I am trying to create hexbins where the x-axis is a date using the hexbin function in the hexbin package in R. When I feed in my data, it seems to convert the dates into a numeric, which gets displayed on the x-axis. I want it force the x-axis to be a date.
#Create Hex Bins
hbin <- hexbin(xData$Date, xData$YAxis, xbins = 80)
#Plot using rBokeh
figure() %>%
ly_hexbin(hbin)
This gives me:
Here's a brute force approach using the underlying grid plotting package. The axes are ugly; maybe someone with better grid skills than I could pretty them up.
# make some data
x = seq.Date(as.Date("2015-01-01"),as.Date("2015-12-31"),by='days')
y = sample(x)
# make the plot and capture the plot
p <- plot(hexbin(x,y),yaxt='n',xaxt='n')
# calculate the ticks
x_ticks_date <-
x_ticks <- axTicks(1, log = FALSE, usr = as.numeric(range(x)),
axp=c(as.numeric(range(x)) ,5))
class(x_ticks_date) <- 'Date'
y_ticks_date <-
y_ticks <- axTicks(1, log = FALSE, usr = as.numeric(range(y)),
axp=c(as.numeric(range(y)) ,5))
class(y_ticks_date) <- 'Date'
# push the ticks to the view port.
pushViewport(p$plot.vp#hexVp.off)
grid.xaxis(at=x_ticks, label = format(y_ticks_date))
grid.yaxis(at=y_ticks, label = format(y_ticks_date))
Related
I have a fv_viz plot currently displaying the labels on hover with the x position, y position and belonging cluster of the data point. I want to display the rowname(index column of the dataframe, the Company).
Currently the labels looklike this:
And this is the code that is generating them.
output$clustering_plot <- renderPlotly({
valuation_total_raised <- unicorn_countries_clustering_cleaned[, c("Valuation...B.", "Total.Raised")]
rownames(valuation_total_raised) <- unicorn_countries_clustering_cleaned$Company
valuation_total_raised <- valuation_total_raised %>% drop_na()
# Perform k-means clustering
kmeans_fancy <- kmeans(valuation_total_raised, max(input$range_clusters) , nstart = 100)
# Add cluster column to the original dataframe
unicorn_countries_clustering_cleaned$cluster <- kmeans_fancy$cluster
# plot the clusters
#fviz_cluster(kmeans_fancy, data = scale(valuation_total_raised), geom = c("point"),ellipse.type = "euclid")
# Create the ggplot2 object
plot <- fviz_cluster(kmeans_fancy, data = scale(valuation_total_raised),
geom = c("point"),
ellipse.type = "convex")
# Convert the ggplot2 object to an interactive plotly object
plotly_plot <- plotly_build(plot)
# Show the interactive plotly object
plotly_plot
})
How can I edit this code so that it displays the Company name of each data point, in which the Company name is the index of each row? (When I add geom = c("point", "text") the Company appears on top of the point. I want it displayed on the label popup that is on the image above)
I am foresting with combination of data sets from fpp2 package and forecasting function from the forecast package. Output from this forecasting is object list with SNAIVE_MODELS_ALL. This object contain data separate for two series, where first is Electricity and second is Cement.
You can see code below :
# CODE
library(fpp2)
library(dplyr)
library(forecast)
library(gridExtra)
library(ggplot2)
#INPUT DATA
mydata_qauselec <- qauselec
mydata_qcement <- window(qcement, start = 1956, end = c(2010, 2))
# Мerging data
mydata <- cbind(mydata_qauselec, mydata_qcement)
colnames(mydata) <- c("Electricity", "Cement")
# Test Extract Name
mydata1 <- data.frame(mydata)
COL_NAMES <- names(mydata1)
rm(mydata_qauselec, mydata_qcement)
# FORCASTING HORIZON
forecast_horizon <- 12
#FORCASTING
BuildForecast <- function(Z, hrz = forecast_horizon) {
timeseries <- msts(Z, start = 1956, seasonal.periods = 4)
forecast <- snaive(timeseries, biasadj = TRUE, h = hrz)
}
frc_list <- lapply(X = mydata1, BuildForecast)
#FINAL FORCASTING
SNAIVE_MODELS_ALL<-lapply(frc_list, forecast)
So my intention here is to put this object SNAIVE_MODELS_ALL into autoplot function in order to get two plots like pic below.
