Assigment 3

Using the heights_weights_genders.csv, analyze the difference between the height weight correlation in women and men.



In [8]:

    
import pandas as pd
%matplotlib inline
import matplotlib.pyplot as plt
import matplotlib
plt.style.use('ggplot')



In [2]:

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



In [3]:

    
df.head(2)



In [13]:

    
fig, ax = plt.subplots(figsize=[10,6])
for category, group in df.groupby('Gender'):
    ax.plot(group['Height'], group['Weight'], marker='o', linestyle='', label=category, markeredgewidth=0,alpha=0.2)
ax.legend()









    Out[13]:





<matplotlib.legend.Legend at 0x109afc550>



In [19]:

    
women = df[df['Gender']=='Female']
men = df[df['Gender']=='Male']



In [21]:

    
women.plot(kind='scatter',x='Height',y='Weight')
women.corr()



In [22]:

    
men.plot(kind='scatter',x='Height',y='Weight')
men.corr()



In [23]:

    
df.corr()

Conclusion

For male, the coefficient of correlation between height and weight is 0.86.
For female, 0.84.
Male's height and weight has a closer corellation than female's.



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