6.25 - Pandas series objects



In [1]:

    
import numpy as np



In [2]:

    
import pandas as pd



In [3]:

    
labels = ['a','b','c']
my_data = [10,20,30] # a list
arr = np.array(my_data) # an array
d = {'a':10,'b':20,'c':30}



In [9]:

    
pd.Series(my_data, labels) # passing pandas a list, defining labels









    Out[9]:





a    10
b    20
c    30
dtype: int64



In [8]:

    
pd.Series(arr) # passing pandas an array, same thing









    Out[8]:





0    10
1    20
2    30
dtype: int64



In [30]:

    
pd.Series(d) # whoa dictionaries are dope









    Out[30]:





a    10
b    20
c    30
dtype: int64



In [31]:

    
pd.Series(data=['a','b','c'])[1]









    Out[31]:





'b'



In [17]:

    
pd.Series(data=[sum,list,len]) # pandas can hold lots of shit









    Out[17]:





0    <built-in function sum>
1              <type 'list'>
2    <built-in function len>
dtype: object



In [20]:

    
ser1 = pd.Series([1,2,3,4],['Williams','Bates','Bowdoin','Colby'])



In [21]:

    
ser2 = pd.Series([1,2,5,4],['Williams','Bates','Middlebury','Colby'])



In [22]:

    
ser1['Williams'] # numba one









    Out[22]:





1



In [29]:

    
ser1 + ser2









    Out[29]:





Bates         4.0
Bowdoin       NaN
Colby         8.0
Middlebury    NaN
Williams      2.0
dtype: float64



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