In [22]:

    

import pandas as pd
import numpy as np
%matplotlib inline


    

In [23]:

    

a = np.arange(10)
d = {'t1':a,'t2':-a}
df = pd.DataFrame(d)


    

In [26]:

    

df.plot()


    

    
Out[26]:





<matplotlib.axes._subplots.AxesSubplot at 0x7fdebbbc1050>






    

In [25]:

    

df


    

    
Out[25]:






  

    

      

      
t1
      
t2
    
  
  

    

      
0
      
 0
      
 0
    
    

      
1
      
 1
      
-1
    
    

      
2
      
 2
      
-2
    
    

      
3
      
 3
      
-3
    
    

      
4
      
 4
      
-4
    
    

      
5
      
 5
      
-5
    
    

      
6
      
 6
      
-6
    
    

      
7
      
 7
      
-7
    
    

      
8
      
 8
      
-8
    
    

      
9
      
 9
      
-9
    
  

In [27]:

    

# find rows in table where:   1 < t1 <5 &  -6 < t2 < -2
a=np.logical_and(df['t1']>1,df['t1']<5)
b=np.logical_and(df['t2']>-6,df['t2']<-2)
criteria_satisfied = np.logical_and(a,b)


    

In [28]:

    

criteria_satisfied


    

    
Out[28]:





0    False
1    False
2    False
3     True
4     True
5    False
6    False
7    False
8    False
9    False
Name: t1, dtype: bool

In [29]:

    

criteria_satisfied.sum()


    

    
Out[29]:





2

In [ ]: