Question

关于游泳者瀑布图的时间轴的一个问题。

我使用下面的代码生成了游泳者图>

但是，我想根据数据集中的responseStartTime和responseEndTime持续时间，用responseType（而不是“ Stage”）对每个主题的条进行着色。请建议我如何在响应持续时间内通过responseType定义颜色。

谢谢！

来源：（http://rpubs.com/alexiswl/swimmer）。

数据代码

    library(magrittr)
library(stringi)
library(readr)   # Reading in the dataset
library(ggplot2) # Viewing the dataset
library(forcats) # Sorting factors
library(RColorBrewer) # Plot colours
library(dplyr, warn.conflicts=FALSE)   # Manipulating the dataframes
library(purrr, warn.conflicts=FALSE)   # Manipulating dataframe metadata
library(zoo, warn.conflicts=FALSE)     # Filling in  NA values
library(reshape2) # Reformmating dataframes 

library(editData)
df.data <- df
swimmer_file = "https://blogs.sas.com/content/graphicallyspeaking/files/2014/06/Swimmer_93.txt"
col.names = c("subjectID", "stage", "startTime", "endTime", 
              "isContinued", "responseType", "responseStartTime", "responseEndTime", "Durable")
df <- readr::read_lines(swimmer_file) %>%
  # Split by line recursion (\r\n)
  stringi::stri_split(fixed="\r\n", simplify=TRUE) %>%
  # Take only lines starting with a number (sample id)
  .[grepl("^[0-9]+", .)] %>%
  # Remove spaces from response column
  gsub(pattern="\\sresponse", replacement="_response") %>%
  # Remove spaces from stage column
  gsub(pattern="Stage\\s",  replacement="Stage_") %>%
  # Some lines missing 'Stage' and 'isContinued' column. 
  # Replace any set of 8 or more spaces with ' . '
  gsub(pattern="\\s{8,}", replacement=' . ') %>%
  # Split strings by spaces, do not include empty strings as columns
  stringi::stri_split(fixed=" ", simplify=TRUE, omit_empty=TRUE) %>%
  # Convert to dataframe
  as.data.frame(stringsAsFactors=FALSE) %>%
  # Set the column names
  purrr::set_names(col.names) %>%
  # We need to do some more cleaning up of the dataframe
  # Convert all . to NAs
  dplyr::na_if(".") %>%
  # Fill NAs in Stage column
  dplyr::mutate(stage=zoo::na.locf(stage)) %>%
  # Turn isContinued into boolean
  dplyr::mutate(isContinued=dplyr::if_else(isContinued=="FilledArrow", TRUE, FALSE, missing=FALSE)) %>%
  # Convert stage variable to factor, remove underscore
  dplyr::mutate(stage = as.factor(gsub(pattern="_", replacement=" ", x=stage))) %>%
  # Remove underscore from response types 
  dplyr::mutate(responseType = gsub("_", " ", responseType)) %>%
  # Change Durable from character to numeric
  dplyr::mutate(Durable = as.numeric(Durable)) %>%
  # Change Time variables from character to numeric
  dplyr::mutate_at(vars(dplyr::ends_with("Time")), as.numeric)

df.shapes <- df %>%
  # Get just the subject and response time columns
  dplyr::select(subjectID, responseType, responseStartTime) %>%
  # Melt the data frame, so one row per response value.
  reshape2::melt(id.vars=c("subjectID", "responseType"), value.name="time") %>%
  # Remove na values
  dplyr::filter(!is.na(time)) %>%
  # Remove response variable column
  dplyr::select(-variable) %>%
  # Add 'start' to the end of the response type
  dplyr::mutate(responseType=paste(responseType, "start", sep=" "))

# Add the end time for each 
df.shapes %<>%
  dplyr::bind_rows(df %>%
                     dplyr::select(subjectID, endTime, responseEndTime, isContinued) %>%
                     # Place endtime as response endtime if not continuing and responseEndTime is NA
                     dplyr::mutate(responseEndTime=dplyr::if_else(!isContinued & is.na(responseEndTime),
                                                                  endTime, responseEndTime)) %>%
                     dplyr::select(-endTime, -isContinued) %>%
                     # Remove other existing NA responseEndTimes
                     dplyr::filter(!is.na(responseEndTime)) %>%
                     dplyr::mutate(responseType="Response end") %>%
                     dplyr::rename(time=responseEndTime))

# Append on the durable column
df.shapes %<>% 
  dplyr::bind_rows(df %>% 
                     dplyr::select(subjectID, Durable) %>%
                     dplyr::filter(!is.na(Durable)) %>%
                     dplyr::mutate(responseType="Durable") %>%
                     dplyr::rename(time=Durable))
# Add on the arrow sets
df.shapes %<>% 
  dplyr::bind_rows(df %>%
                     dplyr::select(subjectID, endTime, isContinued) %>%
                     dplyr::filter(isContinued) %>%
                     dplyr::select(-isContinued) %>%
                     dplyr::mutate(responseType="Continued Treatment") %>%
                     dplyr::mutate(endTime=endTime+0.25) %>%
                     dplyr::rename(time=endTime))

responseLevels = c("Complete response start", "Partial response start", 
                   "Response end", "Durable", "Continued Treatment")

