import pandas.rpy.common as com
import pandas as pd	
import numpy as np
import rpy2.robjects as robjects
from rpy2.robjects.packages import importr
nlme = importr('nlme')
lme4 = importr('lme4')
base = importr('base')
stats = importr('stats')
xtable = importr('xtable')
stargazer = importr('stargazer')
texreg = importr('texreg')

df = pd.DataFrame.from_csv('http://chymera.eu/data/test/TC_all.csv', parse_dates=False, index_col=[0,1,2])

df.reset_index(inplace=True)
df = df[(df["CoI"] == "easy") | (df["CoI"] == "hard")] # remove uninteresting categorizations

dfr = com.convert_to_r_dataframe(df, True)  # convert from pandas to R and make string columns factors

formula1 = robjects.Formula('Pupil~CoI*Time+(1|ID)')
formula2 = robjects.Formula('Pupil~CoI*measurement+(1|ID)')

test1=lme4.lmer(formula1,data=dfr)
test2=lme4.lmer(formula2,data=dfr)

test1_sum= base.summary(test1)
test2_sum= base.summary(test2)