Order facets vertically rather than side-by-side in ggplot2

In this data:

Example <- structure(list(PP_dur_cumsum = c(0, 18, 34, 50, 68, 84, 
100, 118, 134, 150, 168, 184, 200, 218, 234, 250, 268, 284, 300, 318, 
334, 350, 368, 384, 400, 418, 434, 450, 468, 484, 500, 518, 534, 
550, 568, 584, 600, 618, 634, 650, 668, 684, 700, 718, 734, 750, 
768, 784, 800, 818, 834, 850, 868, 884, 900, 918, 934, 950, 968, 
984, 1000, 1018, 1034, 1050, 1068, 1084, 1100, 1118, 1134, 1150, 
1168, 1184, 1200, 1218, 1234, 1250, 1268, 1284, 1300, 1318, 1334, 
1350, 1368, 1384, 1400, 1418, 1434, 1450, 1468, 1484, 1500, 1518, 
1534, 1550, 1568, 1584, 1600, 1618, 1634, 1650, 1668, 1684, 1700, 
1718, 1734, 1750, 1768, 1784, 1800, 1818, 1834, 1850, 1868, 1884, 
1900, 1918, 1934, 1950, 1968, 1984, 2000, 2018, 2034, 2050, 2068, 
2084, 2100, 2118, 2134, 2150, 2168, 2184, 2195, 2200, 2218, 2234, 
2250, 2268, 2284, 2284, 2284, 2300, 2318, 2334, 2350, 2368, 2384, 
2400, 2418, 2434, 2450, 2468, 2484, 2500, 2518, 2534, 2550, 2568, 
2584, 2600, 2618, 2634, 2650, 2668, 2684, 2700, 2718, 2734, 2750, 
2768, 2784, 2800, 2818, 2834, 2850, 2868, 2884, 2900, 2918, 2934, 
2950, 2968, 2984, 3000, 3018, 3034, 3050, 3068, 3084, 3100, 3118, 
3134, 3150, 3168, 3184, 3200, 3218, 3234, 3250, 3268, 3284, 3300, 
3318, 3334, 3350, 3368, 3384, 3400, 3418, 3434, 3450, 3468, 3484, 
3500, 3518, 3534, 3550, 3568, 3584, 3600, 3618, 3634, 3641, 14, 
30, 48, 64, 80, 98, 114, 130, 148, 164, 180, 198, 214, 230, 248, 
264, 280, 298, 314, 330, 348, 364, 380, 398, 414, 430, 448, 464, 
480, 498, 514, 530, 548, 564, 580, 598, 614, 630, 648, 664, 680, 
698, 714, 730, 748, 764, 780, 798, 814, 830, 848, 864, 880, 898, 
914, 930, 948, 964, 980, 998, 1014, 1030, 1048, 1064, 1080, 1098, 
1114, 1130, 1148, 1164, 1180, 1198, 1214, 1230, 1248, 1264, 1280, 
1298, 1314, 1330, 1348, 1364, 1380, 1398, 1414, 1430, 1448, 1464, 
1480, 1498, 1514, 1530, 1548, 1564, 1580, 1598, 1614, 1630, 1648, 
1664, 1680, 1698, 1714, 1730, 1748, 1764, 1780, 1798, 1814, 1830, 
1848, 1864, 1880, 1898, 1914, 1930, 1948, 1964, 1980, 1998, 2014, 
2030, 2048, 2064, 2080, 2098, 2114, 2130, 2148, 2164, 2180, 2195, 
2198, 2214, 2230, 2248, 2264, 2280, 2284, 2298, 2314, 2330, 2348, 
2364, 2380, 2398, 2414, 2430, 2448, 2464, 2480, 2498, 2514, 2530, 
2548, 2564, 2580, 2598, 2614, 2630, 2648, 2664, 2680, 2698, 2714, 
2730, 2748, 2764, 2780, 2798, 2814, 2830, 2848, 2864, 2880, 2898, 
2914, 2930, 2948, 2964, 2980, 2998, 3014, 3030, 3048, 3064, 3080, 
3098, 3114, 3130, 3148, 3164, 3180, 3198, 3214, 3230, 3248, 3264, 
3280, 3298, 3314, 3330, 3348, 3364, 3380, 3398, 3414, 3430, 3448, 
3464, 3480, 3498, 3514, 3530, 3548, 3564, 3580, 3598, 3614, 3630, 
3641), Area_deriv = c(NA, 0.32150000000002, -0.5954999999999, 
6.9704999999999, -4.89850000000001, -5.2349999999999, 4.81950000000006, 
-4.37599999999998, 0.30049999999983, 1.08150000000001, 0.52700000000004, 
-1.3409999999999, -1.30850000000009, -3.4994999999999, 0.05299999999988, 
-1.2439999999999, -4.1465000000001, -0.885500000000102, -0.6114999999999, 
-1.6499999999999, -6.8320000000001, -26.0270000000001, -130.3865, 
-439.311, -194.903666666667, -194.903666666661, -194.90366666667, 
111.918, 324.420499999998, 363.968, 153.002, 74.4695, 29.1435, 
35.31, 8.236, 3.0175, 20.8860000000001, 8.7780000000001, 22.4504999999999, 
-30.2104999999999, 28.5219999999999, -26.6489999999999, 3.14750000000001, 
17.2189999999999, 29.0305, -0.355500000000102, 16.8430000000001, 
-3.125, 12.5450000000001, -3.63400000000001, 2.61750000000006, 
-17.5995, -8.348, -20.5310000000001, 19.6684999999999, -37.5444999999999, 
26.3955000000001, -3.5660000000001, 13.3454999999999, -5.2044999999998, 
1.5609999999999, -12.3565000000001, 24.9115000000002, 6.1979999999999, 
10.4945, 6.61550000000011, 8.89049999999997, -10.9065000000001, 
6.37799999999993, 13.4175000000001, -0.0194999999999013, 4.134, 
10.2469999999998, -6.3409999999999, 5.734, 3.864, 6.9014999999999, 
-0.226499999999994, 3.8740000000001, 0.207500000000003, 4.6694999999999, 
0.0234999999999985, 8.6330000000001, -2.4485, 8.69499999999991, 
-2.45200000000001, -2.2069999999998, 2.5584999999998, 6.9095000000002, 
2.18899999999989, -0.793999999999897, -1.95350000000001, 11.1814999999999, 
5.34500000000001, -0.103499999999912, 2.373, 3.2925, 5.2369999999999, 
2.18300000000001, 5.7524999999999, 0.512999999999991, 3.051, 
-2.743, -0.0564999999999998, -0.537500000000009, -1.74749999999999, 
4.7825, 3.18799999999999, -1.34849999999999, 2.8985, -2.8815, 
-2.021, 1.467, 3.2615, -0.724999999999994, -0.157499999999999, 
-6.59050000000001, 11.2225, -7.348, 9.3015, -1.9075, -2.21900000000001, 
-0.759999999999991, -9.00750000000001, 0.244, 3.0305, -5.7175, 
5.09350000000001, -3.146, -1.672, 4.065, 0.793999999999997, -4.95350000000001, 
0, 9.238, -0.295000000000002, -0.904999999999987, -1.732, -2.54750000000001, 
-3.21749999999999, 3.21749999999999, -3.21749999999999, 12.7615, 
-5.82650000000001, -4.2435, -2.47999999999999, -2.117, -0.581000000000003, 
-4.2384999999998, 12.2954999999998, -18.6424999999998, -229.5555, 
-5.1705, 5.29600000000002, 28.328, -109.2295, 145.12, 66.5205000000001, 
21.4874999999999, 0.116000000000001, -19.045, 12.1685, 11.8625000000001, 
-14.4655, 11.258, 5.2814999999999, -5.1885, -5.59799999999996, 
6.44900000000006, -7.51250000000004, -21.655, 7.43349999999986, 
-25.6240000000001, -38.1875, -3.64999999999981, 2.5684999999998, 
-7.19199999999979, -16.1300000000001, -5.89750000000009, -7.824, 
-1.3075, -9.215, -4.7475, -7.5275, 2.98750000000001, -4.04300000000001, 
1.9195, -7.237, 3.35499999999999, 1.1755, -1.19199999999998, 
0.886499999999984, -33.8335, -172.5375, 57.4545, 70.8445, -9.12099999999998, 
32.6625, 134.7595, 4.1390000000002, 25.0799999999999, -3.5815, 
10.5250000000001, -0.3825, 3.262, 3.161, 0.962499999999901, -5.9825000000001, 
5.3885000000001, 2.26750000000011, -4.00800000000001, -3.5450000000001, 
2.2284999999999, 4.48150000000013, -14.5864999999999, 8.375, 
-2.862, -0.203500000000098, 10.1210000000001, -6.96900000000008, 
-3.5564999999999, 4.4524999999999, 9.01850000000012, NA, 525.092825, 
525.092825, 406.4437, -147.4305, 377.4495, -2995.561, 1781.272, 
2053.7355, -1231.6545, -2316.3695, 3198.586, -3535.4125, 245.4355, 
823.1885, 2291.5645, -3554.3125, 43.627, 10.47775, 10.47775, 
10.47775, 10.47775, -115.268, 88.0915, 100.69, 87.561, 10.6745, 
8.46199999999999, -12.9465, 5.20850000000002, 3051.908, -3036.442, 
2686.2585, 173.568, -47.1695, -2789.406, 2849.397, 275.985, 238.431, 
-511.8895, 181.4075, 184.7545, 259.7205, -401.019, 148.789, -264.382, 
212.546, -121.7445, -227.5715, -2853.0605, 3132.3155, -167.805, 
22.5084999999999, -153.557, 494.4395, -631.7795, 503, 124.0635, 
-111.217, 72.8795, -9.20299999999997, -652.408, 621.0805, -535.923, 
606.046, -356.5365, 368.5785, -1012.366, 1091.0185, -637.7605, 
754.1345, -808.804, 769.112, -92.174, -171.6455, -377.518, 739.5415, 
-1214.455, 952.3835, -614.722, 646.297, -90.7645000000002, -104.3935, 
77.2705000000001, 116.523, -380.8515, -17.7249999999999, 253.7775, 
116.164, -277.668, 34.261, 128.0825, -207.435, 227.2565, 333.0205, 
-298.161, -346.1005, 317.3425, -365.265, 521.0805, -708.813, 
743.0355, -477.743, 601.961, -936.712, -2575.717, 2734.2615, 
304.4085, -123.775, 343.218, -644.843, 297.331, -368.557, -2532.445, 
5.05199999999999, 9.36499999999998, 5.30500000000001, -7.37299999999999, 
5.88900000000001, 2281.2295, -2288.7675, 1.88, 2.368, 2750.645, 
-2746.548, 3271.7975, -380.6475, 204.749, -177.2025, -191.9485, 
238.039, 289.537, 0, 31.1355000000003, -1040.6615, 54.7139999999999, 
709.086, 172.58, 24.9654999999998, 0, 14.9055000000003, -624.715, 
655.8415, -197.586, -3045.0145, 3192.297, -245.667, 335.674, 
-369.364, -203.103, 259.8435, 336.675, -768.6595, 764.824, -299.244, 
-70.1099999999997, -2931.801, -10.256, -7.388, 10.282, -19.591, 
3065.3735, -3092.3425, 34.283, -23.4125, -9.2285, -5.29650000000001, 
24.2975, -24.2225, 7.33900000000003, -2.3065, 4.39599999999999, 
-3.3065, 12.6215, -2.39749999999998, 12.0475, -11.9305, -4.51249999999999, 
10.967, -3.52500000000001, -14.4555, 11.7915, 19.817, 7.21849999999998, 
-0.131, 10.1075, -8.84350000000001, 9.65000000000001, 7.57650000000001, 
-9.44600000000003, 10.2135, -16.4855, 5.5505, 1.44650000000001, 
-2.9315, -4.364, 6.3775, -5.83000000000001, 7.73700000000002, 
2865.7525, -58.5005000000001, 297.424, 424.0625, -38.4135000000001, 
14.9205000000002, -11.085, 41.4870000000001, -3506.623, 3504.3265, 
-3509.251, 4.9485, 2975.634, -207.3205, 172.411, 10.1180000000004, 
82.8999999999996, 517.5385, -374.431, -167.904, -39.904, -36.0614999999998
), mean_deriv = c(-0.0102770270270248, -0.0102770270270248, -0.0102770270270248, 
-0.0102770270270248, -0.0102770270270248, -0.0102770270270248, 
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7.93484249999999, 7.93484249999999, 7.93484249999999, 7.93484249999999, 
7.93484249999999, 7.93484249999999, 7.93484249999999, 7.93484249999999, 
7.93484249999999, 7.93484249999999, 7.93484249999999, 7.93484249999999, 
7.93484249999999, 7.93484249999999, 7.93484249999999, 7.93484249999999, 
7.93484249999999, 7.93484249999999, 7.93484249999999, 7.93484249999999, 
7.93484249999999, 7.93484249999999, 7.93484249999999, 7.93484249999999, 
7.93484249999999, 7.93484249999999, 7.93484249999999, 7.93484249999999, 
7.93484249999999, 7.93484249999999, 7.93484249999999, 7.93484249999999, 
7.93484249999999, 7.93484249999999, 7.93484249999999, 7.93484249999999, 
7.93484249999999, 7.93484249999999, 7.93484249999999, 7.93484249999999, 
7.93484249999999, 7.93484249999999, 7.93484249999999, 7.93484249999999, 
7.93484249999999, 7.93484249999999, 7.93484249999999, 7.93484249999999, 
7.93484249999999, 7.93484249999999, 7.93484249999999, 7.93484249999999, 
7.93484249999999, 7.93484249999999, 7.93484249999999, 7.93484249999999, 
7.93484249999999, 7.93484249999999, 7.93484249999999, 7.93484249999999, 
7.93484249999999, 7.93484249999999, 7.93484249999999, 7.93484249999999, 
7.93484249999999, 7.93484249999999, 7.93484249999999, 7.93484249999999, 
7.93484249999999, 7.93484249999999, 7.93484249999999, 7.93484249999999, 
7.93484249999999, 7.93484249999999, 7.93484249999999, 7.93484249999999, 
7.93484249999999, 7.93484249999999), PP_by = c("NotAnswerer", 
"NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", 
"NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", 
"NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", 
"NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", 
"NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", 
"NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", 
"NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", 
"NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", 
"NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", 
"NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", 
"NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", 
"NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", 
"NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", 
"NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", 
"NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", 
"NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", 
"NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", 
"NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", 
"NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", 
"NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", 
"NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", 
"NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", 
"NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", 
"NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", 
"NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", 
"NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", 
"NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", 
"NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", 
"NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", 
"NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", 
"NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", 
"NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", 
"NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", 
"NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", 
"NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", 
"NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", 
"NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", 
"NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", 
"NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", 
"NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", 
"NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", 
"NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", 
"NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", 
"NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", "NotAnswerer", 
"NotAnswerer", "NotAnswerer", "Answerer", "Answerer", "Answerer", 
"Answerer", "Answerer", "Answerer", "Answerer", "Answerer", "Answerer", 
"Answerer", "Answerer", "Answerer", "Answerer", "Answerer", "Answerer", 
"Answerer", "Answerer", "Answerer", "Answerer", "Answerer", "Answerer", 
"Answerer", "Answerer", "Answerer", "Answerer", "Answerer", "Answerer", 
"Answerer", "Answerer", "Answerer", "Answerer", "Answerer", "Answerer", 
"Answerer", "Answerer", "Answerer", "Answerer", "Answerer", "Answerer", 
"Answerer", "Answerer", "Answerer", "Answerer", "Answerer", "Answerer", 
"Answerer", "Answerer", "Answerer", "Answerer", "Answerer", "Answerer", 
"Answerer", "Answerer", "Answerer", "Answerer", "Answerer", "Answerer", 
"Answerer", "Answerer", "Answerer", "Answerer", "Answerer", "Answerer", 
"Answerer", "Answerer", "Answerer", "Answerer", "Answerer", "Answerer", 
"Answerer", "Answerer", "Answerer", "Answerer", "Answerer", "Answerer", 
"Answerer", "Answerer", "Answerer", "Answerer", "Answerer", "Answerer", 
"Answerer", "Answerer", "Answerer", "Answerer", "Answerer", "Answerer", 
"Answerer", "Answerer", "Answerer", "Answerer", "Answerer", "Answerer", 
"Answerer", "Answerer", "Answerer", "Answerer", "Answerer", "Answerer", 
"Answerer", "Answerer", "Answerer", "Answerer", "Answerer", "Answerer", 
"Answerer", "Answerer", "Answerer", "Answerer", "Answerer", "Answerer", 
"Answerer", "Answerer", "Answerer", "Answerer", "Answerer", "Answerer", 
"Answerer", "Answerer", "Answerer", "Answerer", "Answerer", "Answerer", 
"Answerer", "Answerer", "Answerer", "Answerer", "Answerer", "Answerer", 
"Answerer", "Answerer", "Answerer", "Answerer", "Answerer", "Answerer", 
"Answerer", "Answerer", "Answerer", "Answerer", "Answerer", "Answerer", 
"Answerer", "Answerer", "Answerer", "Answerer", "Answerer", "Answerer", 
"Answerer", "Answerer", "Answerer", "Answerer", "Answerer", "Answerer", 
"Answerer", "Answerer", "Answerer", "Answerer", "Answerer", "Answerer", 
"Answerer", "Answerer", "Answerer", "Answerer", "Answerer", "Answerer", 
"Answerer", "Answerer", "Answerer", "Answerer", "Answerer", "Answerer", 
"Answerer", "Answerer", "Answerer", "Answerer", "Answerer", "Answerer", 
"Answerer", "Answerer", "Answerer", "Answerer", "Answerer", "Answerer", 
"Answerer", "Answerer", "Answerer", "Answerer", "Answerer", "Answerer", 
"Answerer", "Answerer", "Answerer", "Answerer", "Answerer", "Answerer", 
"Answerer", "Answerer", "Answerer", "Answerer", "Answerer", "Answerer", 
"Answerer", "Answerer", "Answerer", "Answerer", "Answerer", "Answerer", 
"Answerer", "Answerer", "Answerer", "Answerer", "Answerer", "Answerer", 
"Answerer", "Answerer", "Answerer", "Answerer", "Answerer", "Answerer", 
"Answerer", "Answerer")), class = c("grouped_df", "tbl_df", "tbl", 
"data.frame"), row.names = c(NA, -444L), groups = structure(list(
    PP_by = c("Answerer", "NotAnswerer"), .rows = structure(list(
        224:444, 1:223), ptype = integer(0), class = c("vctrs_list_of", 
    "vctrs_vctr", "list"))), class = c("tbl_df", "tbl", "data.frame"
), row.names = c(NA, -2L), .drop = TRUE))

