roc.py

import pandas as pd

def rocCalculation(currentCombined, percent):

    try:
        magic_df = pd.DataFrame()
        temp_df = pd.DataFrame()
        temp_df["EBITDA"] = currentCombined.loc["EBITDA",:]
        temp_df["Depreciation & amortization"] = currentCombined.loc["Depreciation & amortization",:]
        temp_df["Total Current Assets"] = currentCombined.loc["Total Current Assets"]
        temp_df["Total Current Liabilities"] = currentCombined.loc["Total Current Liabilities"]
        temp_df["Net property, plant and equipment"] = currentCombined.loc["Net property, plant and equipment"]
        temp_df = temp_df.dropna()

        #ROC
        magic_df["Returns On Capital"] = (temp_df["EBITDA"] - temp_df["Depreciation & amortization"]) / (
                temp_df["Net property, plant and equipment"] + temp_df["Total Current Assets"] - temp_df["Total Current Liabilities"])
        magic_df["ROC Rank"] = magic_df["Returns On Capital"].rank(ascending=False,na_option='bottom')
        magic_df.sort_values(by=["ROC Rank"], inplace = True)
        print('\n',magic_df.loc[:,["ROC Rank", "Returns On Capital"]])

        tickers = magic_df.index.values
        tickers = tickers[:int(len(tickers)*percent)]

        # magic_df.drop(magic_df.index[len(tickers)//2:], inplace=True)

        return list(tickers)

    except:
        print("\nError in ROC calculation...")
        return []