 112.36, 111.46, 111.88, 111.76, 111.28, 111.97, 112.05, 112.1, 112.25, 111.69, 111.28, 111.87, 111.85, 111.98, 111.77, 111.81, 111.78, 111.72, 111.47, 112.01, 112.22, 110.95, 112.06, 111.87, 112.02, 111.63, 111.95, 112.08, 112, 111.48, 112.11, 111.5, 111.85, 112.03, 111.87, 111.53, 111.8, 111.73, 111.44), W_STDEV = c(5.02, 4.5, 4.62, 3.9, 4.31, 4.71, 3.89, 4.59, 4.24, 4.08, 4.19, 3.66, 3.66, 3.93, 3.79, 3.62, 3.67, 3.74, 3.4, 3.74, 3.33, 3.34, 2.98, 3.69, 3.55, 3.18, 3.12, 3.28, 3.58, 3.57, 3.81, 3.14, 3.45, 3.59, 3.81, 3.82, 3.22, 3.37, 3, 3.09, 3.07, 2.96, 2.86, 2.83, 2.72, 2.91, 2.77, 3.17, 3.57, 3.11, 3.2, 3.14, 3.31, 3.71, 3.9, 3.64, 3.21, 2.99, 3.39, 2.99, 3.39, 3.41, 3.12, 3.39, 3.09, 3.16, 3.22, 2.79, 3.13, 3.27, 4.09, 3.02, 3.15, 2.98, 3.13, 3.3, 3.07, 3.07, 3.26, 3.15, 3.35, 3.23, 3.47, 3.65, 2.79, 2.78, 3.3, 3.08, 2.91, 2.76, 2.91, 3.05, 3.24, 3.28, 2.84, 2.76, 2.72, 2.97, 3.44, 2.75, 3.16, 3.58, 2.99, 3.11, 2.96, 3.74, 2.89, 3.51, 3.54, 3.75, 3.36, 3.73, 3.34, 3.64, 3.81, 3.27, 3.87, 3.62, 3.8, 3.36, 3.25, 3.41, 3.33, 3.52, 3.57, 3.96, 3.75, 3.78, 3.57, 3.28, 3.14, 3.53, 3.26, 3.38, 4.39, 3.13, 3.18, 3.13, 3.61, 3.72, 3.47, 3.52, 3.77, 3.26, 3.55, 3.98, 3.63, 3.54, 3.47, 3.42, 3.33, 3.73, 3.04, 3.51, 3.04, 3.63, 2.98, 3.22, 3.47, 3.62, 3.74, 2.9, 4.18), T_STDEV = c(4.61, 3.67, 4.7, 3.29, 4.41, 3.68, 3.19, 3.56, 3.19, 3.43, 3.14, 2.97, 2.83, 3.34, 3.51, 2.78, 2.65, 2.56, 2.75, 2.84, 2.52, 2.66, 2.56, 2.56, 2.47, 2.39, 2.61, 2.44, 2.62, 2.4, 2.46, 2.28, 2.39, 2.5, 2.66, 2.49, 2.33, 2.42, 2.4, 2.49, 2.38, 2.28, 2.32, 2.36, 2.39, 2.13, 2.18, 2.56, 2.44, 2.23, 2.48, 2.41, 2.19, 2.59, 2.44, 2.58, 2.49, 2.28, 2.37, 2.35, 2.3, 2.47, 2.25, 2.71, 2.33, 2.42, 2.58, 2.14, 2.4, 2.48, 3.08, 2.33, 2.33, 2.36, 2.33, 2.53, 2.51, 2.62, 2.6, 2.45, 2.51, 2.55, 2.67, 2.81, 2.32, 2.2, 2.59, 2.53, 2.28, 2.27, 2.15, 2.49, 2.44, 2.41, 2.49, 2.35, 2.37, 2.57, 2.85, 2.4, 2.77, 2.98, 2.45, 2.67, 2.56, 3.15, 2.74, 2.87, 2.96, 3.41, 3.04, 3.25, 3.02, 3.49, 3.42, 2.97, 3.66, 3.46, 3.62, 3.22, 3.16, 3.41, 3.26, 3.35, 3.34, 3.79, 3.65, 3.53, 3.09, 2.95, 3.1, 3.2, 3.04, 3.33, 4.14, 3.01, 2.92, 3.07, 3.35, 3.75, 3.31, 3.27, 3.62, 3.28, 3.31, 4.18, 3.74, 3.6, 3.4, 3.34, 3.23, 3.58, 3.02, 3.27, 2.97, 3.68, 2.92, 3.31, 3.36, 3.52, 3.69, 3.51, 4.27), COUNT = c(117, 167, 162, 154, 163, 159, 164, 170, 171, 170, 168, 170, 163, 166, 172, 173, 173, 166, 173, 163, 177, 174, 175, 173, 175, 170, 165, 172, 175, 176, 174, 175, 174, 168, 174, 171, 174, 175, 176, 170, 171, 168, 171, 165, 171, 170, 170, 174, 173, 174, 158, 170, 168, 170, 168, 169, 174, 171, 166, 168, 169, 172, 158, 163, 173, 167, 172, 167, 169, 168, 166, 165, 171, 158, 158, 170, 174, 173, 169, 164, 168, 174, 168, 169, 170, 174, 174, 171, 159, 161, 169, 163, 169, 169, 164, 172, 171, 164, 170, 165, 161, 162, 165, 163, 166, 169, 173, 168, 169, 165, 169, 166, 163, 170, 171, 172, 169, 169, 166, 163, 168, 166, 168, 168, 172, 171, 172, 168, 172, 164, 169, 169, 170, 172, 171, 167, 161, 166, 170, 170, 172, 169, 173, 160, 168, 161, 171, 173, 171, 166, 158, 170, 167, 166, 169, 169, 159, 160, 157, 150, 159, 146, 88), POSCAT = c("START", "START", "START", "START", "START", "START", "START", "START", "START", "START", "START", "START", "START", "START", "START", "START", "START", "START", "START", "START", "START", "START", "START", "START", "START", "START", "START", "START", "START", "START", "START", "START", "START", "START", "START", "START", "START", "START", "START", "START", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "MIDDLE", "END", "END", "END", "END", "END", "END", "END", "END", "END", "END", "END", "END", "END", "END", "END", "END", "END", "END", "END", "END", "END", "END", "END", "END", "END", "END", "END", "END", "END", "END", "END", "END", "END", "END", "END", "END", "END", "END", "END", "END", "END", "END", "END")), .Names = c("POSITION", "W_MEAN", "T_MEAN", "W_STDEV", "T_STDEV", "COUNT", "POSCAT"), row.names = c(NA, 163L), class = "data.frame")</p> </blockquote>
    singulars
    1. PO
      singulars
      1. PTAnswer
    1. This table or related slice is empty.
    1. PTQuestion
    1. This table or related slice is empty.
    1. USTommy O'Dell
    plurals
    1. This table or related slice is empty.
    1. This table or related slice is empty.
    1. This table or related slice is empty.
    1. PO
      singulars
      1. PTAnswer
    1. VO
      singulars
      1. POR ggplot2 facetting - Error: No Layers in Plot
      1. This table or related slice is empty.
      1. VTUpMod
    2. VO
      singulars
      1. POR ggplot2 facetting - Error: No Layers in Plot
      1. This table or related slice is empty.
      1. VTUpMod
    3. VO
      singulars
      1. POR ggplot2 facetting - Error: No Layers in Plot
      1. This table or related slice is empty.
      1. VTUpMod
    1. COIt's very helpful to post sample data at the bottom, so thank you! +1
      singulars
      1. POR ggplot2 facetting - Error: No Layers in Plot
      1. USChase
 

Querying!

 
Guidance
A row detail

Detail views are divided into sections. All the information in the data section comes from columns in the selected row. The other sections display data from other, related rows.

Related data can be related in a to-one or a to-many fashion. Captions of data related in a to-many fashion link to a list view showing a filtered view of the table.

Try moving around until you find a non-empty to-many entry and click on the label to get to one. You can move back to the root by clicking on the database name in the header.

SQuiL has stopped working due to an internal error.

If you are curious you may find further information in the browser console, which is accessible through the devtools (F12).

Reload