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IndrajeetPatil / ggstatsplot

Enhancing {ggplot2} plots with statistical analysis 📊📣
https://indrajeetpatil.github.io/ggstatsplot/
GNU General Public License v3.0
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Error in ggplot2::discrete_scale #337

Closed scbrown86 closed 5 years ago

scbrown86 commented 5 years ago

Hi, Whenever I try to use any of the functions an error is thrown about using a discrete colour scale.

I've updated both ggstatsplot and ggplot2 to the latest versions on CRAN but the error still occurs.

Error in ggplot2::discrete_scale("colour", palette_name, pal_pal(palette = { : unused argument (package = !!package)

library(ggstatsplot)

## output from dput(x)
plot_df <- structure(list(Start_rec = structure(c(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, 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, 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, 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, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 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, 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, 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, 
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, 4L, 4L, 4L, 4L, 4L, 4L, 
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L
), .Label = c("21-15k BP", "15-11k BP", "11-3k BP", ">3k BP"), class = "factor"), 
    Layer_rec = structure(c(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, 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, 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, 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, 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, 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, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    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, 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, 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, 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, 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, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = c("Observed", 
    "TraCE-21"), class = "factor"), Value = c(0.00594, 0.02022, 
    0.03385, 0.16217, 0.00463, 0.07271, 0.0143, 0.0121, 0.001, 
    0.06169, 0.00637, 0.2713, 0.03872, 0.01683, 0.52778, 0.01154, 
    0.00029, 0.02093, 0.05027, 0.00596, 0.77704, 0.0437, 0.01881, 
    0.01876, 0.00674, 0.12485, 0.01402, 0.00113, 0.02784, 0.02852, 
    0.02139, 0.02686, 0.02518, 0.00697, 0.02899, 0.08844, 0.02512, 
    0.11878, 0.0025, 0.01577, 0.08542, 0.00503, 0.04768, 0.14443, 
    0.02006, 0.02856, 0.00166, 0.00118, 0.07311, 0.02312, 0.02471, 
    0.21024, 0.01341, 0.01128, 0.02357, 0.8821, 0.03332, 0.02939, 
    0.00028, 0.08725, 0.00698, 0.06053, 0.00277, 0.00626, 0.07372, 
    0.28413, 0.00229, 0.05651, 0.00276, 0.01449, 0.2347, 0.0073, 
    0.01674, 0.04127, 0.00747, 0.02103, 0.01852, 0.01373, 0.01332, 
    0.01747, 0.02161, 0.0118, 0.01209, 0.01107, 0.00965, 0.03316, 
    0.02888, 0.00755, 0.01743, 0.00144, 0.02484, 0.03543, 0.0034, 
    0.01012, 0.02347, 0.06883, 0.01332, 0.0151, 0.00141, 0.01011, 
    0.0042, 0.00984, 0.85778, 0.006, 0.0043, 0.01878, 0.00682, 
    0.00114, 0.01064, 0.0195, 0.00233, 0.06742, 0.07392, 0.0074, 
    0.00752, 0.00962, 0.00757, 0.00579, 0.00744, 0.00506, 0.00894, 
    0.0054, 0.00353, 0.00547, 0.00112, 0.05101, 0.00541, 0.00637, 
    0.00332, 0.00193, 0.00587, 0.01303, 0.00219, 0.05986, 0.00033, 
    0.00886, 0.03566, 0.00536, 0.0046, 0.00491, 0.03314, 0.00414, 
    0.01461, 0.00632, 0.02465, 0.00152, 0.03908, 0.01715, 0.02551, 
    0.01623, 0.00144, 0.00293, 0.00894, 0.0576, 0.06191, 0.01615, 
    0.00622, 0.00922, 0.00214, 0.00372, 0.00479, 0.01475, 0.01374, 
    0.0265, 0.02273, 0.0157, 0.01762, 0.01836, 0.00796, 0.00966, 
    0.05544, 0.00045, 0.01164, 0.00289, 0.01164, 0.75564, 0.00261, 
    0.00886, 0.01214, 0.00873, 0.0116, 0.00764, 0.00204, 0.00349, 
    0.01211, 0.00012, 0.00043, 0.0192, 0.01565, 0.03623, 0.00212, 
    0.00816, 0.00566, 0.00469, 0.00247, 3e-04, 0.00557, 0.03346, 
    0.00513, 0.01508, 9e-05, 0.07649, 0.00853, 0.01481, 0.00858, 
    0.06877, 0.00857, 0.00468, 0.00234, 0.0146, 0.02422, 0.0038, 
    0.00361, 0.00462, 0.02181, 0.02404, 0.0065, 0.00623, 0.00085, 
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    0.02701, 0.01519, 4e-04, 0.00012, 0.00314, 0.00014, 0.00318, 
    0.0136, 0.02606, 0.02504, 0.0148, 0.03687, 0.00873, 0.00021, 
    0.00505, 0.00436, 0.00727, 0.0167, 0.01319, 0.01563, 0.00635, 
    0.02283, 0.01394, 0.00129, 0.0036, 0.01994, 0.02838, 0.00309, 
    0.00475, 0.00329, 0.19581, 0.11358, 0.01141, 0.02157, 0.00022, 
    0.01824, 0.00752, 0.00395, 0.00359, 0.02392, 0.00231, 0.00538, 
    0.01826, 0.00088, 0.00215, 0.01331, 0.01009, 0.03432, 0.01344, 
    0.02281, 0.00553, 0.00173, 0.00556, 0.00233, 0.16675, 0.01083, 
    0.00969, 0.01446, 0.00879, 0.00284, 0.00586, 0.00085, 0.01338, 
    0.02063, 0.01156, 0.04009, 0.02187, 0.03251, 0.00711, 0.00117, 
    0.00796, 0.00589, 0.00341, 0.01317, 0.02083, 0.01269, 0.04453, 
    0.0283, 0.02497, 0.00285, 0.01795, 0.0066, 0.00582, 0.0049, 
    0.01363, 0.0241, 0.00483, 0.00234, 0.0127, 0.03815, 0.00032, 
    0.00289, 0.01046, 0.02047, 0.00228, 0.01086, 0.00999, 0.00144, 
    0.01782, 0.03198, 0.02492, 0.01595, 0.01053, 0.00555, 0.02999, 
    0.00781, 0.019, 0.0164, 0.01336, 0.0038, 0.0043, 0.00499, 
    0.00443, 0.04757, 0.11478, 0.18121, 0.00395, 0.23238, 0.01476, 
    0.02959, 0.01648, 0.00921, 0.00263, 0.13583, 0.01686, 0.19391, 
