Deleted:Is there a python package that can replicate this model?

Question

[Mike]

Hi all, I hope this question belongs here since I'm analyzing biological data, if not I'll remove it.

I'm trying to convert a short R data analysis script to python and can't find the right modules/packages to do so. This is the script in R:

for(var in vars){
  model<-lm(eval(parse(text=dep))~treatment,data = param)
  org.lsm<-lsmeans(model,"treatment")
  org.lsm <- confint(org.lsm, side = “=”, level = 0.95, type = "lsmean")  
  final = data.frame()
  treatments = unique(param$treatment)
  for (treat in treatments){
    results<-list()
    ind = paste0(treat)
    results[[ind]]$A <-  var
    results[[ind]]$B <-  param
    results[[ind]]$C <- treat
    results[[ind]]$N <- dim(param[param$treatment == treat,])[1]
    results[[ind]]$LS <- org.lsm$lsmean[org.lsm$treatment==treat]
    results[[ind]]$SE <- org.lsm$SE[org.lsm$Treatment==treat]
    results[[ind]]$df <- org.lsm$df[org.lsm$Treatment==treat]
    t=org.lsm$lsmean[org.lsm$treatment==treat]-0
    t=t/org.lsm$SE[org.lsm$treatment==treat]
    results[[ind]]$PVAL=round(2*pt(-abs(t),df=org.lsm$df[org.lsm$treatment==treat]),5)
    if (is.na(results[[ind]]$PVAL)){stop("Message")}
    results<-do.call("rbind.data.frame",results)
    final <- rbind(final,results)
  }
  }

Basically I'm trying to understand just how to make the initial model in python- not rewrite the whole script. I found statsmodels but can't seem to configure it so much as in the R script. (the lsmeans, confint, SE and more)

Any help with this will be highly appreciated!