英文:
How do I make my plot from R look like the one I have on Python?
问题
我试图让我的R中的图表看起来像我在Python中拥有的那个：这是Python和R的数据框。Python：# 为了绘制折线图# 为每一年创建单独的数据框years = All_Flights_Combined_Month['Year'].unique()data_frames_month = [All_Flights_Combined_Month[All_Flights_Combined_Month['Year'] == year] for year in years]# 创建子图fig, ax = plt.subplots(figsize=(10, 8))# 为每一年绘制 Delay_countfor i, year in enumerate(years):color = 'red' if str(year) == '2003' else 'green' if str(year) == '2004' else 'blue'ax.plot(data_frames_month[i]['Month'], data_frames_month[i]['Delay_count'], label=f"{year} Delay Count", color=color)# 为每一年绘制 Total_Countfor i, year in enumerate(years):color = 'orange' if str(year) == '2003' else 'yellow' if str(year) == '2004' else 'purple'ax.plot(data_frames_month[i]['Month'], data_frames_month[i]['Total_Count'], label=f"{year} Total Count", color=color)# 设置标题和标签ax.set_title('Flight Count by Month')ax.set_xlabel('Month')ax.set_ylabel('Number of Flights')# 添加图例ax.legend(title='Year')# 将图表保存为pdf文件plt.savefig('Monthly Flight Comparison Python.pdf', format='pdf')# 显示图表plt.show()R：# 为了绘制折线图month_plot <- ggplot() + geom_line(data= All_Flights_Combined_Month, aes(x =Month, y=Delay_count, group=Year, color=Year)) +geom_line(data=All_Flights_Combined_Month, aes(x =Month, y=Total_count, group=Year, color=Year))+ scale_x_discrete(limits = c("Jan","Feb","Mar","Apr","May","Jun","Jul","Aug","Sep","Oct","Nov","Dec"))+xlab("Months")+ylab("Number of Flights")+ggtitle("Flight Count by Month")# 保存图表为 .pdfggplot2::ggsave("Monthly Flight Comparison R.pdf", plot = last_plot(), width = 8, height = 6)
在R代码中，您可以尝试添加 scale_color_manual 来手动设置颜色，但要确保您没有重复使用相同的颜色值。
英文:
I am trying to make a plot on my R look like the one I have on my Python:
This is the data frame for both Python and R.
All_Flights_Combined_Month
| Year | Month | Delay_count | Total_count |
|---|---|---|---|
| 2003 | Jan | 151238 | 552109 |
| 2003 | Feb | 158369 | 500206 |
| 2003 | Mar | 152156 | 559342 |
| 2003 | Apr | 125699 | 527303 |
| 2003 | May | 136551 | 533782 |
| 2003 | Jun | 163497 | 536496 |
| 2003 | Jul | 183491 | 558568 |
| 2003 | Aug | 178979 | 556984 |
| 2003 | Sep | 113916 | 527714 |
| 2003 | Oct | 131409 | 552370 |
| 2003 | Nov | 157157 | 528171 |
| 2003 | Dec | 206743 | 555495 |
| 2004 | Jan | 198818 | 583987 |
| 2004 | Feb | 183658 | 553876 |
| 2004 | Mar | 183273 | 601412 |
| 2004 | Apr | 170114 | 582970 |
| 2004 | May | 191604 | 594457 |
| 2004 | Jun | 238074 | 588792 |
| 2004 | Jul | 237670 | 614166 |
| 2004 | Aug | 215667 | 623107 |
| 2004 | Sep | 147508 | 585125 |
| 2004 | Oct | 193951 | 610037 |
| 2004 | Nov | 197560 | 584610 |
| 2004 | Dec | 254786 | 606731 |
| 2005 | Jan | 229809 | 594924 |
| 2005 | Feb | 184920 | 545332 |
| 2005 | Mar | 226883 | 617540 |
| 2005 | Apr | 169221 | 594492 |
| 2005 | May | 178327 | 614802 |
| 2005 | Jun | 236724 | 609195 |
| 2005 | Jul | 268988 | 627961 |
| 2005 | Aug | 240410 | 630904 |
| 2005 | Sep | 165541 | 574253 |
| 2005 | Oct | 186778 | 592712 |
| 2005 | Nov | 193399 | 566138 |
| 2005 | Dec | 256861 | 572343 |
And these are the codes for Python:
# To plot the line graph# Create separate data frames for each yearyears = All_Flights_Combined_Month['Year'].unique()data_frames_month = [All_Flights_Combined_Month[All_Flights_Combined_Month['Year'] == year] for year in years]# Create subplotsfig, ax = plt.subplots(figsize=(10, 8))# Plot Delay_count for each yearfor i, year in enumerate(years):color = 'red' if str(year) == '2003' else 'green' if str(year) == '2004' else 'blue'ax.plot(data_frames_month[i]['Month'], data_frames_month[i]['Delay_count'], label=f"{year} Delay Count", color=color)# Plot Total_Count for each yearfor i, year in enumerate(years):color = 'orange' if str(year) == '2003' else 'yellow' if str(year) == '2004' else 'purple'ax.plot(data_frames_month[i]['Month'], data_frames_month[i]['Total_Count'], label=f"{year} Total Count", color=color)# Set title and labelsax.set_title('Flight Count by Month')ax.set_xlabel('Month')ax.set_ylabel('Number of Flights')# Add legendax.legend(title='Year')# Save the plot as a pdf fileplt.savefig('Monthly Flight Comparison Python.pdf', format='pdf')# Show the plotplt.show()
While this is for R:
{r}# To plot the line graphmonth_plot <- ggplot() + geom_line(data= All_Flights_Combined_Month, aes(x =Month, y=Delay_count, group=Year, color=Year)) +geom_line(data=All_Flights_Combined_Month, aes(x =Month, y=Total_count, group=Year, color=Year))+ scale_x_discrete(limits = c("Jan","Feb","Mar","Apr","May","Jun","Jul","Aug","Sep","Oct","Nov","Dec"))+xlab("Months")+ylab("Number of Flights")+ggtitle("Flight Count by Month")# To save the plot as .pdfggplot2::ggsave("Monthly Flight Comparison R.pdf", plot = last_plot(), width = 8, height = 6)
I need the legend and the line colors to match the ones on Python. I hope I have provide sufficient information. Please kindly advice thank you.
