python 3.x - Error while fitting a linear regression "ValueError: Found arrays with inconsistent numbers of samples" -

i trying execute following code:

import numpy np sklearn import linear_model  class marketingcosts:      def desired_marketing_expenditure(marketing_expenditure, units_sold, desired_units_sold):         model = linear_model.linearregression()         model.fit(units_sold, marketing_expenditure)         output = model.predict(desired_units_sold)         return output   print(marketingcosts.desired_marketing_expenditure(     [300000, 200000, 400000, 300000, 100000],     [60000, 50000, 90000, 80000, 30000],     60000)) 

however, obtain following error when run it:

exec(code, run_globals)    file "marketingcosts.py", in       60000))    file "marketingcosts.py", in desired_marketing_expenditure      model.fit(units_sold, marketing_expenditure)  valueerror: found arrays inconsistent numbers of samples: [1 5] 

does know why happening? tried make model.fit using np.array argument throws similar error.

thanks in advance

this code works. need transpose data:

xtrain = np.array([[300000, 200000, 400000, 300000, 100000],]).t y = np.array([[60000, 50000, 90000, 80000, 30000],]).t xtest = np.array([[60000],]).t  print(marketingcosts.desired_marketing_expenditure(y, xtrain, xtest)) 

i'v misplaced parameters, it's fixed. output 22000, looks good.