为什么我的一个R函数抛出一个错误

Question

我试图把这段代码到一个R的功能

separea=quantile(foo6$area,seq(0,1,0.001),na.rm=T) 
nb=length(separea)[1]-1 
resultats=matrix(NA,nb,8) 
for (count in 1:nb){ 
    print(c("area: ",separea[count])) 
    b=foo6[foo6$area >= separea[max(1,count-20)] & foo6$area <= separea[min(count+20,nb+1)],] 
    q01 = quantile(b$nq , 0.01,na.rm=T) 
    q10 = quantile(b$nq , 0.10,na.rm=T) 
    q25 = quantile(b$nq , 0.25,na.rm=T) 
    q50 = quantile(b$nq , 0.50,na.rm=T) 
    q75 = quantile(b$nq , 0.75,na.rm=T) 
    q90 = quantile(b$nq , 0.90,na.rm=T) 
    q99 = quantile(b$nq , 0.99,na.rm=T) 
    if(dim(b)[1]>100){ 
    resultats[count,]=cbind(separea[count],q01,q10,q25,q50,q75,q90,q99) 
    } 
} 
resultats=resultats[!is.na(resultats[,1]),] 
dim1=dim(resultats)[1] 

我写了这个功能：

quantile.prep<-function(dframe,xvar,yvar){ 
    separea=quantile(dframe$xvar,seq(0,1,0.001),na.rm=T) 
    nb=length(separea)[1]-1 
    resultats=matrix(NA,nb,8) 
    for (count in 1:nb){ 
    print(c("area: ",separea[count])) 
    b=dframe[dframe$xvar >= separea[max(1,count-20)] & dframe$area <= separea[min(count+20,nb+1)],] 
    q01 = quantile(b$yvar , 0.01,na.rm=T) 
    q10 = quantile(b$yvar , 0.10,na.rm=T) 
    q25 = quantile(b$yvar , 0.25,na.rm=T) 
    q50 = quantile(b$yvar , 0.50,na.rm=T) 
    q75 = quantile(b$yvar , 0.75,na.rm=T) 
    q90 = quantile(b$yvar , 0.90,na.rm=T) 
    q99 = quantile(b$yvar , 0.99,na.rm=T) 
    if(dim(b)[1]>100){ 
     resultats[count,]=cbind(separea[count],q01,q10,q25,q50,q75,q90,q99) 
    } 
    } 
    resultats=resultats[!is.na(resultats[,1]),] 
    dim1=dim(resultats)[1] 
} 

但我得到这个错误：错误DFRAME $ XVAR：$操作者为原子矢量

无效当我打电话使用quantile.prep（DFRAME ='富6' ，XVAR = '区域'，yvar = 'NQ'）

dput(droplevels(head(foo6))) 

structure(list(area = c(162.6513, 162.6513, 162.6513, 162.6513, 
162.6513, 162.6513), nq = c(0.140843018162167, 0.152855833307204, 
0.193245919337872, 0.156860105022216, 0.171658019333384, 0.18628194179819 
)), .Names = c("area", "nq"), row.names = c(NA, 6L), class = "data.frame") 

能否请你帮忙吗？

提出的输出

工作液

quantile.prep<-function(dframe,xvar,yvar){ 
    separea=quantile(dframe[,xvar],seq(0,1,0.001),na.rm=T) 
    nb=length(separea)[1]-1 
    resultats=matrix(NA,nb,8) 
    for (count in 1:nb){ 
    print(c("area: ",separea[count])) 
    b=dframe[dframe[,xvar]>= separea[max(1,count-20)] & dframe[,'xvar']<= separea[min(count+20,nb+1)],] 
    q01 = quantile(b[,yvar] , 0.01,na.rm=T) 
    q10 = quantile(b[,yvar] , 0.10,na.rm=T) 
    q25 = quantile(b[,yvar] , 0.25,na.rm=T) 
    q50 = quantile(b[,yvar] , 0.50,na.rm=T) 
    q75 = quantile(b[,yvar] , 0.75,na.rm=T) 
    q90 = quantile(b[,yvar] , 0.90,na.rm=T) 
    q99 = quantile(b[,yvar] , 0.99,na.rm=T) 
    if(dim(b)[1]>100){ 
     resultats[count,]=cbind(separea[count],q01,q10,q25,q50,q75,q90,q99) 
    } 
    } 
    resultats=resultats[!is.na(resultats[,1]),] 
    dim1=dim(resultats)[1] 
} 

Answer 1

这是不是你想要做什么？

# An example data set 
area = seq(log10(10), log10(10000), length.out=5000) 
discharge = seq(1,0.08,length.out=5000) + rnorm(5000, 0, 0.2) 
df = data.frame(area=area, nq=discharge) 

# Quick peak at the data 
plot(df) 

# Bin the data into 1,000 bins 
# If I read your code right, you are essentially looking at 
# a window of your data that has 
# a width of of 40/1000*range(data[,"area"]) 
# You are looking at that window at 1,000 evenly spaced points 
# along the x-axis (here saved as xout) 
xout = seq(min(df[,"area"]), max(df[,"area"]), length.out=1000) 
window.size = 40/1000*diff(range(df[,"area"])) 
results = matrix(NA,nrow=length(xout),ncol=8) # allocate matrix that stores quantiles 
for(i in seq_along(xout)) { 

    window = df[,"area"] < (xout[i] + window.size/2) & 
      df[,"area"] > (xout[i] - window.size/2) 
    values = df[window,"nq"] 
    quantiles = quantile(values, probs=c(0.01,0.1,0.25,0.5,0.75,0.9,0.90), na.rm=TRUE) 
    results[i,] = c(xout[i],quantiles) 
} 

# Now plot the results 
library(reshape) 
library(ggplot2) 
colnames(results) = c("area","q01","q10","q25","q50","q75","q90","q99") 
results = as.data.frame(results) 
melted.results = melt(results, id.vars="area") 
ggplot() + 
    geom_point(data=df, aes(x=area,y=nq), alpha=0.15) + 
    geom_line(data=melted.results,aes(x=area,y=value,group=variable,color=variable),size=2)