Python pandas demo



In [15]:

    
%matplotlib inline
import numpy as np
import pandas as pd
import seaborn as sns

df = (pd.read_csv('cars.csv')
        .sort_values(by='hp', ascending = False)
        .assign(fct_cyl=lambda x: pd.Categorical(x['cyl']))
        .reset_index())
print(df.head())









    



   index   mpg  cyl   disp     hp  drat     wt   qsec   vs   am  gear  carb  \
0     26  15.0  8.0  301.0  335.0  3.54  3.570  14.60  0.0  1.0   5.0   8.0   
1     22  15.8  8.0  351.0  264.0  4.22  3.170  14.50  0.0  1.0   5.0   4.0   
2     29  13.3  8.0  350.0  245.0  3.73  3.840  15.41  0.0  0.0   3.0   4.0   
3     28  14.3  8.0  360.0  245.0  3.21  3.570  15.84  0.0  0.0   3.0   4.0   
4     27  14.7  8.0  440.0  230.0  3.23  5.345  17.42  0.0  0.0   3.0   4.0   

   id fct_cyl  
0  27     8.0  
1  23     8.0  
2  30     8.0  
3  29     8.0  
4  28     8.0



In [12]:

    
(df.groupby('cyl')
   .size())









    Out[12]:





cyl
4.0    11
6.0     7
8.0    14
dtype: int64



In [11]:

    
(df.groupby('cyl')
   .hp.agg([np.mean, np.median]))



In [13]:

    
(df.groupby('cyl')
   .qsec.agg([np.mean, np.median]))



In [16]:

    
sns.regplot(data=df, x='hp', y='qsec')









    Out[16]:





<matplotlib.axes._subplots.AxesSubplot at 0x118353c88>



In [17]:

    
sns.pairplot(df, hue='fct_cyl', vars=['hp', 'qsec'])









    Out[17]:





<seaborn.axisgrid.PairGrid at 0x10ac88518>



In [ ]: