Passing a list into a function that requires boolean [Python]

Question

Im quite new to python so i apologize if this question is basic. say i have some simple function

 def get_choiceCost(numChances,init_cost,ratio):
    numChances[]
    if np.equal(numChances,1):
        c=init_cost
    elif np.equal(numChances,2):
        c=init_cost+init_cost/ratio
    elif np.equal(numChances,3):
        c=init_cost+init_cost/ratio+init_cost/np.power(ratio,2)
    else:
        c=0
    return c

how do i pass an array for numChances which will have different truth values? For example,

Im hoping to add a column to a dataframe that takes whatever the value of numChances,init_cost and ratio is for that particular row and calculates the cost (i.e. get_choiceCost to those values). I tried

numChances=np.array([0,1,2])
init_cost=np.array([3,4,5])
rat=np.array([2,3])

products = np.array(np.meshgrid(numChances,init_cost,ratio)).T.reshape(-1, 3)
 df = pd.DataFrame(products, columns= ["numChances","init_cost","ratio"]);
 

df["cost"]=df.apply(get_choiceCost(df["numChances"],df["init_cost"],df["rat"]),axis=0)

i get the error

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

Answer 1

def get_choiceCost(row):
    numChances = row.values[0]
    init_cost = row.values[1]
    ratio = row.values[2]
    if np.equal(numChances, 1):
        c=init_cost
    elif np.equal(numChances, 2):
        c=init_cost * 2 / ratio
    elif np.equal(numChances, 3):
        c=init_cost * 2 / ratio + init_cost / np.power(ratio, 2)

df["cost"] = df.apply(get_choiceCost, axis=0) 

I think that should work, its not very elegant though, let me know if you have any issues.