In [1]:

    

%matplotlib inline  
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt


    

In [23]:

    

df = pd.read_csv('train.csv')
df = df.loc[df['season'].isin([1, 2, 3, 4])]
df.tail()


    

    
Out[23]:






  

    

      

      
datetime
      
season
      
holiday
      
workingday
      
weather
      
temp
      
atemp
      
humidity
      
windspeed
      
casual
      
registered
      
count
    
  
  

    

      
10881
      
2012-12-19 19:00:00
      
4
      
0
      
1
      
1
      
15.58
      
19.695
      
50
      
26.0027
      
7
      
329
      
336
    
    

      
10882
      
2012-12-19 20:00:00
      
4
      
0
      
1
      
1
      
14.76
      
17.425
      
57
      
15.0013
      
10
      
231
      
241
    
    

      
10883
      
2012-12-19 21:00:00
      
4
      
0
      
1
      
1
      
13.94
      
15.910
      
61
      
15.0013
      
4
      
164
      
168
    
    

      
10884
      
2012-12-19 22:00:00
      
4
      
0
      
1
      
1
      
13.94
      
17.425
      
61
      
6.0032
      
12
      
117
      
129
    
    

      
10885
      
2012-12-19 23:00:00
      
4
      
0
      
1
      
1
      
13.12
      
16.665
      
66
      
8.9981
      
4
      
84
      
88
    
  

In [17]:

    

df.shape


    

    
Out[17]:





(10886, 12)

In [18]:

    

df = df.cumsum()
plt.figure(); df.plot();


    

    






<matplotlib.figure.Figure at 0x1328e7908>






    

In [21]:

    

np.unique(df['weather'])


    

    
Out[21]:





array([1, 2, 3, ..., 15439, 15440, 15441], dtype=object)

In [24]:

    

df.plot(kind='scatter', y='count', x='season')


    

    
Out[24]:





<matplotlib.axes._subplots.AxesSubplot at 0x108cb76d8>






    

In [26]:

    

df.plot(kind='scatter', y='count', x='weather')


    

    
Out[26]:





<matplotlib.axes._subplots.AxesSubplot at 0x13328bc88>






    

In [27]:

    

df.plot(kind='scatter', y='count', x='temp')


    

    
Out[27]:





<matplotlib.axes._subplots.AxesSubplot at 0x1332ab4e0>






    

In [ ]: