Create two models for the relationship between height and weight based on gender

Modify the code in Assignment 1 to ask for a person's gender as well as their height to produce an estimate of a person's weight using the models you created Find the weights and use those in your function (i.e. don't generate a model each time)



In [2]:

    
import pandas as pd









    



/usr/local/lib/python3.5/site-packages/matplotlib/__init__.py:1035: UserWarning: Duplicate key in file "/Users/mercybenzaquen/.matplotlib/matplotlibrc", line #2
  (fname, cnt))



In [3]:

    
import statsmodels.formula.api as smf



In [4]:

    
df = pd.read_csv("heights_weights_genders.csv")



In [5]:

    
df.head()

y = ß0 + ß1x

Here:

y: is the variable that we want to predict

ß0: is intercept of the regression line i.e. value of y when x is 0

ß1: is coefficient of x i.e. variation in y with change in value of x

x: Variables that affects value of y i.e. already know variable whose effect we want to se on values of y



In [6]:

    
lm = smf.ols(formula="Weight ~ Height + Gender",data=df).fit()



In [7]:

    
lm.params









    Out[7]:





Intercept        -244.923503
Gender[T.Male]     19.377711
Height              5.976941
dtype: float64



In [ ]:

    
given_height= input("What's your height")



In [8]:

    
given_gender= input('Male or Famale')









    



Male or FamaleMale



In [12]:

    
def weight_calculator(my_height, my_gender): 
    Intercept= -244.923503
    Male= 19.377711 #add to males
    Slope= 5.976941
    if my_gender == 'Male':
        return (Intercept + Male + (Slope * float(my_height)))
    else:
        return (Intercept + (Slope * float(my_height)))



In [13]:

    
weight_calculator(73.847017, 'Male')









    Out[13]:





215.83347163499695



In [14]:

    
weight_calculator(73.847017, 'Female')









    Out[14]:





196.45576063499695



In [ ]:

	Gender	Height	Weight
0	Male	73.847017	241.893563
1	Male	68.781904	162.310473
2	Male	74.110105	212.740856
3	Male	71.730978	220.042470
4	Male	69.881796	206.349801