Pandas Series : Answer

Series :- one-dimensional array of indexed data



In [5]:

    
#Create a series 
import pandas as pd
series_1 = pd.Series([1,2,3,4])



In [6]:

    
# Left column is index and Right column is Data
series_1









    Out[6]:





0    1
1    2
2    3
3    4
dtype: int64



In [7]:

    
series_1.index









    Out[7]:





RangeIndex(start=0, stop=4, step=1)



In [8]:

    
series_1.values









    Out[8]:





array([1, 2, 3, 4], dtype=int64)



In [9]:

    
series_1[1]









    Out[9]:





2



In [10]:

    
series_1[1:]









    Out[10]:





1    2
2    3
3    4
dtype: int64



In [11]:

    
series_1[:2]









    Out[11]:





0    1
1    2
dtype: int64



In [12]:

    
# Here Index Assign naming to particulr data 
series_2 = pd.Series([1,2,3,4], index=['a','b','c','d'])



In [13]:

    
series_2









    Out[13]:





a    1
b    2
c    3
d    4
dtype: int64



In [14]:

    
series_2[1]









    Out[14]:





2



In [15]:

    
series_2['b']









    Out[15]:





2



In [17]:

    
#Use Python Dictionary as series Series.
# A dictionary is a structure which maps arbitrary keys to a set of arbitrary values, and a series is a structure which 
# maps typed keys to a set of typed values.
#Create a Python Dictionary
python_dic = {'Nandan':'Big Data','Kundan':'Manager','Chandan':'Businees Man'}
# Assign Dictionary to Series 
people = pd.Series(python_dic)
# Check the Series 
people









    Out[17]:





Chandan    Businees Man
Kundan          Manager
Nandan         Big Data
dtype: object



In [18]:

    
#Check type of data object
type(people)









    Out[18]:





pandas.core.series.Series



In [19]:

    
people['Nandan']









    Out[19]:





'Big Data'



In [21]:

    
people[2]









    Out[21]:





'Big Data'



In [ ]: