How can I add additional labels mually to the swimmer plot using pplot2 in r?

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• pivot_wider does not keep all the variables

  I would like to keep the variable cat (category) in the output of my function. However, I am not able to keep it. The idea is to apply a similar function to m <- 1 - (1 - se * p2)^df$n based on the category. But in order to perform that step, I need to keep the variable category.

  Here's the code:

  #script3
  
  suppressPackageStartupMessages({
    library(mc2d)
    library(tidyverse)
  })
  
  sim_one <- function() {
  df<-data.frame(id=c(1:30),cat=c(rep("a",12),rep("b",18)),month=c(1:6,1,6,4,1,5,2,3,2,5,4,6,3:6,4:6,1:5,5),n=rpois(30,5))
    nr <- nrow(df)
    df$n[df$n == "0"] <- 3
    se <- rbeta(nr, 96, 6)
    epi.a <- rpert(nr, min = 1.5, mode = 2, max = 3)
    p <- 0.2
    p2 <- epi.a*p
    m <- 1 - (1 - se * p2)^df$n
    results <- data.frame(month = df$month, m, df$cat)
    results %>%
      arrange(month) %>%
      group_by(month) %>%
      mutate(n = row_number(), .groups = "drop") %>%
      pivot_wider(
      id_cols = n,
      names_from = month,
      names_glue = "m_{.name}",
      values_from =m
      ) 
  }
  
  set.seed(99)
  
  iters <- 1000
  sim_list <- replicate(iters, sim_one(), simplify = FALSE)
  sim_list[[1]]
  #> # A tibble: 7 x 7
  #>       n    m_1    m_2    m_3    m_4   m_5    m_6
  #>   <int>  <dbl>  <dbl>  <dbl>  <dbl> <dbl>  <dbl>
  #> 1     1  0.970  0.623  0.905  0.998 0.929  0.980
  #> 2     2  0.912  0.892  0.736  0.830 0.890  0.862
  #> 3     3  0.795  0.932  0.553  0.958 0.931  0.798
  #> 4     4  0.950  0.892  0.732  0.649 0.777  0.743
  #> 5     5 NA     NA     NA      0.657 0.980  0.945
  #> 6     6 NA     NA     NA      0.976 0.836 NA    
  #> 7     7 NA     NA     NA     NA     0.740 NA
  

  ^{Created on 2022-05-07 by the reprex package (v2.0.1)}
• calculate weighted average over several columns with NA

  I have a data frame like this one:

  ID  duration1   duration2   total_duration  quantity1   quantity2
   1     5            2             7             3         1
   2     NA           4             4             3         4
   3     5            NA            5             2         NA
  

  I would like to do a weighted mean for each subject like this:

  df$weighted_mean<-  ((df$duration1*df$quantity1) + (df$duration2*df$quantity2) ) / (df$total_duration)
  

  But as I have NA, this command does not work and it is not very nice....

  The result would be this:

  ID  duration1   duration2   total_duration  quantity1   quantity2   weighted_mean
   1     5            2             7             3         1          2.43
   2     NA           4             4             3         4          4
   3     5            NA            5             2         NA         2
  

  Thanks in advance for the help
• I am to extract data from netCDF file using R for specific loaction the code i've written as showen and I have an error at the end of the code

  I need some help with extracting date from NetCDF files using R , I downloaded them from cordex (The Coordinated Regional climate Downscaling Experiment). In total I have some files. This files have dimensions of (longitude, latitude, time) and the variable is maximum temperature (tasmax). At specific location, I need to extract data of tasmax at different time. In total I have some files. This files have dimensions of (longitude, latitude, time) and variable maximum temperature (tasmax). At specific location, I need to extract data of tasmax at different time.I wrote the code using R but at the end of code, an error appeared. Error ( location subscript out of bounds)

  getwd() setwd("C:/Users/20120/climate change/rcp4.5/tasmax")

  dir()
  library ("ncdf4")
  libra,-ry(ncdf4.helpers)
  library ("chron")
  ncin <- nc_open("tasmax_AFR-44_ICHEC-EC-EARTH_rcp45_r1i1p1_KNMI-RACMO22T_v1_mon_200601-201012.nc")
  
  lat <- ncvar_get(ncin, "lat")
  
  lon <- ncvar_get(ncin, "lon")
  
  tori <- ncvar_get(ncin, "time")
  title <- ncatt_get(ncin,0,"title")
  institution <- ncatt_get(ncin,0,"institution") 
  datasource <- ncatt_get(ncin,0,"source") 
  references <- ncatt_get(ncin,0,"references")
  history <- ncatt_get(ncin,0,"history") 
  Conventions <- ncatt_get(ncin,0,"Conventions") 
  tustr <- strsplit(tunits$value,"")
  ncin$dim$time$units
  ncin$dim$time$calendar
  tas_time <- nc.get.time.series(ncin, v = "tasmax",
                             time.dim.name = "time")
  tas_time[c(1:3, length(tas_time) - 2:0)]
  tmp.array <- ncvar_get(ncin,"tasmax")
  dunits <- ncatt_get(ncin,"tasmax","units")
  tmp.array <- tmp.array-273.15
  tunits <- ncatt_get(ncin,"time","units")
  nc_close(ncin)
  which.min(abs(lat-28.9))
  which.min(abs(lon-30.2))
  tmp.slice <- tmp.array[126,32981,]
  tmp.slice
  

  Error in tmp.array[126, 32981, ] : subscript out of bounds
• How to delete label above bar chart in R that's already in the legend?

  this is my first post!

