如何使用 geom_ribbon 绘制图表

Question

我有三张桌子：

Upper  Bound  
    Q      C   
    1     30  
    2     50  
    3     40

Lower  Bound      
    Q      C       
    1     10   
    2     15     
    3     20 

不良数据：

Q      C      Name  
1      50     Sample 1  
2      40     Sample 1  
3      30     Sample 1  
1      0      Sample 2  
2      60     Sample 2  
3      5      Sample 2

我想要一个图表，以灰色绘制下限和上限，并填充之间的所有内容，并用不同的颜色和图例在顶部绘制不良样本：

plot <- ggplot(Bad_Data, aes(x = Bad_Data$Q, y = Bad_Data$C, group = 1))
plot + geom_line(aes(color = N)) + geom_ribbon(aes(ymin = Lower_Bound$C, ymax = Upper_Bound$C))  

我尝试过，但它给了我这个错误：

错误：美学必须是长度 1 或与数据 (624) 相同：ymin、ymax、x、y、group

谁能帮助我？

Answer 1

我用geom_ribbon预测来遮蔽预测置信区间。您可以组合多个数据框以使其全部正常工作。您需要传递数据框、x 值（日期）和 y 值（之间有阴影的两条线）。

以下函数用于绘制序列、模型回测、预测和置信区间。

plot_predictions <- function(start_date) {
    # function to use Plotly to plot the predictions,
    # confidence interval and actuals
    # inputs:
    # plot_df, starting date of the series, r-pred (prediction data frame)

# output: interactive plot of the actual and the model backtest

# set the end date parameter first
pred_end <- as.Date(tail(r_pred$week_ending, 1))


p <- ggplot() + 
# add the backtest series from the backtest data frame
geom_line(data=r_back, mapping = aes(x=week_ending, y=Backtest_Model,
                                   color = 'Backtest Model'), linetype='solid') + 

# add the actual series from the training dataframe
# use aes_string to pass the series variable
geom_line(data=r_train, mapping = aes_string(x='week_ending', y=series,
                                   color = 'series'), linetype='solid') +

# r_pred holds he predictions and confidence levels
geom_line(data=r_pred, mapping = aes(x=week_ending, y=Predictions,
                                   color = 'Predictions'), linetype='solid') + 


# upper forecast limit
geom_line(data=r_pred, mapping = aes(x=week_ending, y=upper_conf_limit,
                                   color = 'upper_limit'), linetype='solid') + 

# lower forecast limit
geom_line(data=r_pred, mapping = aes(x=week_ending, y=lower_conf_limit,
                                   color = 'lower_limit'), linetype='solid') + 


# format the plot 
scale_linetype_manual() + 

# prediction_pal is a five color palette
scale_color_manual(values = pred_pal, name = "Series") +

# fill between lines with geom_ribbon using a blue toned down by alpha
geom_ribbon(data=r_pred, aes(x = week_ending, 
                             ymin=lower_conf_limit,
                             ymax=upper_conf_limit),
            fill="blue", alpha=0.2) + 



# format the y axis with commas
scale_y_continuous(label = comma)

# extend the date series from the beginning to end of predictions
scale_x_date(breaks = pretty_breaks(20),
             limits = c(as.Date(start_date), pred_end)) +  


# add the custom theme    
theme_bryan() + 

# customize the plot
# rotate the text of the x axis
theme(axis.text.x = element_text(angle= 45, hjust = 1)) + 
labs(fill = 'Series') + 
guides(color = guide_legend(reverse = FALSE)) +


# add the holiday lines as vertical red dotted lines
# holidays in the training set
geom_vline(xintercept = as.numeric(holiday$week_ending),
           linetype='dotted', colour = 'red', alpha =0.5) + 

# holidays in the forecasting set
    geom_vline(xintercept = as.numeric(r_exog_lines$week_ending),
               linetype='dotted', colour = 'red', alpha =0.5)

# output the plot in Plotly format
subplot(with_options(list(digits = 0),
                     ggplotly(p))) %>% 
    layout(legend = list(orientation = 'v', y = .1, x = 0))
}

使用称为“riders”的系列series <- 'riders'会产生以下结果。