    0.01862, 0.05687, 0.07482, 0.01695, 0.03236, 0.05562, 0.0012, 
    0.00527, 0.06459, 0.10981, 0.01596, 0.03915, 0.00512, 0.06126, 
    0.01294, 0.00802, 2.45562, 1.02683, 1.73622, 1.52249, 1.06235, 
    2.85443, 0.83453, 0.00566, 0.00164, 0.00466, 0.04963, 0.08354, 
    0.32275, 0.15772, 0.09837, 0.01103, 0.38555, 0.02938, 0.02932, 
    1.09479, 0.03529, 0.05294, 0.00817, 1.40976, 0.11133, 0.12145, 
    0.01021, 4.29457, 3.45625, 0.02739, 0.02742, 0.05391, 0.01136, 
    0.11911, 0.00433, 0.05126, 0.0392, 0.01258, 0.00358, 0.06557, 
    0.00908, 0.28427, 0.00696, 0.06481, 0.0809, 0.13234, 0.04013, 
    3.45455, 0.03756, 0.05701, 0.04528, 2.98742, 0.02558, 0.01874, 
    0.0209, 0.04035, 0.00341, 0.04379, 0.04095, 0.02113, 0.00929, 
    0.01474, 0.01925, 0.00156, 0.00066, 0.02533, 0.02119, 0.1126, 
    0.05156, 0.0291, 0.0223, 0.0024, 0.13224, 0.01846, 0.02872, 
    0.03117, 0.00662, 0.034, 0.01024, 0.00031, 0.00095, 0.00049, 
    0.00288, 0.04122, 0.02307, 0.01379, 0.03223, 0.03997, 0.00386, 
    0.03829, 0.04801, 0.04058, 0.00577, 0.03092, 0.14106, 0.00885, 
    0.02232, 0.0639, 0.01151, 0.00815, 0.01091, 0.00872, 0.00214, 
    0.00246, 0.01047, 0.02497, 0.00377, 0.02797, 0.02292, 0.00671, 
    0.04779, 0.0427, 0.0666, 0.00046, 0.03824, 0.06087, 0.01286, 
    0.03962, 0.01121, 0.0144, 0.03252, 0.02041, 0.02067, 0.02694, 
    0.04157, 0.01719, 0.02489, 0.02558, 0.02089, 0.02111, 0.00319, 
    0.0034, 0.04232, 0.04024, 0.00725, 0.0215, 0.03998, 0.0571, 
    0.01398, 0.04149, 0.0301, 0.0661, 0.03703, 0.0018, 0.05615, 
    0.01753, 0.65285, 0.114, 0.05059, 0.00376, 0.03139, 0.01046, 
    0.00719, 0.02602, 0.0119, 0.02264, 0.03489, 0.00261, 0.02551, 
    0.00659, 0.00684, 0.01494, 0.01074, 0.01527, 0.02484, 0.00426, 
    0.05551, 0.01411, 0.03134, 0.77559, 0.13779, 0.014, 0.01646, 
    0.02924, 0.05149, 0.00379, 0.03205, 0.00786, 0.0085, 0.02557, 
    0.00316, 0.01979, 0.0049, 0.0198, 0.01654, 0.01569, 0.00263, 
    0.02079, 0.00743, 0.02897, 0.01051, 0.02234, 0.22303, 0.10977, 
    0.036, 0.02201, 0.02279, 0.04258, 0.10482, 0.03752, 0.01329, 
    0.02328, 0.05358, 0.04498, 0.02736, 0.06529, 0.00689, 0.02144, 
    0.00051, 0.03399, 0.05917, 0.00789, 0.03038, 0.04545, 0.00132, 
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    0.00074, 0.06936, 0.0168, 0.01678, 0.06623, 0.0276, 0.02853, 
    0.03062, 0.00175, 0.02299, 0.09136, 0.04278, 0.00538, 0.06848, 
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    0.00337, 0.00194, 0.02624, 0.0045, 0.00719, 0.00501, 0.01551, 
    0.03953, 0.00292, 0.02187, 0.01435, 0.01039, 0.00818, 0.04737, 
    0.02357, 0.00399, 0.02218, 0.07975, 0.09209, 0.03208, 0.00586, 
    0.00762, 0.01346, 0.02157, 0.02856, 0.03061, 0.01595, 3e-04, 
    0.00647, 0.01051, 0.01759, 0.01715)), class = "data.frame", row.names = c(NA, 
-678L))