I tried adding scale_color_manual to each geom_line but it churned out an error stating that scale_color_manual values has already been used and it will overwrite the previous ones.
答案1
得分: 2
你可以将你的数据转换为长格式，然后使用 paste0 和 gsub 将年份、延误计数和总计数的长格式合并为一个字符串。要获得正确的颜色，你可以使用 scale_color_manual，并使用 breaks 指定正确的顺序，如下所示：
library(ggplot2)library(dplyr)library(tidyr)df %>%pivot_longer(cols = Delay_count:Total_count) %>%mutate(Year2 = paste0(Year, " ", gsub("_", " ", name)),Month = factor(Month, levels = month.abb)) %>%ggplot(aes(x = Month, y = value, color = Year2, group = Year2)) +geom_line() +labs(color = "Year", x = "Month", y = "Number of Flights") +scale_color_manual(values = c("2003 Delay count" = "red","2004 Delay count" = "green","2005 Delay count" = "blue","2003 Total count" = "orange","2004 Total count" = "yellow","2005 Total count" = "purple"),breaks = c("2003 Delay count","2004 Delay count","2005 Delay count","2003 Total count","2004 Total count","2005 Total count"))
创建于2023-02-19，使用 reprex v2.0.2
英文:
You could transform your data to a longer format and combine the Year and longer format of Delay count and Total count to one string using paste0 and gsub. To get the right colors you could use scale_color_manual, with right order using breaks like this:
library(ggplot2)library(dplyr)library(tidyr)df %>%pivot_longer(cols = Delay_count:Total_count) %>%mutate(Year2 = paste0(Year, " ", gsub("_", " ", name)),Month = factor(Month, levels = month.abb)) %>%ggplot(aes(x = Month, y = value, color = Year2, group = Year2)) +geom_line() +labs(color = "Year", x = "Month", y = "Number of Flights") +scale_color_manual(values = c("2003 Delay count" = "red","2004 Delay count" = "green","2005 Delay count" = "blue","2003 Total count" = "orange","2004 Total count" = "yellow","2005 Total count" = "purple"),breaks = c("2003 Delay count","2004 Delay count","2005 Delay count","2003 Total count","2004 Total count","2005 Total count"))
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<sup>Created on 2023-02-19 with reprex v2.0.2</sup>
答案2
得分: 2
这种类型的问题通常涉及到数据重塑。格式应该是长格式，而数据是宽格式。请参考[这篇帖子](https://stackoverflow.com/questions/2185252/reshaping-data-frame-from-wide-to-long-format)来了解如何将数据从宽格式转换为长格式。然后将变量 `Year` 或 `name` 更改为它们之间的交互作用。这是颜色和分组变量。clrs <- c("2003 Delay Count" = "#e44b3b", "2003 Total Count" = "#edbe70","2004 Delay Count" = "#0d720d", "2004 Total Count" = "#f8f867","2005 Delay Count" = "#0000cb", "2005 Total Count" = "#6d0469")All_Flights_Combined_Month %>%pivot_longer(ends_with("count")) %>%mutate(Month = factor(Month, levels = month.abb),Year = interaction(Year, name, sep = " "),Year = sub("_c", " C", Year)) %>%select(-name) %>%ggplot(aes(Month, value, colour = Year, group = Year)) +geom_line(linewidth = 1.25) +scale_color_manual(values = clrs) +theme_minimal()
英文:
This type of problems generally has to do with reshaping the data. The format should be the long format and the data is in wide format. See this post on how to reshape the data from wide to long format.
Then change variable Year or name to the interaction between these two. That's the color and grouping variable.
suppressPackageStartupMessages({library(dplyr)library(tidyr)library(ggplot2)})clrs <- c("2003 Delay Count" = "#e44b3b", "2003 Total Count" = "#edbe70","2004 Delay Count" = "#0d720d", "2004 Total Count" = "#f8f867","2005 Delay Count" = "#0000cb", "2005 Total Count" = "#6d0469")All_Flights_Combined_Month %>%pivot_longer(ends_with("count")) %>%mutate(Month = factor(Month, levels = month.abb),Year = interaction(Year, name, sep = " "),Year = sub("_c", " C", Year)) %>%select(-name) %>%ggplot(aes(Month, value, colour = Year, group = Year)) +geom_line(linewidth = 1.25) +scale_color_manual(values = clrs) +theme_minimal()
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<sup>Created on 2023-02-19 with reprex v2.0.2</sup>
Data
x <- "Year Month Delay_count Total_count2003 Jan 151238 5521092003 Feb 158369 5002062003 Mar 152156 5593422003 Apr 125699 5273032003 May 136551 5337822003 Jun 163497 5364962003 Jul 183491 5585682003 Aug 178979 5569842003 Sep 113916 5277142003 Oct 131409 5523702003 Nov 157157 5281712003 Dec 206743 5554952004 Jan 198818 5839872004 Feb 183658 5538762004 Mar 183273 6014122004 Apr 170114 5829702004 May 191604 5944572004 Jun 238074 5887922004 Jul 237670 6141662004 Aug 215667 6231072004 Sep 147508 5851252004 Oct 193951 6100372004 Nov 197560 5846102004 Dec 254786 6067312005 Jan 229809 5949242005 Feb 184920 5453322005 Mar 226883 6175402005 Apr 169221 5944922005 May 178327 6148022005 Jun 236724 6091952005 Jul 268988 6279612005 Aug 240410 6309042005 Sep 165541 5742532005 Oct 186778 5927122005 Nov 193399 5661382005 Dec 256861 572343"All_Flights_Combined_Month <- read.table(text = x, header = TRUE)
<sup>Created on 2023-02-19 with reprex v2.0.2</sup>
答案3
得分: 2
以下是代码的翻译部分：
library(tidyverse)df %>%pivot_longer(-c(Year, Month)) %>%mutate(Year = paste(Year, name)) %>%ggplot(aes(x = Month, y = value, color = factor(Year))) +geom_line(aes(group = Year)) +scale_x_discrete(limits = c("Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sep", "Oct", "Nov", "Dec")) +scale_color_manual(values = c("purple", "yellow", "gold", "blue", "green", "red")) +xlab("Months") +ylab("Number of Flights") +ggtitle("Flight Count by Month") +theme_classic()
英文:
Something like this:
library(tidyverse)df %>%pivot_longer(-c(Year, Month)) %>%mutate(Year = paste(Year, name)) %>%ggplot(aes(x =Month, y=value, color=factor(Year)))+geom_line(aes(group = Year))+scale_x_discrete(limits = c("Jan","Feb","Mar","Apr","May","Jun","Jul","Aug","Sep","Oct","Nov","Dec"))+scale_color_manual(values = c("purple", "yellow", "gold", "blue", "green", "red"))+xlab("Months")+ylab("Number of Flights")+ggtitle("Flight Count by Month")+theme_classic()
答案4
得分: 1
使用基本的R语言功能。首先，将数据重塑为宽格式，然后使用matplot函数自定义axis和mtext。
dat_w <- reshape(dat, idvar='Month', timevar='Year', direction='w')par(mar=c(5, 6, 4, 2))matplot(dat_w[, -1], type='l', lty=1, col=2:8, axes=FALSE, ylab='', main='Flight Count By Month')axis(side=1, at=1:12, labels=dat_w$Month, cex.axis=0.8)axis(2, axTicks(2), formatC(axTicks(2), format='f', digits=0), las=2, cex.axis=0.8)mtext('Month', side=1, line=2.5, cex=0.8)mtext('Number of Flights', side=2, line=4, cex=0.8)legend('right', c(paste(unique(dat$Year), rep(gsub('_', ' ', names(dat)[3:4]), each=3))),col=2:8, lty=1, title='Year', cex=0.7)box()
请注意，我已经保留了代码部分的原文，只翻译了注释和函数参数的内容。
英文:
Using just base R. First, reshape into wide format, then use matplot and customize axis and mtext a little.
dat_w <- reshape(dat, idvar='Month', timevar='Year', direction='w')par(mar=c(5, 6, 4, 2))matplot(dat_w[, -1], type='l', lty=1, col=2:8, axes=FALSE, ylab='', main='Flight Count By Month')axis(side=1, at=1:12, labels=dat_w$Month, cex.axis=.8)axis(2, axTicks(2), formatC(axTicks(2), format='f', digits=0), las=2, cex.axis=.8)mtext('Month', side=1, line=2.5, cex=.8); mtext('Number of Flights', 2, 4, cex=.8)legend('right', c(paste(unique(dat$Year), rep(gsub('_', ' ', names(dat)[3:4]), each=3))),col=2:8, lty=1, title='Year', cex=.7)box()
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