ANOVA in python using pandas dataframe with statsmodels or scipy?

I set up a direct comparison to test them, found that their assumptions can differ slightly , got a hint from a statistician, and here is an example of ANOVA on a pandas dataframe matching R’s results:

import pandas as pd
import statsmodels.api as sm
from statsmodels.formula.api import ols


# R code on R sample dataset

#> anova(with(ChickWeight, lm(weight ~ Time + Diet)))
#Analysis of Variance Table
#
#Response: weight
#           Df  Sum Sq Mean Sq  F value    Pr(>F)
#Time        1 2042344 2042344 1576.460 < 2.2e-16 ***
#Diet        3  129876   43292   33.417 < 2.2e-16 ***
#Residuals 573  742336    1296
#write.csv(file="ChickWeight.csv", x=ChickWeight, row.names=F)

cw = pd.read_csv('ChickWeight.csv')

cw_lm=ols('weight ~ Time + C(Diet)', data=cw).fit() #Specify C for Categorical
print(sm.stats.anova_lm(cw_lm, typ=2))
#                  sum_sq   df            F         PR(>F)
#C(Diet)    129876.056995    3    33.416570   6.473189e-20
#Time      2016357.148493    1  1556.400956  1.803038e-165
#Residual   742336.119560  573          NaN            NaN