如何将数据框的一列的值转换为 0 和 1？

Question

I am working on a negative binomial regression model, which predicts the number of initiated private member bills by MPs in Japan based on their voteshare, age, sex and parliamentary office. In order to calculate the AME for the parliamentary_office variable I need to create two new data frames df.0 and df.1. As an example, here's the data frame df.0:

  (Intercept) voteshare age sexmale term parliamentary_office
1           1     37.92  57    male    0                    0
2           1     45.99  65    male    5                    0
3           1     36.18  59  female    3                    0
4           1      43.3  47    male    1                    0
5           1     45.48  58    male    5                    0
6           1     31.89  44    male    0                    0

How to convert the the sexmale column to numbers?

Here is my code:

#rm(list=ls())
library(foreign)
dat <- read.dta(file = 'activity.dta', convert.factors = FALSE)
dat_clear <- na.omit(dat)
datc_2012 <- dat_clear[dat_clear$election == 2012, ]

library(MASS)
summary(m2.negbin <- glm.nb(num_pmbs_initiated ~
voteshare + age + sex + term
+ parliamentary_office, data = datc_2012,
link = "log"))

df.0 <- data.frame(cbind(1,
m2.negbin[["model"]]$voteshare,
m2.negbin[["model"]]$age,
m2.negbin[["model"]]$sex,
m2.negbin[["model"]]$term,
m2.negbin[["model"]]$parliamentary_office))

colnames(df.0) <- names(coef(m2.negbin))
df.1 <- df.0
df.0[,"parliamentary_office"] <- 0
df.1[,"parliamentary_office"] <- 1 

Answer 1

you can use the ifelse function if you only have only male and female and need to change the column into 0-1 numbers.

df.0$sexmale <- sapply(df.0$sexmale, function (x) ifelse(x == "male", 0, 1))