在月中获取不均匀分布的 geom_points 的 geom_line 值

发布于 2025-01-14 02:12:43 字数 956 浏览 2 评论 0原文

我需要在每月 15 日从使用下面的可重现示例创建的几何线中获取值。原始几何点的每月日期取决于数据收集日。感谢任何可能的帮助在此处输入图像描述

Value <- c(19.14104, 11.72115, 9.66083, 10.99109, 13.65047, 10.10627, 13.53027, 18.25272, 25.57741)
Dates <- c("07/11/19", "28/11/19", "16/12/19", "10/01/20", "21/01/20", "03/02/20", "04/03/20", "19/03/20", "20/05/20")

df <- data.frame(Value, Dates)
View(df)

df$Dates <- lubridate::dmy(df$Dates)


gpp_plot <- ggplot() + 
  geom_point(data = df, aes(x=Dates, y=Value), alpha=0.5) +
  geom_line(data = df, aes(x=Dates, y=Value), alpha=0.5) +
  theme(axis.text.y=element_text(size=10),
        axis.title=element_text(size=10, , face = "bold"),
        axis.text.x = element_text(size=10, face = "bold", angle = 45, vjust = 0.5))+
  xlab('') +
  ylab('LI-7810_FCH4_DRY_[nmol+1m-2s-1]') +
  scale_x_date(date_labels = "%b %y",breaks = "1 months") +
  theme(legend.position="none")
gpp_plot

原文

I need to obtain value at 15th of every month from the geom line created using the reproducible example below. The original geom points are at varied monthly dates depending on data collection days. Appreciate any help possible enter image description here

Value <- c(19.14104, 11.72115, 9.66083, 10.99109, 13.65047, 10.10627, 13.53027, 18.25272, 25.57741)
Dates <- c("07/11/19", "28/11/19", "16/12/19", "10/01/20", "21/01/20", "03/02/20", "04/03/20", "19/03/20", "20/05/20")

df <- data.frame(Value, Dates)
View(df)

df$Dates <- lubridate::dmy(df$Dates)


gpp_plot <- ggplot() + 
  geom_point(data = df, aes(x=Dates, y=Value), alpha=0.5) +
  geom_line(data = df, aes(x=Dates, y=Value), alpha=0.5) +
  theme(axis.text.y=element_text(size=10),
        axis.title=element_text(size=10, , face = "bold"),
        axis.text.x = element_text(size=10, face = "bold", angle = 45, vjust = 0.5))+
  xlab('') +
  ylab('LI-7810_FCH4_DRY_[nmol+1m-2s-1]') +
  scale_x_date(date_labels = "%b %y",breaks = "1 months") +
  theme(legend.position="none")
gpp_plot

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苹果你个爱泡泡 2025-01-21 02:12:43

正如评论中所建议的，您可以近似新日期的值：

library(ggplot2)
library(lubridate)

Dates <- dmy(Dates)

NewDates <- seq(floor_date(min(Dates),'month'),floor_date(max(Dates),'month'),by='month')+days(14)

#[1] "2019-11-15" "2019-12-15" "2020-01-15" "2020-02-15" "2020-03-15" "2020-04-15" "2020-05-15"

NewValue <- approx(Dates,Value,NewDates)$y

df <- data.frame(Value=c(Value,NewValue), Dates=c(Dates,NewDates))


gpp_plot <- ggplot() + 
  geom_point(data = df, aes(x=Dates, y=Value), alpha=0.5) +
  geom_line(data = df, aes(x=Dates, y=Value), alpha=0.5) +
  theme(axis.text.y=element_text(size=10),
        axis.title=element_text(size=10, , face = "bold"),
        axis.text.x = element_text(size=10, face = "bold", angle = 45, vjust = 0.5))+
  scale_x_date(date_labels = "%b %y",breaks = "1 months") +
  ylab('LI-7810_FCH4_DRY_[nmol+1m-2s-1]') +

  theme(legend.position="none")
gpp_plot

As suggested in comments, you could approx the Value at new dates:

library(ggplot2)
library(lubridate)

Dates <- dmy(Dates)

NewDates <- seq(floor_date(min(Dates),'month'),floor_date(max(Dates),'month'),by='month')+days(14)

#[1] "2019-11-15" "2019-12-15" "2020-01-15" "2020-02-15" "2020-03-15" "2020-04-15" "2020-05-15"

NewValue <- approx(Dates,Value,NewDates)$y

df <- data.frame(Value=c(Value,NewValue), Dates=c(Dates,NewDates))


gpp_plot <- ggplot() + 
  geom_point(data = df, aes(x=Dates, y=Value), alpha=0.5) +
  geom_line(data = df, aes(x=Dates, y=Value), alpha=0.5) +
  theme(axis.text.y=element_text(size=10),
        axis.title=element_text(size=10, , face = "bold"),
        axis.text.x = element_text(size=10, face = "bold", angle = 45, vjust = 0.5))+
  scale_x_date(date_labels = "%b %y",breaks = "1 months") +
  ylab('LI-7810_FCH4_DRY_[nmol+1m-2s-1]') +

  theme(legend.position="none")
gpp_plot