Create Conditional column in Pandas data frame

Question

I would like to create a calculated column which is as shown in line 1 but is 0 otherwise

 openOptions['Cash Reserve'] =  (openOptions['Quantity'] * openOptions['Strike'] * 100)
 openOptions['Cash Reserve'] = 0 if (openOptions['OptionType'] == 'C') else openOptions['Cash Reserve']

I get an error:

ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().

How should I resolve this?

SeaBean · Accepted Answer · 2021-04-10 03:23:56Z

1

You can use np.where(), which is like an if-then-else statement for numpy/Pandas, as follows:

openOptions['Cash Reserve'] = np.where(openOptions['OptionType'] == 'C',
                                       0,
                                       openOptions['Cash Reserve'])

Alternatively, as your Cash Reserve column has already been set up and you modify it to 0 only under a condition, you can also use .loc[] :

openOptions.loc[openOptions['OptionType'] == 'C', 'Cash Reserve'] = 0

Or even further simplified, as follows:

openOptions['Cash Reserve'][openOptions['OptionType'] == 'C'] = 0

edited Apr 10, 2021 at 3:23

answered Apr 9, 2021 at 19:16

SeaBean

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