ggstatsplot::grouped_ggbetweenstats(
  data = plot_df,
  x = Layer_rec,
  y = Value,
  grouping.var = Start_rec)

Error in ggplot2::discrete_scale("colour", palette_name, pal_pal(palette = { : 
  unused argument (package = !!package)

Session Info

> sessionInfo()
R version 3.5.1 (2018-07-02)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 17763)

Matrix products: default

locale:
[1] LC_COLLATE=English_Australia.1252  LC_CTYPE=English_Australia.1252   
[3] LC_MONETARY=English_Australia.1252 LC_NUMERIC=C                      
[5] LC_TIME=English_Australia.1252    

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] ggstatsplot_0.1.3

loaded via a namespace (and not attached):
  [1] tidyselect_0.2.5          lme4_1.1-21              
  [3] robust_0.4-18.1           htmlwidgets_1.5.1        
  [5] grid_3.5.1                munsell_0.5.0            
  [7] codetools_0.2-15          future_1.14.0            
  [9] miniUI_0.1.1.1            Brobdingnag_1.2-6        
 [11] metaBMA_0.6.2             colorspace_1.4-1         
 [13] knitr_1.25                rstudioapi_0.10          
 [15] stats4_3.5.1              DescTools_0.99.28        
 [17] robustbase_0.93-5         rcompanion_2.3.0         
 [19] ggsignif_0.6.0            listenv_0.7.0            
 [21] emmeans_1.4.1             rstan_2.19.2             
 [23] repr_0.19.2               mnormt_1.5-5             
 [25] MCMCpack_1.4-4            bridgesampling_0.7-2     
 [27] coda_0.19-3               vctrs_0.2.0              
 [29] generics_0.0.2            TH.data_1.0-10           
 [31] metafor_2.1-0             xfun_0.10                
 [33] R6_2.4.0                  BayesFactor_0.9.12-4.2   
 [35] palr_0.0.6                pals_1.5                 
 [37] manipulateWidget_0.10.0   reshape_0.8.8            
 [39] logspline_2.1.13          assertthat_0.2.1         
 [41] promises_1.1.0            scales_1.1.0             
 [43] multcomp_1.4-10           ggExtra_0.9              
 [45] gtable_0.3.0              multcompView_0.1-7       
 [47] globals_0.12.4            processx_3.4.1           
 [49] mcmc_0.9-6                sandwich_2.5-1           
 [51] rlang_0.4.1               MatrixModels_0.4-1       
 [53] EMT_1.1                   zeallot_0.1.0            
 [55] splines_3.5.1             TMB_1.7.15               
 [57] lazyeval_0.2.2            dichromat_2.0-0          
 [59] broom_0.5.2               scico_1.1.0              
 [61] inline_0.3.15             abind_1.4-5              
 [63] rgl_0.100.30              reshape2_1.4.3           
 [65] modelr_0.1.5              crosstalk_1.0.0          
 [67] backports_1.1.5           httpuv_1.5.2             
 [69] tools_3.5.1               psych_1.8.12             
 [71] ggplot2_3.2.1             ellipsis_0.3.0           
 [73] WRS2_1.0-0                ez_4.4-0                 
 [75] Rcpp_1.0.3                plyr_1.8.4               
 [77] base64enc_0.1-3           jmvcore_1.0.8            
 [79] purrr_0.3.3               ps_1.3.0                 
 [81] prettyunits_1.0.2         pbapply_1.4-2            
 [83] cowplot_1.0.0             zoo_1.8-6                
