CODEWITHSUNDEEP
pythonpandasnumpy
Amy
Amy

Reputation: 25

Adding additional calculations to a numpy.where statement

So, I currently have the below code- which calculates a new column based on two others, depending on which one has data present. I would like to add an additional step to the code. Where if the data in a column being used in the calculations (Total-S_%S, Sulphate-S_%S and Sulphate-S(HCL Leachable)_%S) is negative, the program will times the negatives value by -0.5, and then continue with the calculations as described in the code already. I'm not really sure where to start with this. Thanks,

df['Sulphide-S(calc)-C_%S'] = np.where(
    df["Sulphate-S(HCL Leachable)_%S"].isna(),
    df["Total-S_%S"]- df["Sulphate-S_%S"],
    df["Total-S_%S"]- df["Sulphate-S(HCL Leachable)_%S"])

Upvotes: 2

Views: 129

Answers (1)

Stanislav Nosulenko
Stanislav Nosulenko

Reputation: 194

The first option below doesn't really work after the additional input from this answer's comments, but I will keep it here for reference. Please look at the second option for the actually working solution You could create a nested np.where() statement like this:

df['Sulphide-S(calc)-C_%S'] = np.where((df["Total-S_%S"] < 0) & (df["Sulphate-S(HCL Leachable)_%S"] >= 0), 
    np.where(
        df["Sulphate-S(HCL Leachable)_%S"].isna(),
        df["Total-S_%S"]- df["Sulphate-S_%S"],
        df["Total-S_%S"]- df["Sulphate-S(HCL Leachable)_%S"]),
    np.where(
        df["Sulphate-S(HCL Leachable)_%S"].isna(),
        df["Total-S_%S"] * (-0.5) - df["Sulphate-S_%S"] * (-0.5),
        df["Total-S_%S"] * (-0.5) - df["Sulphate-S(HCL Leachable)_%S"] * (-0.5))

Working solution below

Otherwise, you could create 2 columns, each of which would have processed values from the initital ones, like this:

df["Sulphate-S_%S_PROCESSED"] = np.where(df["Sulphate-S_%S"] < 0,
    df["Sulphate-S_%S"] * -0.5,
    df["Sulphate-S_%S"])

and then conduct you computations on these new columns

Upvotes: 4

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