英文:
Issue with plotting two time series in one graph
问题
我有一个绘制两个时间序列在一个图中的问题。我已经从Yahoo! Finance下载了两个时间序列。数据没问题。我可以分别绘制它们，但是当我想要将它们绘制在一起以比较它们的动态时，R没有创建我需要的图。我使用了https://rpubs.com/odenipinedo/visualizing-time-series-data-in-R 中的脚本，但没有帮助。然而，该网站上显示的图形就是我需要的，也是R应该完成的工作。
我个人认为问题出在索引上，即日期的位置。由于图形需要x和y，其中y是时间序列数据，x应该是日期（例如2022-02-20），但R没有匹配图形。
lapply(c("quantmod", "dplyr", "tidyr", "timeSeries", "ggplot2"), require, character.only = TRUE)tickers <- c("TSN", "^GSPC")start_date <- "2022-02-20"portfolioPrices <- NULLfor (Ticker in tickers)portfolioPrices <- cbind(portfolioPrices,getSymbols(Ticker, from = start_date, src = "yahoo", auto.assign=FALSE)[,4])portfolioPrices <- portfolioPrices[apply(portfolioPrices,1,function(x) all(!is.na(x))),]colnames(portfolioPrices) <- tickersportfolioReturns <- ROC(portfolioPrices, type = "discrete")portfolioReturns <- as.timeSeries(portfolioPrices)plot(portfolioReturns$TSN)lines(portfolioReturns$`^GSPC`, col = "red")axis(side = 4, at = pretty(portfolioReturns$`^GSPC`)
我已经查看了几个网站和YouTube视频，但没有帮助。我尝试了ggplot和ggseas包，但它们也没有帮助。结果应该类似于这个截图：图片描述
英文:
I have an issue with plotting two time series in one graph. I have downloaded two time series from Yahoo! Finance. Data is OK. I can plot them separately well, but when I want to plot them together to compare their dynamics, R did not create plot I needed. I used scripts from https://rpubs.com/odenipinedo/visualizing-time-series-data-in-R but it did not help. However, the plot that is shown on this website is what I need and what should be done by R.
I personally think the problem is with index, where the dates are located. As graph needs x and y, where y are time series data, x should be dates (e.g. 2022-02-20), but R did not match graphs.
lapply(c("quantmod", "dplyr", "tidyr", "timeSeries", "ggplot2"), require, character.only = TRUE)tickers <- c("TSN", "^GSPC")start_date <- "2022-02-20"portfolioPrices <- NULLfor (Ticker in tickers)portfolioPrices <- cbind(portfolioPrices,getSymbols(Ticker, from = start_date, src = "yahoo", auto.assign=FALSE)[,4])portfolioPrices <- portfolioPrices[apply(portfolioPrices,1,function(x) all(!is.na(x))),]colnames(portfolioPrices) <- tickersportfolioReturns <- ROC(portfolioPrices, type = "discrete")portfolioReturns <-as.timeSeries(portfolioPrices)plot(portfolioReturns$TSN)lines(portfolioReturns$`^GSPC`, col = "red")axis(side = 4, at = pretty(portfolioReturns$`^GSPC`)
enter image description here))
I have checked several websites and youtube videos, but nothing helped. I tried ggplot and ggseas packages, but they did not help either. The result should be similar to this screenshot:enter image description here
答案1
得分: 1
以下是代码部分的翻译：
- 返回图表只是一个调用
autoplot的操作，再加上一些元素的重新排列、颜色、标题和背景面板; - 价格图是一个双Y轴图。右边的Y轴的刻度是根据数据计算的一个因子来缩放。
suppressPackageStartupMessages({library(quantmod)library(dplyr)library(ggplot2)})tickers <- c("TSN", "^GSPC")start_date <- "2022-02-20"portfolioPrices <- NULLfor (Ticker in tickers) {portfolioPrices <- cbind(portfolioPrices,getSymbols(Ticker, from = start_date, src = "yahoo", auto.assign=FALSE)[,4])}head(portfolioPrices)#> TSN.Close GSPC.Close#> 2022-02-22 92.44 4304.76#> 2022-02-23 91.99 4225.50#> 2022-02-24 90.33 4288.70#> 2022-02-25 93.37 4384.65#> 2022-02-28 92.66 4373.94#> 2022-03-01 93.83 4306.26portfolioPrices <- portfolioPrices[apply(portfolioPrices,1,function(x) all(!is.na(x))),]colnames(portfolioPrices) <- c("TSN", "GSPC")portfolioReturns <- ROC(portfolioPrices, type = "discrete")autoplot(portfolioReturns, facets = NULL) +scale_color_manual(values = c(TSN = "black", GSPC = "red")) +ggtitle("Stock Returns") +theme_bw()#> Warning: Removed 2 rows containing missing values (`geom_line()`).