and this plot:

library(ggplot2)
ggplot(Example,
       aes(x = PP_dur_cumsum, y = Area_deriv, color = mean_deriv > 0)) +
  geom_smooth(method = "loess", se = FALSE) +
  geom_smooth(method = "lm", se = FALSE, color = "black") +
  facet_grid(. ~ PP_by, scales = 'free_x')

I need to change the arrangement of the facets: from side-by-side to vertical, i.e., one (for Answerer) on top of the other (for NotAnswerer). How can that be done?

>Solution :

The formula interface for facet_grid isn’t super flexible, but version 3.0 (2018) introduced an interface option to use rows or cols:

ggplot(Example,
       aes(x = PP_dur_cumsum, y = Area_deriv, color = mean_deriv > 0)) +
  geom_smooth(method = "loess", se = FALSE) +
  geom_smooth(method = "lm", se = FALSE, color = "black") +
  facet_grid(
    rows = vars(PP_by),
    scales = 'free_x'
  )

I’d also suggest that the main point of facet_grid is to have shared scales and different variables in rows and columns – forming a grid. If you are only faceting by 1 variable you don’t have a grid, and you want free scales, so facet_wrap seems like a better option:

ggplot(Example,
       aes(x = PP_dur_cumsum, y = Area_deriv, color = mean_deriv > 0)) +
  geom_smooth(method = "loess", se = FALSE) +
  geom_smooth(method = "lm", se = FALSE, color = "black") +
  facet_wrap(
    vars(PP_by),
    ncol = 1,
    scales = 'free_x'
  )

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