 [85] LaplacesDemon_16.1.1      haven_2.1.1              
 [87] ggrepel_0.8.1             cluster_2.0.7-1          
 [89] furrr_0.1.0               magrittr_1.5             
 [91] data.table_1.12.2         openxlsx_4.1.0.1         
 [93] manipulate_1.0.1          SparseM_1.77             
 [95] lmtest_0.9-37             mvtnorm_1.0-11           
 [97] broomExtra_0.0.6          sjmisc_2.8.2             
 [99] matrixStats_0.55.0        hms_0.5.1                
[101] mime_0.7                  xtable_1.8-4             
[103] rio_0.5.16                sjstats_0.17.7           
[105] pairwiseComparisons_0.1.2 broom.mixed_0.2.4        
[107] readxl_1.3.1              gridExtra_2.3            
[109] rstantools_2.0.0          compiler_3.5.1           
[111] tibble_2.1.3              maps_3.3.0               
[113] crayon_1.3.4              minqa_1.2.4              
[115] StanHeaders_2.19.0        htmltools_0.4.0          
[117] mgcv_1.8-27               mc2d_0.1-18              
[119] pcaPP_1.9-73              later_1.0.0              
[121] jcolors_0.0.4             libcoin_1.0-5            
[123] tidyr_1.0.0               rrcov_1.4-7              
[125] expm_0.999-4              sjlabelled_1.1.1         
[127] jmv_1.0.8                 MASS_7.3-51.1            
[129] boot_1.3-23               Matrix_1.2-15            
[131] car_3.0-3                 cli_1.1.0                
[133] parallel_3.5.1            insight_0.7.0            
[135] forcats_0.4.0             pkgconfig_2.0.3          
[137] fit.models_0.5-14         statsExpressions_0.1.1   
[139] coin_1.3-1                foreign_0.8-71           
[141] skimr_2.0.1               oompaBase_3.2.9          
[143] paletteer_0.2.1.9000      ggcorrplot_0.1.3         
[145] webshot_0.5.1             estimability_1.3         
[147] stringr_1.4.0             callr_3.3.2              
[149] digest_0.6.22             parameters_0.3.0         
[151] cellranger_1.1.0          nortest_1.0-4            
[153] curl_4.1                  modeltools_0.2-22        
[155] shiny_1.4.0               gtools_3.8.1             
[157] quantreg_5.51             rjson_0.2.20             
[159] nloptr_1.2.1              lifecycle_0.1.0          
[161] nlme_3.1-137              jsonlite_1.6             
[163] carData_3.0-2             groupedstats_0.1.0       
[165] mapproj_1.2.6             pillar_1.4.2             
[167] lattice_0.20-38           loo_2.1.0                
[169] fastmap_1.0.1             DEoptimR_1.0-8           
[171] pkgbuild_1.0.5            survival_2.43-3          
[173] glue_1.3.1                bayestestR_0.4.0         
[175] zip_2.0.4                 stringi_1.4.3            
[177] performance_0.4.0         rematch2_2.1.0           
[179] rsample_0.0.5             dplyr_0.8.3
IndrajeetPatil commented 5 years ago

This is because you are currently using the development version of paletteer, which made breaking changes to its syntax. In future, I will start supporting the new version of paletteer.

scbrown86 commented 5 years ago

Thanks a lot - rolling back to paletteer 0.2.1 (off CRAN) solved the issue.

MichaelPeibo commented 4 years ago

I am using paletteer 1.0.0, but still got this error, any suggestion? Should I roll back to 0.2.1?

I changed to another conda env, it works. But i haven't figure out which package cause this error.

this one works:

R version 3.6.1 (2019-07-05) Platform: x86_64-conda_cos6-linux-gnu (64-bit) Running under: Ubuntu 16.04.3 LTS

Matrix products: default BLAS/LAPACK: /home/xupb/anaconda3/envs/urd/lib/R/lib/libRblas.so

locale: [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
[3] LC_TIME=zh_CN.UTF-8 LC_COLLATE=en_US.UTF-8
[5] LC_MONETARY=zh_CN.UTF-8 LC_MESSAGES=en_US.UTF-8
[7] LC_PAPER=zh_CN.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=zh_CN.UTF-8 LC_IDENTIFICATION=C

attached base packages: [1] stats graphics grDevices utils datasets methods base

other attached packages: [1] ggstatsplot_0.3.1 ggplot2_3.3.0 tibble_2.1.3 dplyr_0.8.4 [1] tidyselect_1.0.0 lme4_1.1-21
[3] grid_3.6.1 munsell_0.5.0
[5] codetools_0.2-16 effectsize_0.2.0
[7] miniUI_0.1.1.1 withr_2.1.2
[9] Brobdingnag_1.2-6 metaBMA_0.6.2
[11] colorspace_1.4-1 knitr_1.28
[13] rstudioapi_0.11 stats4_3.6.1
[15] DescTools_0.99.32 ipmisc_1.2.0
[17] ggsignif_0.6.0 rcompanion_2.3.25
[19] labeling_0.3 emmeans_1.4.5
[21] rstan_2.19.3 repr_1.1.0
[23] bbmle_1.0.23.1 mnormt_1.5-6
[25] farver_2.0.3 bridgesampling_1.0-0
[27] coda_0.19-3 vctrs_0.2.3
[29] generics_0.0.2 TH.data_1.0-10
[31] metafor_2.1-0 xfun_0.12
[33] R6_2.4.1 BayesFactor_0.9.12-4.2
[35] palr_0.2.0 pals_1.6
[37] reshape_0.8.8 logspline_2.1.15
[39] assertthat_0.2.1 promises_1.1.0
[41] scales_1.1.0 multcomp_1.4-12
[43] ggExtra_0.9 gtable_0.3.0
[45] multcompView_0.1-8 processx_3.4.2
[47] sandwich_2.5-1 rlang_0.4.5
[49] MatrixModels_0.4-1 EMT_1.1
[51] zeallot_0.1.0 splines_3.6.1
[53] TMB_1.7.16 dichromat_2.0-0
[55] broom_0.5.5 scico_1.1.0
[57] prismatic_0.2.0 inline_0.3.15
[59] reshape2_1.4.3 abind_1.4-5
[61] modelr_0.1.6 backports_1.1.5
[63] httpuv_1.5.2 tools_3.6.1
[65] psych_1.9.12.31 ellipsis_0.3.0
[67] WRS2_1.0-0 ez_4.4-0
[69] Rcpp_1.0.3 plyr_1.8.5
[71] base64enc_0.1-3 jmvcore_1.2.5
[73] purrr_0.3.3 ps_1.3.2
[75] prettyunits_1.1.1 pbapply_1.4-2
[77] cowplot_1.0.0 zoo_1.8-7
[79] LaplacesDemon_16.1.4 haven_2.2.0
[81] ggrepel_0.8.1 cluster_2.1.0
[83] magrittr_1.5 data.table_1.12.8
[85] openxlsx_4.1.4 lmtest_0.9-37
[87] mvtnorm_1.1-0 broomExtra_2.0.0
[89] sjmisc_2.8.3 matrixStats_0.55.0
[91] hms_0.5.3 mime_0.9
[93] xtable_1.8-4 rio_0.5.16
[95] sjstats_0.17.9 pairwiseComparisons_0.2.5 [97] broom.mixed_0.2.4 readxl_1.3.1
[99] gridExtra_2.3 rstantools_2.0.0
[101] compiler_3.6.1 bdsmatrix_1.3-4
[103] maps_3.3.0 crayon_1.3.4
[105] minqa_1.2.4 StanHeaders_2.19.2
[107] htmltools_0.4.0 mgcv_1.8-31
[109] mc2d_0.1-18 later_1.0.0
[111] jcolors_0.0.4 tidyr_1.0.2
[113] libcoin_1.0-5 expm_0.999-4
[115] sjlabelled_1.1.3 jmv_1.2.5
[117] MASS_7.3-51.5 boot_1.3-24
[119] Matrix_1.2-18 car_3.0-6
[121] cli_2.0.2 parallel_3.6.1
[123] insight_0.8.2 forcats_0.4.0
[125] pkgconfig_2.0.3 metaplus_0.7-11
[127] statsExpressions_0.3.1 numDeriv_2016.8-1.1
[129] coin_1.3-1 foreign_0.8-75
[131] skimr_2.1 oompaBase_3.2.9
[133] paletteer_1.0.0 ggcorrplot_0.1.3
[135] estimability_1.3 stringr_1.4.0
[137] callr_3.4.2 digest_0.6.25
[139] parameters_0.5.0 fastGHQuad_1.0
[141] cellranger_1.1.0 nortest_1.0-4
[143] curl_4.3 shiny_1.4.0
[145] gtools_3.8.1 modeltools_0.2-23
[147] rjson_0.2.20 nloptr_1.2.1
[149] lifecycle_0.1.0 nlme_3.1-144
[151] jsonlite_1.6.1 carData_3.0-3
[153] groupedstats_0.2.0 mapproj_1.2.7
[155] fansi_0.4.1 pillar_1.4.3
[157] lattice_0.20-40 loo_2.2.0
[159] fastmap_1.0.1 pkgbuild_1.0.6
[161] survival_3.1-8 glue_1.3.1
[163] bayestestR_0.5.2 zip_2.0.4
[165] stringi_1.4.6 performance_0.4.4
[167] rematch2_2.1.0