# Convert responseType to factor and set the levels
df.shapes %<>% 
  dplyr::mutate(responseType = factor(responseType, levels=responseLevels)) %>%
  # Order by response type
  dplyr::arrange(desc(responseType))

unicode = list(triangle=sprintf('\u25B2'),
               circle=sprintf('\u25CF'),
               square=sprintf('\u25A0'),
               arrow=sprintf('\u2794'))

地块代码：

  df %>% 
  # Get just the variables we need for the base of the plot
  dplyr::select(subjectID, endTime, stage) %>%
  # Remove duplicate rows
  dplyr::distinct() %>%
  # Order subject ID by numeric value
  dplyr::mutate(subjectID=forcats::fct_reorder(.f=subjectID, .x=as.numeric(subjectID), .desc = TRUE)) %>%
  # Pipe into ggplot
  ggplot(aes(subjectID, endTime)) + # Base axis
  geom_bar(stat="identity", aes(fill=factor(stage))) + # Bar plot. Colour by stage
  geom_point(data=df.shapes, # Use df.shapes to add reponse points
             aes(subjectID, time, colour=responseType, shape=responseType), size=5) +
  coord_flip() + # Flip to horizonal bar plot.
  scale_colour_manual(values=c(RColorBrewer::brewer.pal(3, "Set1")[1:2], # Add colours
                               rep("black", 3))) + # min of brewerpal is three but we only need 2.
  scale_shape_manual(values=c(rep(unicode[["triangle"]], 2), # Add shapes
                              unicode[["circle"]], unicode[["square"]], unicode[["arrow"]])) +
  scale_y_continuous(limits=c(-0.5, 20), breaks=0:20) + # Set time limits
  labs(fill="Disease Stage", colour="Symbol Key", shape="Symbol Key",  # Add labels
       x="Subject ID ", y="Months since diagnosis",
       title="Swimmer Plot",
       caption="Durable defined as subject with six months or more of confirmed response") +
  theme(plot.title = element_text(hjust = 0.5), # Put title in the middle of plot
        plot.caption = element_text(size=7, hjust=0)) # Make caption size smaller

Answer 1

很抱歉，您的回答很晚，但是我认为这是一个非常有趣的问题，因此即使您不再需要了，我也可以发布解决方案。我希望我了解你想要的。

基本上，您必须采用其他方法并使用geom_segment(). 如果这样做，解决方案将非常简单。唯一的问题是您没有明确设定目标：例如，如果您拥有responseEndTime值的NA，或者想要保留或不保留自己的信息，该怎么办？显示在您的条形图中，因此我不得不做出任意选择，但是您应该能够弄清楚如何从此解决方案中获得所需的东西：

df %>% 
  # Add a few variables to your df
  dplyr::select(subjectID, stage, responseStartTime, responseEndTime, 
                endTime, responseType) %>%
  # Remove duplicate rows
  dplyr::distinct() %>%
  # Order subject ID by numeric value
  dplyr::mutate(
          subjectID=forcats::fct_reorder(.f=subjectID, 
                                         .x=as.numeric(subjectID),
                                         .desc = TRUE)) %>%
  # Pipe into ggplot
  ggplot(aes(subjectID, endTime)) + # Base axis
  # substitute geom_bar by a geom_segment
  geom_segment(aes(x = 0, xend = endTime, y=subjectID, 
                   yend=subjectID, color = factor(stage)),
               size = 12) +
  # Substitue geom_point with another geom_segment for the responseTime part
  geom_segment(aes(x = responseStartTime, xend = responseEndTime,
                   y=subjectID, yend=subjectID, color = responseType),
               size =8) +
  # don't need coord_flip anymore
  # probably could improve this part but you got the idea
  scale_colour_manual(values=c("#FFFFFF", "#000000",
                               "#F8766D", "#C49A00", "#53B400", 
                               "#00C094")) +
  # the y scale is now the x scale...
  scale_x_continuous(limits=c(-0.5, 20), breaks=0:20) + # Set time limits
  labs(fill="Disease Stage", colour="Symbol Key", 
       shape="Symbol Key",  # Add labels
       y="Subject ID ", x="Months since diagnosis",
       title="Swimmer Plot",
       caption="Durable defined as subject with six months or more of confirmed response") +
  theme(plot.title = element_text(hjust = 0.5),
        plot.caption = element_text(size=7, hjust=0))

游泳者生存图ggplot_Events按持续时间进行颜色编码

数据代码

地块代码：

1 个答案: