Book to Market Ratios in pandas
Read the Exam-Ford_Accounting.csv file into a pandas dataframeNow read in the Exam-Ford_Price_Shares.csv file into another pandas dataframeFor each dataframe, make year the index so that we can easily add/subtract/multiple/divide, etc. across the two dataframes and the years will be lined up correctly. Note that you don’t have to convert anything into a datetime.The Book-to-Market ratio is the Book value of equity divided by the market value of equity.In this case, shares are listed in thousands and the accounting data are in millions, so let’s divide shares by 1000 so that they are also in millions.ME (Market value of equity in millions) = price * (shares/1000)Create a market value of equity column in the dataframe with prices and shares.Now calculate the book to market ratio using the book value of equity and the market value of equity. You’ll have to use columns from both dataframes.Show the summary statistics (i.e., mean, standard deviation, min, max, etc.)Set all negative values equal to zeroNow what are the summary statistics?Plot out Ford’s Book-to-Market ratio over time.
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