我想在箱線圖中可視化一些數據。我有用 Python 編寫的代碼，但我想用 R 重寫它。這是 Python 中的代碼：fig, ax = plt.subplots()d = df.to_numpy()f = [d[m] for d, m in zip(d.T, ~np.isnan(d).T)]ax.boxplot(f)ax.set_ylim([0, 150])ax.set_ylabel('IRE binding activity (%)', fontsize=14)ax.set_xticklabels(['NF', 'F'])ax.tick_params(axis='x', labelsize=14, labelrotation=45)ax.tick_params(axis='y', labelsize=14)glue('fig1', fig, display=False)這是我在 R 中嘗試過的：na_if(d, df)f <- [d[m] for d, m in zip(d.T, ~np.isnan(d).T)]boxplot(f)boxplot(NF ~ F, data = f, col = "lightgray", varwidth = TRUE,         main = "IRE binding activity for non-failing (NF) and failing (F) hearts.",        ylab = "IRE binding activity (%)",xlab = "['NF', 'F']")fivenum(f)我的數據代碼包含一個 t 檢驗函數：labels <- list('non-failing heart (NF)', 'failing heart (F)')data <- list(c(99, 52), c(96, 40), c(100, 38), c(105, 18),              c(NA_integer_, 11), c(NA_integer_, 5), c(NA_integer_, 42),              c(NA_integer_, 55), c(NA_integer_, 53), c(NA_integer_, 39),             c(NA_integer_, 42), c(NA_integer_, 50))df <- setNames(do.call(rbind.data.frame,                        lapply(data, function(d) data.frame(d[1], d[2]))),              labels)    df                                                      results <- t.test(df[['non-failing heart (NF)']], df[['failing heart (F)']])results                           results$statisticresults$estimateresults$p.value                           ceiling(results$p.value * 1000.0)/ 1000.0