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這是一個益智遊戲。我正在計算大型數據集的線性模型，並使用「geom_text_repel」將公式粘貼到圖上。 我跑我的腳本成功了很多次，但突然開始收到以下錯誤：多次成功運行r腳本後出現「lm.fit 0（非NA）情況下的錯誤」
錯誤lm.fit（X，Y，偏移=偏移，singular.ok = singular.ok，.. ） ：0（非NA）的情況下
這令人生氣，因爲我沒有改變任何東西。我已經詳細閱讀了這個問題，但還沒有找到解決方案。很多人說這是由於在數據集的每一行都有NAs，因此缺少協變量（lm called from inside dlply throws "0 (non-NA) cases" error [r]和R linear regression issue : lm.fit(x, y, offset = offset, singular.ok = singular.ok, ...)和Error in lm.fit(x, y, offset = offset, singular.ok = singular.ok, ...) 0 non-na cases）。我的數據集也相當齊全：
> apply(ro_aue_SO,1,function(x) sum(is.na(x)))
40 41 42 43 44 45 46 47 48 49 50 51 52 53
0 0 0 0 0 0 0 0 0 0 0 0 0 1
有此數據與ZERO的NAS其他子集，我仍然得到同樣的錯誤。我試過使用na.action = na.omit，我在錯誤上使用了traceback（）以獲得更多的見解，我嘗試了不同的數據輸入方法 - 沒有任何工作。由於錯誤消息剛好在腳本運行幾個小時後出現，我想知道這是否是系統問題。我在OSX 10.12.6上使用RStudio v1.0.153和r 3.4.2。
幫助！幫幫我！幫幫我！並且預先感謝你。
這是我（簡化）代碼：
holes_SO <- read.csv(file = 'data.csv', sep = ",", header = TRUE)
holes_SO$depth <- factor(holes_SO$depth)
ro_aue_SO <- subset(holes_SO, holes_SO$field == "ROA")
ot_slope_SO <- subset(holes_SO, holes_SO$field == "OTS")
#Set-up the empty equation
lm_origin_eqn <- function(m){
eq <- substitute(italic(y) == b %.% italic(x)*","~~italic(r)^2~"="~r2,
list(b = format(coef(m)[1], digits = 2),
r2 = format(summary(m)$r.squared, digits = 3)))
as.character(as.expression(eq));
}
roa_RTO <- ggplot(data = ro_aue_SO, aes(x = soc_concentration_kg_m3, y = co2_flux_µmol_c_m2_s1, color = depth, shape = depth)) +
geom_point(size = 3) +
labs(x = "SOC concentration", y = "CO2 Flux") +
labs(color="Depth", shape= "Depth") +
ggtitle(expression('RO Aue, CO'[2]*'')) +
geom_smooth(aes(color = depth), method=lm, se=FALSE, formula=y~x-1, fullrange = TRUE) +
xlim(-5,45) +
theme(plot.title = element_text(size = 16, hjust = 0.5, face = "bold"),
axis.text = element_text(size = 10),
axis.title = element_text(size = 12)) +
scale_color_discrete(drop=FALSE) +
scale_shape_discrete(drop=FALSE)
#THIS IS WHERE THE ERROR OCCURS
#fill in the linear equation
roa_eqns <- ro_aue_SO %>% split(.$depth) %>%
map(~ lm(co2_flux_µmol_c_m2_s1 ~ soc_concentration_kg_m3 - 1, data = .)) %>%
map(lm_origin_eqn) %>%
do.call(rbind, .) %>%
as.data.frame() %>%
set_names("equation") %>%
mutate(depth = rownames(.))
#paste equations onto graph
roa_RTO_equations <- roa_RTO + geom_text_repel(data = roa_eqns, aes(x = c(0, 0, 0, 0), y = c(125, 115, 105, 95), label = equation),
parse = TRUE, segment.size = 0, show.legend = FALSE)
而且數據的一個小樣本（使用生成的 「dput（holes_SO）」）：
structure(list(sample_id = structure(c(1L, 2L, 3L, 4L, 10L, 11L,
12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L,
25L, 26L, 29L, 30L, 31L, 32L, 27L, 28L, 33L, 36L, 37L, 38L, 39L,
34L, 35L, 5L, 6L, 7L, 8L, 9L, 40L, 41L, 42L, 43L, 44L, 45L, 46L,
47L, 48L, 49L, 50L, 51L, 52L, 53L), .Label = c("OTS1-0", "OTS1-30",
"OTS1-60", "OTS1-90", "OTS10-0", "OTS10-20", "OTS10-30", "OTS10-60",
"OTS10-90", "OTS2-0", "OTS3-0", "OTS3-30", "OTS3-60", "OTS3-90",
"OTS4-0", "OTS5-0", "OTS5-30", "OTS5-60", "OTS5-90", "OTS6-0",
"OTS7-0", "OTS7-20", "OTS7-30", "OTS7-60", "OTS7-90", "OTS8-0",
"OTS8-120A", "OTS8-120B", "OTS8-20", "OTS8-30", "OTS8-60", "OTS8-90",
"OTS9-0", "OTS9-120A", "OTS9-120B", "OTS9-20", "OTS9-30", "OTS9-60",
"OTS9-90", "ROA1-0", "ROA1-30", "ROA1-60", "ROA1-90", "ROA2-0",
"ROA2-30", "ROA3-0", "ROA3-30", "ROA3-60", "ROA3-90", "ROA4-0",
"ROA4-30", "ROA4-60", "ROA4-90"), class = "factor"), site = 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, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L), .Label = c("OT", "RO"), class = "factor"), field = 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, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L), .Label = c("OTS", "ROA"), class = "factor"),
hole_number = c(1L, 1L, 1L, 1L, 2L, 3L, 3L, 3L, 3L, 4L, 5L,
5L, 5L, 5L, 6L, 7L, 7L, 7L, 7L, 7L, 8L, 8L, 8L, 8L, 8L, 8L,
8L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 10L, 10L, 10L, 10L, 10L,
1L, 1L, 1L, 1L, 2L, 2L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L),
depth = c(0L, 30L, 60L, 90L, 0L, 0L, 30L, 60L, 90L, 0L, 0L,
30L, 60L, 90L, 0L, 0L, 20L, 30L, 60L, 90L, 0L, 20L, 30L,
60L, 90L, 120L, 120L, 0L, 20L, 30L, 60L, 90L, 120L, 120L,
0L, 20L, 30L, 60L, 90L, 0L, 30L, 60L, 90L, 0L, 30L, 0L, 30L,
60L, 90L, 0L, 30L, 60L, 90L), co2_flux_µmol_c_m2_s1 = c(1.710293078,
0.30924686, 0.36469938, 0.227477037, 1.254479063, 0.752737414,
2.257215969, 11.50282226, 3.566654093, 0.69900321, 1.591361818,
13.92149665, 22.73002129, 22.45049, 1.109443533, 7.406644295,
7.855618003, 17.78010488, 6.471314337, 5.315970134, 6.347455312,
11.54719043, 10.11479135, 11.47752926, 2.805488908, 5.222756475,
4.377681384, 7.173613131, 14.51864231, 9.729229653, 4.564367185,
10.17710718, 7.70956059, 4.382202183, 3.321182297, 3.858269154,
7.542932281, 19.88469738, 10.55216436, 3.572542676, 6.530127468,
10.78088543, 12.82422246, 3.093747739, 6.956941294, 3.316715055,
8.781949843, 7.684561849, 6.142716566, 2.69743231, 9.67046938,
7.018872033, 9.475929618), soc_concentration_kg_m3 = c(16.57,
1.28, 1.86, 1.63, 16.88, 16.8, 6.59, 5.7, 1.33, 15, 15.67,
3.8, 3.95, 3.95, 17.17, 20.5, 21.1, 4.94, 4.27, 2.43, 14.9,
16.52, 4.12, 4.59, 4.59, 4.24, 4.24, 15.36, 15.93, 15.93,
7.14, 7.14, 3.87, 3.87, 19.21, 20.24, 6.45, 5, 4.85, 40,
7.78, 7.78, 3.6, 41.25, 23, 36.67, 23.04, 12.4, 3.33, 35.71,
9.66, 12.31, NA)), .Names = c("sample_id", "site", "field",
"hole_number", "depth", "co2_flux_µmol_c_m2_s1", "soc_concentration_kg_m3"
), class = "data.frame", row.names = c(NA, -53L))
這裏是我做過什麼得到，應該仍然得到（與稍有不同的顏色/標籤），從運行上述腳本： 
您是否更新了tidyverse軟件包？哈德利毫不猶豫地做出突變。 – Roland
也許你有0級的'ro_aue_SO $深度'一些級別？如果是這樣，請嘗試在您的鏈條中添加「水滴」。 – Aaron
@羅蘭，也許？大概。我一直在專門研究這個腳本幾天。有什麼辦法可以使我可能做的事情失去意義嗎？ – jls