在R中可视化Python编写的箱线图的问题

Question

我想在箱线图中可视化一些数据。我有用Python编写的代码，但我想用R重写它

这是Python中的代码：

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)

这是我在R中尝试过的：

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)

我的数据代码包括一个t-test函数：

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$statistic
results$estimate
results$p.value
                           
ceiling(results$p.value * 1000.0)/ 1000.0

Answer 1

我已经成功地在R中重写了代码，我想与您分享解决方案：

boxplot(df[1:2],
        data=df,
        main="box plot",
        ylab="Degree Fahrenheit",
        col="orange",
        border="brown",
        ylim = c(0, 120)
)