In [1]:

    

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
plt.style.use('ggplot')
import dateutil.parser
import pg8000
from pandas import DataFrame


    

In [2]:

    

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


    

In [3]:

    

df.head()


    

    
Out[3]:






  

    

      

      
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 [14]:

    

male = df[df['Gender']=='Male']


    

In [15]:

    

male['Height'].median()


    

    
Out[15]:





69.02770850939555

In [16]:

    

male['Weight'].median()


    

    
Out[16]:





187.033546088862

In [17]:

    

male.plot(kind='scatter', x='Height', y='Weight')
plt.xlabel('Heights of Male Population')
plt.ylabel('Weights of Male Population')


    

    
Out[17]:





<matplotlib.text.Text at 0x7dc5910>






    

In [25]:

    

male.boxplot()


    

    




c:\users\radhika\appdata\local\programs\python\python35-32\lib\site-packages\ipykernel\__main__.py:1: FutureWarning: 
The default value for 'return_type' will change to 'axes' in a future release.
 To use the future behavior now, set return_type='axes'.
 To keep the previous behavior and silence this warning, set return_type='dict'.
  if __name__ == '__main__':






    
Out[25]:





{'boxes': [<matplotlib.lines.Line2D at 0x92aae10>,
  <matplotlib.lines.Line2D at 0x92b8c70>],
 'caps': [<matplotlib.lines.Line2D at 0x92b1d70>,
  <matplotlib.lines.Line2D at 0x92b1e10>,
  <matplotlib.lines.Line2D at 0x92bdeb0>,
  <matplotlib.lines.Line2D at 0x92c3410>],
 'fliers': [<matplotlib.lines.Line2D at 0x92b8bd0>,
  <matplotlib.lines.Line2D at 0x92c3d90>],
 'means': [],
 'medians': [<matplotlib.lines.Line2D at 0x92b82f0>,
  <matplotlib.lines.Line2D at 0x92c34b0>],
 'whiskers': [<matplotlib.lines.Line2D at 0x92aaef0>,
  <matplotlib.lines.Line2D at 0x92b18b0>,
  <matplotlib.lines.Line2D at 0x92bd5d0>,
  <matplotlib.lines.Line2D at 0x92bda90>]}






    

In [18]:

    

female = df[df['Gender']=='Female']


    

In [19]:

    

female['Height'].median()


    

    
Out[19]:





63.7309238591475

In [20]:

    

female['Weight'].median()


    

    
Out[20]:





136.11758297008498

In [21]:

    

female.plot(kind='scatter', x='Height', y='Weight')
plt.xlabel('Heights of Male Population')
plt.ylabel('Weights of Male Population')


    

    
Out[21]:





<matplotlib.text.Text at 0x7e05110>






    

In [9]:

    

male.corr(method='pearson', min_periods=1)


    

    
Out[9]:






  

    

      

      
Height
      
Weight
    
  
  

    

      
Height
      
1.000000
      
0.849609
    
    

      
Weight
      
0.849609
      
1.000000
    
  

In [24]:

    

female.boxplot()


    

    




c:\users\radhika\appdata\local\programs\python\python35-32\lib\site-packages\ipykernel\__main__.py:1: FutureWarning: 
The default value for 'return_type' will change to 'axes' in a future release.
 To use the future behavior now, set return_type='axes'.
 To keep the previous behavior and silence this warning, set return_type='dict'.
  if __name__ == '__main__':






    
Out[24]:





{'boxes': [<matplotlib.lines.Line2D at 0x925ccf0>,
  <matplotlib.lines.Line2D at 0x9267b50>],
 'caps': [<matplotlib.lines.Line2D at 0x9262c50>,
  <matplotlib.lines.Line2D at 0x9262cf0>,
  <matplotlib.lines.Line2D at 0x926edb0>,
  <matplotlib.lines.Line2D at 0x926ee50>],
 'fliers': [<matplotlib.lines.Line2D at 0x9267ab0>,
  <matplotlib.lines.Line2D at 0x9272c10>],
 'means': [],
 'medians': [<matplotlib.lines.Line2D at 0x92671d0>,
  <matplotlib.lines.Line2D at 0x9272330>],
 'whiskers': [<matplotlib.lines.Line2D at 0x925cdd0>,
  <matplotlib.lines.Line2D at 0x9262790>,
  <matplotlib.lines.Line2D at 0x9267ff0>,
  <matplotlib.lines.Line2D at 0x926e8f0>]}






    

In [ ]: