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'])