Prices <- fortify(portfolioPrices)(fac <- with(Prices, range(TSN)/range(GSPC)))#> [1] 0.01676810 0.02124536fac <- max(fac)ggplot(data = Prices, aes(Index, TSN)) +geom_line(aes(color = "TSN")) +geom_line(aes(y = GSPC * fac, color = "GSPC")) +scale_x_date(date_breaks = "1 year", date_labels = "%b %Y") +scale_color_manual(values = c(TSN = "red", GSPC = "black")) +scale_y_continuous(sec.axis = sec_axis(~ . / fac, name = "GSPC Close Prices")) +labs(x = "Date", y = "TSN Close Price", color = "") +ggtitle("Stock Price") +theme_bw()
创建于2023-02-23，使用 reprex v2.0.2
英文:
Here are two plots.
- The returns plot is simply a call to
autoplotplus rearrange some elements, color, title, background panel; - the prices plot is a two y axis plot. The right hand y axis is scaled by a factor computed from the data.
suppressPackageStartupMessages({library(quantmod)library(dplyr)library(ggplot2)})tickers <- c("TSN", "^GSPC")start_date <- "2022-02-20"portfolioPrices <- NULLfor (Ticker in tickers) {portfolioPrices <- cbind(portfolioPrices,getSymbols(Ticker, from = start_date, src = "yahoo", auto.assign=FALSE)[,4])}head(portfolioPrices)#> TSN.Close GSPC.Close#> 2022-02-22 92.44 4304.76#> 2022-02-23 91.99 4225.50#> 2022-02-24 90.33 4288.70#> 2022-02-25 93.37 4384.65#> 2022-02-28 92.66 4373.94#> 2022-03-01 93.83 4306.26portfolioPrices <- portfolioPrices[apply(portfolioPrices,1,function(x) all(!is.na(x))),]colnames(portfolioPrices) <- c("TSN", "GSPC")portfolioReturns <- ROC(portfolioPrices, type = "discrete")autoplot(portfolioReturns, facets = NULL) +scale_color_manual(values = c(TSN = "black", GSPC = "red")) +ggtitle("Stock Returns") +theme_bw()#> Warning: Removed 2 rows containing missing values (`geom_line()`).
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Prices <- fortify(portfolioPrices)(fac <- with(Prices, range(TSN)/range(GSPC)))#> [1] 0.01676810 0.02124536fac <- max(fac)ggplot(data = Prices, aes(Index, TSN)) +geom_line(aes(color = "TSN")) +geom_line(aes(y = GSPC * fac, color = "GSPC")) +scale_x_date(date_breaks = "1 year", date_labels = "%b %Y") +scale_color_manual(values = c(TSN = "red", GSPC = "black")) +scale_y_continuous(sec.axis = sec_axis(~ . / fac, name = "GSPC Close Prices")) +labs(x = "Date", y = "TSN Close Price", color = "") +ggtitle("Stock Price") +theme_bw()
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<sup>Created on 2023-02-23 with reprex v2.0.2</sup>
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