如何从列表中提取模型系数并制作图？

Question

I have a data frame DF with the columns TrainStation,timeofday,Date and NumberOfPassenger .

First you see the code, then the file for the regression and finally the list with the regression

TrainStation<-c("East","North","East","North","North","Central","North",
                "Central","East","North","East","North","Central","North",
                "Central","North","Central","North","Central","North","Central",
                "North","Central","East","North","East","North","Central","North",
                "Central","East","North","East","North","Central","East")

TimeOfday<-c(12,12,8,16,10,6,0,7,1,3,23,15,12,8,16,10,1,3,5,7,9,10,12,11,17,2,4,5,
             13,14,18,19,20,21,22,23)

Date<-sample(seq(as.Date('2019/01/01'), as.Date('2019/02/28'), by="day"), 36)
Date<-as.character(Date)

DF<-cbind(TrainStation,TimeOfday,Date)
DF<-as.data.frame(DF)

#Weekdays
DF$Date<-as.Date(DF$Date)
DF$Date<-weekdays(DF$Date)
#TimeOfday
DF$TimeOfday<-strptime(DF$TimeOfday,format = "%H")
DF$TimeOfday<-hour(DF$TimeOfday)

DF$TrainStation<-as.character(DF$TrainStation)
DF$TimeOfday<-as.factor(DF$TimeOfday)
DF$Date<-as.factor(DF$Date)

And my data for the regression is this:

library(tidyverse)
DF2<-DF%>%
  group_by(TrainStation,Date,TimeOfday)%>%
  summarize(NumberOfPassenger = n_distinct(TrainStation))

then I make a list with my data, followed by a regression (glm)

#List and glm
l_DF2<-split(DF2,DF2$TrainStation)
lapply(l_DF2, function(x) glm(formula = NumberOfPassenger~TimeOfday+Date,family = poisson(link = "log"), data = x))

Question:

Now I would like to look at the coefficients and make some Plots . But how do I get the coefficients from the list?

Plot example for a different model:

mod<-glm(formula = NumberOfPassenger~TrainStation+TimeOfday+Date,family = poisson(link = "log"), data = DF2)

i could show the coefficients of the TimeOfday in a plot with this:

barplot(coef(mod)[grep("TimeOfday",names(coef(mod)))]) 

How can I plot in my case?

Answer 1

What about

res <- lapply(l_DF2,
  function(x) {
    glm(formula = NumberOfPassenger ~ TimeOfday + Date,
        family = poisson(link = "log"), data = x)
  }
)
lapply(res, coef)

To extract the coefficients of a model, you can use stats::coef() . Now you only have to iterate over your list, which you can do using lapply() as you have already done to fit the models.

If you did not have stats::coef() available, you could just extract the coefficients entries from the list using something like

lapply(res, `[[`, "coefficients")
# or slightly more verbose
lapply(res, function(x) x[["coefficients"]])