With code below I draw both plots separate, but my main intention is to do this with function autoplot and some function like apply or something similar, which can automatically draw this two chart like pic above.This is only small example in real example I will have maybe 5 or 10 charts.
#PLOT 1
P_PLOT1<-autoplot(SNAIVE_Electricity,main = "Snaive Electricity forecast",xlab = "Year", ylab = "in billion kWh")+
autolayer(SNAIVE_Electricity,series="Data")+
autolayer(SNAIVE_Electricity$fitted,series="Forecasts")
# PLOT 2
P_PLOT2<-autoplot(SNAIVE_Cement,main = "Snaive Cement forecast",xlab = "Year", ylab = "in millions of tonnes")+
autolayer(SNAIVE_Cement,series="Data")+
autolayer(SNAIVE_Cement$fitted,series="Forecasts")
#UNION PLOTS (PLOT 1 AND PLOT 2)
SNAIVE_PLOT_ALL<-grid.arrange(P_PLOT1,P_PLOT2)
So can anybody help me with this code ?
If I understand in a proper way, one of the difficulties with that problem is that each plot should have a specific title and y label. One of the possible solutions is to set the plot titles and y-lables as function arguments:
PlotForecast <- function(df_pl, main_pl, ylab_plt){
autoplot(df_pl,
main = main_pl,
xlab = "Year", ylab = ylab_plt)+
autolayer(df_pl,series="Data")+
autolayer(df_pl$fitted,series="Forecasts")
}
Prepare lists of the plot labels to be used with PlotForecast():
main_lst <- list("Snaive Electricity forecast", "Snaive Cement forecast")
ylab_lst <- list("in billion kWh", "in millions of tonnes")
Construct a list of plot-objects using a base Map() function:
PL_list <- Map(PlotForecast, df_pl = SNAIVE_MODELS_ALL, main_pl = main_lst,
ylab_plt= ylab_lst)
Then all we have to do is to call grid.arrange() with the plot list:
do.call(grid.arrange, PL_list)
Note, please, that main_lst and ylab_lst are created manually for demonstration purposes, but it is not the best way if you work with a lot of charts. Ideally, the labels should be generated automatically using the original SNAIVE_PLOT_ALL list.
I'm trying to produce a dotchart with a secondary axis on top. However once I plot the second dotchart (with a par(new=T)), I can't figure out how not to display the axis ticks over the previous ones in axis side=1. Here's my code with mock data:
y1_i <- c(2,8,2,14,2)
y2_i <- c(15,17,28,22,30)
y1_f <- c(4,9,11,16,7)
y2_f <- c(13,11,16,11,21)
y=c(y1_i,y2_i,y1_f,y2_f)
x <- c("AAEG","AALO","AGAM","ACHR","AALB")
y1=c(y1_i,y1_f)
y2=c(y2_i,y2_f)
dotchart(y1_i,labels=x,xlab="N50 length",xlim = c(0,max(y1)))
par(new=T)
dotchart(y2_i,labels=x,xlim = c(0,max(y2)))
axis(side=3)
Also, if possible, I would like to add a second data set which would be slightly pushed vertically above the first dataset (to not overlap it), but still corresponding to the same y-axis categories.
Thank you for any suggestion :)
Found it, by using dotchart2 from the Hmisc package
library(Hmisc)
y1_i <- c(2,8,2,14,2)
y2_i <- c(15,17,28,22,30)
y1_f <- c(4,9,11,16,7)
y2_f <- c(13,11,16,11,21)
y=c(y1_i,y2_i,y1_f,y2_f)
x <- c("AAEG","AALO","AGAM","ACHR","AALB")
y1=c(y1_i,y1_f)
y2=c(y2_i,y2_f)
y1_i <- c(2,8,2,14,2)
y2_i <- c(15,17,28,22,30)
y1_f <- c(4,9,11,16,7)
y2_f <- c(13,11,16,11,21)
y=c(y1_i,y2_i,y1_f,y2_f)
x <- c("AAEG","AALO","AGAM","ACHR","AALB")
y1=c(y1_i,y1_f)
y2=c(y2_i,y2_f)
dotchart2(y1_i,labels=x,xlab="N50 length",xlim = c(0,max(y1)))
par(new=T)
dotchart2(y2_i,labels=x,xlim = c(0,max(y2)),xlab="Scaffold number",lines=F,xaxis=F)
axis(side=3,xlab="Scaffold number")
I've been trying to write out an R script that will plot the date-temp series for a set of locations that are identified by a Deployment_ID.
Ideally, each page of the output pdf would have the name of the Deployment_ID (check), a graph with proper axes (check) and correct scaling of the x-axis to best show the date-temp series for that specific Deployment_ID (not check).
At the moment, the script makes a pdf that shows each ID over the full range of the dates in the date column (i.e. 1988-2010), instead of just the relevant dates (i.e. just 2005), which squishes the scatterplot down into uselessness.
I'm pretty sure it's something to do with how you define xlim, but I can't figure out how to have R access the date min and the date max for each factor as it draws the plots.
Script I have so far:
#Get CSV to read data from, change the file path and name
data <- read.csv(file.path("C:\Users\Person\Desktop\", "SampleData.csv"))
#Make Date real date - must be in yyyy/mm/dd format from the csv to do so
data$Date <- as.Date(data$Date)
#Call lattice to library, note to install.packages(lattice) if you don't have it
library(lattice)
#Make the plots with lattice, this takes a while.
dataplot <- xyplot(data$Temp~data$Date|factor(data$Deployment_ID),
data=data,
stack = TRUE,
auto.key = list(space = "right"),
layout = c(1,1),
ylim = c(-10,40)
)
#make the pdf
pdf("Dataplots_SampleData.pdf", onefile = TRUE)
#print to the pdf? Not really sure how this works. Takes a while.
print(dataplot)
dev.off()
Use the scales argument. give this a try
dataplot <- xyplot(data$Temp~data$Date|factor(data$Deployment_ID),
data=data,
stack = TRUE,
auto.key = list(space = "right"),
layout = c(1,1),
scales= list( relation ="free")
)
I'm trying to produce voronoi diagrams with R. The plotting of the diagrams itself is working fine, but I have a problem with labelling the different tiles of my plots.
The code I'm using is as follows:
data <- read.csv("data.csv", sep=",")
x <- data$column1
y <- data$column2
voro <- deldir(x,y,rw=c(0,1,0,1))
list <- tile.list(voro)
color <- heat.colors(6)
plot(list,polycol=color,close=TRUE)
plot(voro,number=TRUE,add=TRUE,wlines=c('tess'))
Is it possible to swap the numbers for custom labels before plotting the diagram?
You can use text to add the labels (you already know the coordinates, x and y).
library(deldir)
# Sample data
x <- c(2.3,3.0,7.0,1.0,3.0,8.0)
y <- c(2.3,3.0,2.0,5.0,8.0,9.0)
voro <- deldir(x,y,list(ndx=2,ndy=2),c(0,10,0,10))
# Plot
plot( tile.list(voro), polycol = heat.colors(6), close=TRUE )
plot( voro, add = TRUE, wlines = 'tess' )
text( x, y, labels = LETTERS[1:length(x)], adj = c(0,0) )