this one cause error:

R version 3.5.1 (2018-07-02) Platform: x86_64-conda_cos6-linux-gnu (64-bit) Running under: Ubuntu 16.04.3 LTS

Matrix products: default BLAS/LAPACK: /home/xupb/anaconda3/envs/seuratv3/lib/R/lib/libRblas.so

locale: [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
[3] LC_TIME=zh_CN.UTF-8 LC_COLLATE=en_US.UTF-8
[5] LC_MONETARY=zh_CN.UTF-8 LC_MESSAGES=en_US.UTF-8
[7] LC_PAPER=zh_CN.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=zh_CN.UTF-8 LC_IDENTIFICATION=C

attached base packages: [1] stats graphics grDevices utils datasets methods base

other attached packages: [1] WRS2_1.0-0 ggstatsplot_0.1.1 ggplot2_3.2.1 tibble_2.1.3
[5] dplyr_0.8.5

loaded via a namespace (and not attached): [1] readxl_1.3.1 pairwiseComparisons_0.1.0 [3] backports_1.1.5 broomExtra_2.0.0
[5] plyr_1.8.5 repr_1.1.0
[7] lazyeval_0.2.2 TMB_1.7.16
[9] splines_3.5.1 TH.data_1.0-10
[11] rstantools_2.0.0 inline_0.3.15
[13] digest_0.6.23 htmltools_0.4.0
[15] jcolors_0.0.4 fansi_0.4.1
[17] magrittr_1.5 paletteer_1.0.0
[19] cluster_2.1.0 openxlsx_4.1.4
[21] modelr_0.1.6 matrixStats_0.55.0
[23] MCMCpack_1.4-4 sandwich_2.5-1
[25] prettyunits_1.0.2 colorspace_1.4-1
[27] skimr_2.1 ggrepel_0.8.2
[29] haven_2.2.0 xfun_0.3
[31] libcoin_1.0-5 callr_3.4.2
[33] crayon_1.3.4 jsonlite_1.6.1
[35] lme4_1.1-21 survival_3.1-8
[37] zoo_1.8-7 glue_1.3.1
[39] palr_0.2.0 pals_1.6
[41] gtable_0.3.0 emmeans_1.4.5
[43] MatrixModels_0.4-1 sjstats_0.17.9
[45] sjmisc_2.8.3 scico_1.1.0
[47] statsExpressions_0.1.1 car_3.0-6
[49] pkgbuild_1.0.6 rstan_2.19.3
[51] maps_3.3.0 abind_1.4-5
[53] SparseM_1.78 scales_1.1.0
[55] mvtnorm_1.1-0 miniUI_0.1.1.1
[57] Rcpp_1.0.3 xtable_1.8-4
[59] performance_0.4.4 foreign_0.8-74
[61] mapproj_1.2.7 stats4_3.5.1
[63] StanHeaders_2.21.0-1 rcompanion_2.3.25
[65] modeltools_0.2-23 logspline_2.1.15
[67] ellipsis_0.3.0 pkgconfig_2.0.3
[69] reshape_0.8.8 loo_2.2.0
[71] metaBMA_0.6.2 multcompView_0.1-8
[73] ez_4.4-0 tidyselect_0.2.5
[75] rlang_0.4.5 reshape2_1.4.3
[77] later_1.0.0 ggcorrplot_0.1.3
[79] effectsize_0.2.0 cellranger_1.1.0
[81] munsell_0.5.0 tools_3.5.1
[83] LaplacesDemon_16.1.4 cli_2.0.2
[85] jmvcore_1.2.5 sjlabelled_1.1.3
[87] broom_0.5.0 EMT_1.1
[89] stringr_1.4.0 fastmap_1.0.1
[91] rematch2_2.1.0 mcmc_0.9-6.1
[93] processx_3.4.2 knitr_1.26
[95] zip_2.0.4 purrr_0.3.3
[97] coin_1.3-1 jmv_1.2.5
[99] pbapply_1.4-2 nlme_3.1-143
[101] mime_0.8 quantreg_5.54
[103] groupedstats_0.1.1 ggExtra_0.9
[105] compiler_3.5.1 rstudioapi_0.11
[107] curl_4.3 ggsignif_0.6.0
[109] DescTools_0.99.29 stringi_1.4.5
[111] ps_1.3.2 parameters_0.5.0
[113] Brobdingnag_1.2-6 forcats_0.5.0
[115] purrrlyr_0.0.5 lattice_0.20-38
[117] Matrix_1.2-18 psych_1.9.12.31
[119] nloptr_1.2.1 vctrs_0.2.3
[121] pillar_1.4.3 lifecycle_0.2.0
[123] mc2d_0.1-18 lmtest_0.9-37
[125] bridgesampling_1.0-0 estimability_1.3
[127] data.table_1.11.6 cowplot_1.0.0
[129] insight_0.8.2 httpuv_1.5.2
[131] oompaBase_3.2.9 R6_2.4.1
[133] promises_1.1.0 rio_0.5.16
[135] gridExtra_2.3 BayesFactor_0.9.12-4.2
[137] codetools_0.2-16 dichromat_2.0-0
[139] boot_1.3-24 MASS_7.3-51.5
[141] gtools_3.8.1 assertthat_0.2.1
[143] rjson_0.2.20 nortest_1.0-4
[145] withr_2.1.2 metafor_2.1-0
[147] mnormt_1.5-6 multcomp_1.4-12
[149] broom.mixed_0.2.4 expm_0.999-4
[151] mgcv_1.8-31 bayestestR_0.5.2
[153] parallel_3.5.1 hms_0.4.2
[155] grid_3.5.1 tidyr_1.0.2
[157] coda_0.19-3 minqa_1.2.4
[159] carData_3.0-3 shiny_1.4.0
[161] base64enc_0.1-3

IndrajeetPatil commented 4 years ago

No, you should no longer be getting this error.

Can you please post the exact error you get and the traceback for it?

MichaelPeibo commented 4 years ago

Hi @IndrajeetPatil Sorry for delayed reply. Here is traceback():

