geom_boxplot(R)的库存烛台绘图问题

Question

我正在使用geom_boxplot股票市场数据绘制烛台.问题在于,单个箱线图的上边缘和下边缘以及上部晶须端点在y轴上显示出比其对应值更高的方式.虽然每个箱线图的相对高度(上边缘和下边缘之间的差异)和下部晶须的终点都很好.这是我的代码:

candlestickPlot <- function(x){

library("ggplot2")

# x is a data.frame with columns 'date','open','high','low','close'
x$candleLower <- pmin(x$open, x$close)
x$candleUpper <- pmax(x$open, x$close)
x$candleMiddle <- NA
x$fill <- "red"
x$fill[x$open < x$close] = "green"

# Draw the candlesticks
g <- ggplot(x, aes(x=date, lower=candleLower, middle=candleMiddle, upper=candleUpper, ymin=low, ymax=high)) 
g <- g + geom_boxplot(stat='identity', aes(group=date, fill=fill))
g 
}

这是x:

    date     close volume  open  high   low
5 2013-12-30 25.82 3525026 27.30 27.76  25.7
4 2013-12-31 27.41 5487204 25.25 27.70 25.25
3 2014-01-02 30.70 7835374 29.25 31.24 29.21
2 2014-01-03 30.12 4577278 31.49 31.80 30.08
1 2014-01-06 30.65 4042724 30.89 31.88 30.37

我在这里做错了吗？

Answer 1

与ggplot2您使用的方式相比,有更有效的方法来创建OHLC烛台geom_boxplot.您的代码与链接中的示例非常相似:http: //www.perdomocore.com/2012/using-ggplot-to-make-candlestick-charts-alpha/

似乎很多人在网上放置ggplot烛台示例,这些示例基于该链接中使用的示例geom_boxplot.但绘图的问题geom_boxplot在于,随着绘制条形图数量的增加,绘图本身在生成绘图时变得缓慢.

以下是使用烛台/ OHLC条绘制财务数据的计算速度更快的解决方案:

library(ggplot2)
library(quantmod)
FOSL <- getSymbols("FOSL", from="2015-01-01", auto.assign=FALSE)
names(FOSL) <- gsub("^.+\\.","",names(FOSL))  # remove "FOSL." from column names

rng <- "2015-08"
FOSL <- FOSL[rng]
FOSL <- data.frame(Date=as.POSIXct(index(FOSL)), FOSL[,1:4])

FOSL$chg <- ifelse(Cl(FOSL) > Op(FOSL), "up", "dn")
FOSL$width <- as.numeric(periodicity(FOSL)[1])
FOSL$flat_bar <- FOSL[, "High"] == FOSL[, "Low"]

# Candle chart:
pl <- ggplot(FOSL, aes(x=Date))+
  geom_linerange(aes(ymin=Low, ymax=High)) +
  theme_bw() +
  labs(title="FOSL") +
  geom_rect(aes(xmin = Date - width/2 * 0.9, xmax = Date + width/2 * 0.9, ymin = pmin(Open, Close), ymax = pmax(Open, Close), fill = chg)) + guides(fill = FALSE, colour = FALSE) + scale_fill_manual(values = c("dn" = "darkred", "up" = "darkgreen"))

# Handle special case of drawing a flat bar where OHLC = Open:
if (any(FOSL$flat_bar)) pl <- pl + geom_segment(data = FOSL[FOSL$flat_bar,], aes(x = Date - width / 2 * 0.9, y = Close, yend = Close, xend = Date + width / 2 * 0.9))

print(pl)

Answer 2

感谢FXQuantTrader为R中的烛台棒引入一种美观,快速的替代方法!真棒,简洁,易读!这里有一个FXQuantTrader解决方案的改进版本,其中包括:
  - 将其包装成一个功能
  - 支持更低的分辨率(低至1秒条)
  - 将蜡烛的胡须颜色从黑色更改为正确的颜色
  - 为条形添加小水平线,使用Close = =打开
  - 将第3种颜色(蓝色)添加到条形图中,使用关闭==打开
  - 添加"alpha"参数,这样可以使整个烛台图表更加透明,因此当您在顶部绘制一些布林带和/或移动平均线时会不那么分散注意力(更像是背景)
- 对新手来说更多的评论来弄清楚发生了什么:)

她来了:

library(ggplot2)
library(quantmod)
draw_candles <- function(df, title_param, alpha_param = 1){
  df$change <- ifelse(df$Close > df$Open, "up", ifelse(df$Close < df$Open, "down", "flat"))

  # originally the width of the bars was calculated by FXQuantTrader with use of 'periodicity()', which 
  # seems to work ok only with: ‘minute’,‘hourly’, ‘daily’,‘weekly’, ‘monthly’,
  # ‘quarterly’, and ‘yearly’, but can not do 1 sec bars while we want arbitrary bar size support!-)
  # df$width <- as.numeric(periodicity(df)[1])
  # So let us instead find delta (seconds) between 1st and 2nd row and just 
  # use it for all other rows. We check 1st 3 rows to avoid larger "weekend gaps"
  width_candidates <- c(as.numeric(difftime(df$Date[2], df$Date[1]), units = "secs"), 
                        as.numeric(difftime(df$Date[3], df$Date[2]), units = "secs"), 
                        as.numeric(difftime(df$Date[4], df$Date[3]), units = "secs"))

  df$width_s = min(width_candidates)  # one (same) candle width (in seconds) for all the bars

  # define the vector of candle colours either by name or by rgb()
  #candle_colors = c("down" = "red", "up" = "green", "flat" = "blue")
  candle_colors = c("down" = rgb(192,0,0,alpha=255,maxColorValue=255), "up" = rgb(0,192,0,alpha=255,maxColorValue=255), "flat" = rgb(0,0,192,alpha=255,maxColorValue=255))

  # Candle chart:
  g <- ggplot(df, aes(x=Date))+
    geom_linerange(aes(ymin=Low, ymax=High, colour = change), alpha = alpha_param) +  # candle whiskerss (vertical thin lines:)
    theme_bw() +
    labs(title=title_param) +
    geom_rect(aes(xmin = Date - width_s/2 * 0.9, xmax = Date + width_s/2 * 0.9, ymin = pmin(Open, Close), ymax = pmax(Open, Close), fill = change), alpha = alpha_param) +                            # cabdke body
    guides(fill = FALSE, colour = FALSE) +
    scale_color_manual(values = candle_colors) +  # color for line
    scale_fill_manual(values = candle_colors)     # color for candle fill  

    # Handle special cases: flat bar and Open == close:
    if (any(df$change == "flat")) g <- g + geom_segment(data = df[df$change == "flat",], aes(x = Date - width_s / 2 * 0.9, y = Close, yend = Close, xend = Date + width_s / 2 * 0.9, colour = change), alpha = alpha_param)

  #print(g)
  g
}

Answer 3

无法完全理解您的问题，但这似乎效果很好：

http://www.perdomocore.com/2012/using-ggplot-to-make-candlestick-charts-alpha/