I have dataframe
weight height 56 167 88 179 42 159 51 162 90 170 And I try to apply some function
def min_error(w0, w1, height, weight): return np.sum(np.power((height - (w0 + w1*weight))), 2) (data.apply(lambda row: min_error(60, 0.05, row['Height'], row['Weight']), axis=1)) But it returns
ValueError: ('invalid number of arguments', u'occurred at index 1')
How can I fix that?
The problem is your call to np.power. You have the parenthesis in the wrong place. Try:
def min_error(w0, w1, height, weight): return np.sum(np.power((height - (w0 + w1*weight)), 2)) The problem is not with Pandas, but it was identified at a Pandas index, so it appeared to be an error with data.apply, which it isn't.
Your math formula is incorrect. What is happening here is that np.power expects two arguments but is only receiving 1. Check your parenthesis.
I think this is the formula you want:
def min_error(w0, w1, height, weight): return np.sum(np.power((height - (w0 + w1*weight)),2)) (data.apply(lambda row: min_error(60, 0.05, row['height'], row['weight']), axis=1)) Output:
0 10857.6400 1 13133.1600 2 9389.6100 3 9890.3025 4 11130.2500 dtype: float64 maybe this will help you too.
df['min_error']=min_error(60, 0.05, df['height'], df['weight']) 