Dataframe 为什么lm为每个自变量生成NA？

我尝试使用lm函数进行线性回归，但每个自变量的输出都是NA。数据帧是数字的

我已经尝试过改变自变量，只使用一个因变量，但结果是一样的

# Read csv file
gh_old_shorty <- read.csv(file.choose(), header=T, sep=";")

# make dataframe numeric
as.data.frame(lapply(gh_old_shorty, as.numeric))

# create linear regression
model1 <- lm(Year ~ Age +  OfficeOfPresidency + MembersOfParliament + 
     Assembly + GovernmentOfficials + LocalGovernmentOfficials + JudgesAndMagistrates + FightingCorruption, data=gh_old_shorty, na.action = na.omit)
summary(model1)

Call:
lm(formula = Year ~ Age + OfficeOfPresidency + MembersOfParliament + 
    Assembly + GovernmentOfficials + LocalGovernmentOfficials + 
    JudgesAndMagistrates + FightingCorruption, data = gh_old_shorty, 
    na.action = na.omit)

Residuals:
ALL 1 residuals are 0: no residual degrees of freedom!

Coefficients: (8 not defined because of singularities)
                         Estimate Std. Error t value
(Intercept)                  2007         NA      NA
Age                            NA         NA      NA
OfficeOfPresidency             NA         NA      NA
MembersOfParliament            NA         NA      NA
Assembly                       NA         NA      NA
GovernmentOfficials            NA         NA      NA
LocalGovernmentOfficials       NA         NA      NA
JudgesAndMagistrates           NA         NA      NA
FightingCorruption             NA         NA      NA
                         Pr(>|t|)
(Intercept)                    NA
Age                            NA
OfficeOfPresidency             NA
MembersOfParliament            NA
Assembly                       NA
GovernmentOfficials            NA
LocalGovernmentOfficials       NA
JudgesAndMagistrates           NA
FightingCorruption             NA

Residual standard error: NaN on 0 degrees of freedom