5: paletteer::scale_color_paletteer_d(package = !!package, palette = !!palette, direction = direction) 4: aesthetic_addon(plot = plot, x = data %>% dplyr::pull({ { x } }), xlab = xlab, ylab = ylab, title = title, subtitle = subtitle, caption = caption, ggtheme = ggtheme, ggstatsplot.layer = ggstatsplot.layer, package = package, palette = palette, direction = direction, ggplot.component = ggplot.component) 3: .f(data = .l[[1L]][[i]], title = .l[[2L]][[i]], ...) 2: purrr::pmap(.l = list(data = df, title = paste(title.prefix, ": ", names(df), sep = "")), .f = ggstatsplot::ggwithinstats, x = { { x } }, y = { { y } }, outlier.label = { { outlier.label } }, type = type, pairwise.comparisons = pairwise.comparisons, pairwise.annotation = pairwise.annotation, pairwise.display = pairwise.display, p.adjust.method = p.adjust.method, effsize.type = effsize.type, partial = partial, effsize.noncentral = effsize.noncentral, bf.prior = bf.prior, bf.message = bf.message, sphericity.correction = sphericity.correction, results.subtitle = results.subtitle, xlab = xlab, ylab = ylab, subtitle = subtitle, caption = caption, sample.size.label = sample.size.label, k = k, conf.level = conf.level, nboot = nboot, tr = tr, path.point = path.point, path.mean = path.mean, sort = sort, sort.fun = sort.fun, axes.range.restrict = axes.range.restrict, mean.label.size = mean.label.size, mean.label.fontface = mean.label.fontface, mean.label.color = mean.label.color, notch = notch, notchwidth = notchwidth, linetype = linetype, outlier.tagging = outlier.tagging, outlier.label.color = outlier.label.color, outlier.color = outlier.color, outlier.shape = outlier.shape, outlier.coef = outlier.coef, mean.plotting = mean.plotting, mean.ci = mean.ci, mean.size = mean.size, mean.color = mean.color, ggtheme = ggtheme, ggstatsplot.layer = ggstatsplot.layer, package = package, palette = palette, direction = direction, ggplot.component = ggplot.component, return = return, messages = messages) 1: ggstatsplot::grouped_ggwithinstats(data = dplyr::filter(data_bugs, condition %in% c("LDLF", "LDHF")), x = condition, y = desire, xlab = "Condition", ylab = "Desire to kill an artrhopod", grouping.var = region, outlier.tagging = TRUE, outlier.label = education, ggtheme = hrbrthemes::theme_ipsum_tw(), ggstatsplot.layer = FALSE, messages = FALSE)

IndrajeetPatil commented 4 years ago

@MichaelPeibo I can't reproduce this.

Note that below I am using the same example as you but with a different dataset:

library(ggstatsplot)

ggstatsplot::grouped_ggwithinstats(
  data = dplyr::filter(bugs_long,
                       condition %in% c("LDLF", "LDHF"),
                       region %in% c("Europe", "North America")),
  x = condition,
  y = desire,
  xlab = "Condition",
  ylab = "Desire to kill an artrhopod",
  grouping.var = region,
  outlier.tagging = TRUE,
  outlier.label = education,
  ggtheme = hrbrthemes::theme_ipsum_tw(),
  ggstatsplot.layer = FALSE,
  messages = FALSE
)

Created on 2020-03-18 by the reprex package (v0.3.0)

Session info ``` r devtools::session_info() #> - Session info --------------------------------------------------------------- #> setting value #> version R Under development (unstable) (2020-02-28 r77874) #> os Windows 10 x64 #> system x86_64, mingw32 #> ui RTerm #> language (EN) #> collate English_United States.1252 #> ctype English_United States.1252 #> tz Europe/Berlin #> date 2020-03-18 #> #> - Packages ------------------------------------------------------------------- #> ! package * version date lib #> abind 1.4-5 2016-07-21 [1] #> assertthat 0.2.1 2019-03-21 [1] #> backports 1.1.5 2019-10-02 [1] #> base64enc 0.1-3 2015-07-28 [1] #> BayesFactor 0.9.12-4.2 2018-05-19 [1] #> bayestestR 0.5.2.1 2020-03-16 [1] #> bbmle 1.0.23.1 2020-02-03 [1] #> bdsmatrix 1.3-4 2020-01-13 [1] #> boot 1.3-24 2019-12-20 [2] #> bridgesampling 1.0-0 2020-02-26 [1] #> Brobdingnag 1.2-6 2018-08-13 [1] #> broom 0.5.3.9000 2020-03-01 [1] #> broom.mixed 0.2.4.9000 2020-03-09 [1] #> broomExtra 2.5.0 2020-03-17 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Github (easystats/insight@e0b229b) #> local #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> Github (r-lib/lifecycle@355dcba) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> Github (easystats/performance@913fee0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> Github (r-lib/usethis@3e7c8b2) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> CRAN (R 4.0.0) #> #> [1] C:/Users/inp099/Documents/R/win-library/4.0 #> [2] C:/Program Files/R/R-devel/library #> #> D -- DLL MD5 mismatch, broken installation. ```
MichaelPeibo commented 4 years ago

@IndrajeetPatil It is OK. I move to another conda env with R/3.6.1. and it worked. Thanks!