A potential bug in portfolio optimization?

[johnsonice]

in your fundamental_portfolio.ipynb, under "4. Potfolio Optimization using pypfopt", you have this two lines
p1_return_table_pivot=p1_return_table.pivot_table(index = 'datadate',columns = 'tic', values = 'daily_return')
S = risk_models.sample_cov(p1_return_table_pivot)
I think you should use
S = risk_models.sample_cov(p1_return_table_pivot,returns_data=True)

I am reading the documentation, sample_cov assumes the first argument to be price data rather than returns. you will have to specify returns_data=True in this case, since you're using return data directly? (let me know if I got it wrong)
https://pyportfolioopt.readthedocs.io/en/latest/RiskModels.html?highlight=sample_cov#pypfopt.risk_models.sample_cov