  Just wondering how to remove these titles above the charts:

  

  Here's the code for the diagram!

  I imagine I'll have to use something like:
  p + theme(axis.title.x = element_blank(), axis.title.y = element_blank())

  ggplot(data=bike_data_v4)+
        geom_bar(mapping = aes(x=day_of_week,fill=member_casual))+
        scale_x_discrete(limits = c("Sunday","Monday","Tuesday","Wednesday","Thursday","Friday","Saturday"),
                         labels = c("Sun","Mon","Tue","Wed","Thu","Fri","Sat"))+ #the discrete lines show how I rearranges the x-axis labels to go from sun-sat and be renamed to shorter text
        facet_wrap(~member_casual)+
        labs(title="Weekly Rider Differences by Cyclist Type", subtitle="Members vs. Casual Riders",
             x = "Day of the Week",
             y = "Number of Overall Rides",
             caption="Data Provided by Google Capstone Project")+
        scale_y_continuous(limits=c(0,500000), labels = scales::comma)+ #this combined scale_y_continuous(limits=c(0,500000)  AND scale_y_continuous(labels=comma)
        theme_fivethirtyeight()+
        labs(fill='Rider Type')+
        theme(axis.title = element_text())
  
  
    
  
• Scale_x_discrete breaks are not appearing

  I'm creating a rank abundaunce curve for some species data. The y axis is the abundaunce (numeric) and the x axis is the factor "rank" of each species (one with the most abundance gets rank #1, and so forth)

  This data is between rank 1-400, and so I want to set my own x axis limits ( i dont want to see every single label).

  I confirmed that "ab" (which is abundaunce) is numeric and rank.freq (which is the rank) is a factor.

  But, the x-axis scale just never shows up. What am I doing wrong?

  rank.abun<- ggplot(HEMI ,aes(x =reorder(rank.freq, -ab), y = ab))+
   geom_bar(stat = "identity")+
    scale_x_discrete(breaks = c("700", "1000", "2000", "3000", "4000"), labels = c("700", "1000", "2000", "3000", "4000"))+ ## not sure why this isn't working
    labs(x = "Abundance Rank", y = "Abundance"); rank.abun
  

  the data

       X Species freq     ab rank.freq
  330 330    COUM  197 178.39       330
  472 472    PEBR  139 149.50       472
  548 548    KRGR  119 207.04       548
  555 555    PECE  117  59.52       555
  657 657  CAMI12   98  97.53       657
  702 702   PEGR2   92 139.20       702
  

  and the resulting plot
• R: How to remove spikes/outliers on ggplot2

  Given the following R script:

  library(glue)
  library(ggplot2)
  library(tidyverse)
  library(magrittr)
  library(stringi)
  library(dplyr)
  
  ir.data <- read.csv(file="~/apps/mine/cajueiro_weather_station/sensor_data/temperature_data.csv", header = F)
  ir.data$V1 <- as.POSIXct(ir.data$V1, format = "%Y-%m-%dT%H:%M:%S", tz = "UTC")
  
  ir.data %>%
    pivot_longer(-V1, names_to = "Labels", values_to = "V") %>%
    ggplot(aes(x = V1, y = V, colour = Labels)) +
    labs(
      title = "IR-radiation-based sky temperature monitoring.",
      subtitle = glue::glue(
        "Samples from {ir.data$V1[1]}h to {tail(ir.data$V1, n=1)}h UTC-3."
      ),
      caption = "Cajueiro Weather Station - fschuindt.githhub.io/blog/weather"
    ) +
    geom_line(size = 1) +
    scale_color_manual(
      name = "Labels",
      values = c("#1e2975", "#ad1fa2"),
      # limits = c("V2", "V3"),
      labels = c("Ambient temperature.", "Sky temperature."),
    ) +
    xlab("Timestamp") +
    ylab("Measured temperature in °Celcius")
  

  That produces the following plot:

  

  From a dataset that looks like this:

  2022-04-30T19:47:00,28.03,28.05
  2022-04-30T19:47:02,27.99,28.01
  2022-04-30T19:47:04,28.07,28.01
  2022-04-30T19:47:06,28.05,28.05
  2022-04-30T19:47:08,28.05,28.01
  2022-04-30T19:47:10,28.03,28.01
  2022-04-30T19:47:12,28.05,27.99
  2022-04-30T19:47:14,28.07,28.01
  

  How can I remove those temperature spikes that look more like verticals lines from the plot? I'm pretty sure those are sensors misreadings.