In [8]:

    

import pandas as pd
import statsmodels.formula.api as smf
import matplotlib.pyplot as plt
%matplotlib inline


    

In [6]:

    

df = pd.read_csv('heights_weights_genders.csv')
df.head()


    

    
Out[6]:






  

    

      

      
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
    
  

In [7]:

    

df.plot(kind='scatter', x="Height", y="Weight")


    

    
Out[7]:





<matplotlib.axes._subplots.AxesSubplot at 0x112315390>






    

In [9]:

    

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


    

In [10]:

    

lm.params


    

    
Out[10]:





Intercept   -350.737192
Height         7.717288
dtype: float64

In [26]:

    

height_input = input('Please tell me your height in inches:')
if height_input:
    if height_input <= "0":
        print("Something went wrong with data input. Please try again - add in a value bigger than 0!")
    else:
        output = (7.717288 * int(height_input)) + (-350.737192)
        print("I guess your weight might be approximately", output, "pounds. No offense, if it's incorrect; I'm just a simple algorithm ¯\_(ツ)_/¯")


    

    




Please tell me your height in inches:68
I guess your weight might be approximately 174.038392 pounds. No offense, if it's incorrect; I'm just a simple algorithm ¯\_(ツ)_/¯

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