Operations on a Series (Indexing / Extracting an Element)

Extracting an Element from a Series 

A. Created from a  Series of  Scalar Value List  -  [100, 200, 300, 400, 100]

Series -

index address        data

0                            100

1                            200

2                            300

3                            400

4                            100

Case Default - extraction with the default index address 

A. (Positional Positive Indexing)

# Accessing Elements through Positional Indexing on a Series created from Scalar Value List

import pandas

scalarvalue=[100,200,300,400,100]

print("The Scalar Value List is       = ", scalarvalue)

S1=pandas.Series(scalarvalue)

# Positional indexing

print("The data at 1st index address  is = ", S1[0])

Ex. 2 --

The Scalar Value List is       =  [100, 200, 300, 400, 100]
The data at '1st' row label thru positional index is =  100

Similarly,

S1[1] --> 200

S1[2] --> 300

.

.

S1[6])  -->        IndexError: index 6 is out of bounds for axis 0 with size 5

B. Positional negative indexing 

import pandas

scalarvalue=[100,200,300,400,100]

print("The Scalar Value List is       = ", scalarvalue)

S1=pandas.Series(scalarvalue)

# Positional indexing

print("The last data is = ", S1[-2])

The Scalar Value List is       =  [100, 200, 300, 400, 100]

KeyError: -2
-2 is not in range

** The elements of a Series created from a Scalar value list can not be extracted through negative positional indexing.

Case 1 - When the row label index has been reindexed with non-numeric  (character /  String) value

A. Labelled Indexing 

import pandas

scalarvalue=[100,200,300,400,100]

print("The Scalar Value List is       = ", scalarvalue)

S1=pandas.Series(scalarvalue, index=['1st', '2nd', '3rd', '4th','5th'])

OR 

S1=pandas.Series(scalarvalue, index=pandas.Index( ['1st', '2nd', '3rd', '4th','5th']) )

# Labelled indexing  (non-numeric)

print("The data at '1st' row label thru labelled index is   = ", S1['1st'])

The Scalar Value List is       =  [100, 200, 300, 400, 100]
The data at '1st' row label thru labelled index is   =  100

Like-wise --

S1['2nd']) -- >  200    Labelled indexing  (non-numeric)

S1['3rd'] -->     300    Labelled indexing  (non-numeric)

**  The elements of a Series created from a Scalar value list is when redefined with non-numeric row label indexing, then it's data can be extracted through the the labelled indexing 

B.  Positional Positive Indexing

# Accessing Elements through  Positional Indexing of a Series created from Scalar Value List where the default index address has been redefined.

import pandas

scalarvalue=[100,200,300,400,100]

print("The Scalar Value List is       = ", scalarvalue)

S1=pandas.Series(scalarvalue, index=['1st', '2nd', '3rd', '4th','5th'])

# Positional positive indexing (default)

print("The data at '1st' row label thru positional index is = ", S1[0])

The Scalar Value List is       =  [100, 200, 300, 400, 100]
The data at '1st' row label thru labelled index is   =  100
The data at '1st' row label thru positional index is =  100

S1[1] -- >         200    Positional indexing (default)

S1[2] -->          300    Positional indexing (default)

**The elements of a Series created from a Scalar value list is when redefined with 
non-numeric row label indexing, then it's data can be extracted both through the 
positional indexing and through the labelled indexing.

Negative Positional indexing

Ex. 1 --

import pandas
scalarvalue=[100,200,300,400,100]
print("The Scalar Value List is       = ", scalarvalue)

S1=pandas.Series(scalarvalue, index=['1st', '2nd', '3rd', '4th','5th'])


# Positional indexing
print("The last data is               = ", S1[-1])


The Scalar Value List is       =  [100, 200, 300, 400, 100]
The last data is               =  100

** The negative positional indexing can be used to extract an element from the Series created with non-numeric index.

Ex.  2 --  Negative Positional indexing 

import pandas
scalarvalue=[100,200,300,400,100]
print("The Scalar Value List is       = ", scalarvalue)

S1=pandas.Series(scalarvalue, index=['1st', '2nd', '3rd', '4th','5th'])


# Positional indexing
print("The last data is               = ", S1[-2])

The Scalar Value List is       =  [100, 200, 300, 400, 100]
The last data is               =  400

Ex. 3 --

S1[-6])        IndexError: index -6 is out of bounds for axis 0 with size 5

Case 2 - When the row label index is redefined with numeric row-labels (index)

Ex. 1 -- 

# Accessing Elements through Indexing on a Series created from Scalar Value List with numeric labelled index (other than positional indexing)

import pandas

scalarvalue=[100,200,300,400,100]

print("The Scalar Value List is       = ", scalarvalue)

S1=pandas.Series(scalarvalue, index=[10, 20, 30, 40, 50])

# Labelled indexing 

print("The data at '1st' row label thru labelled index is   = ", S1[10])

# Positional indexing

print("The data at '1st' row label thru positional index is = ", S1[0])

The Scalar Value List is       =  [100, 200, 300, 400, 100]
The data at '1st' row label thru labelled index is   =  100

KeyError: 0

Negative indexing 

import pandas

scalarvalue=[100,200,300,400,100]

print("The Scalar Value List is       = ", scalarvalue)

S1=pandas.Series(scalarvalue, index=[10, 20, 30, 40, 50])

# Negative Positional indexing

print("The data at '1st' row label thru positional index is = ", S1[-2])


The Scalar Value List is       =  [100, 200, 300, 400, 100]
KeyError: -2

Ex. 2 --

# Accessing Elements Through Indexing on a Series created from Scalar Value List with numeric labelled index (other than positional indexing)

import pandas
scalarvalue=[100,200,300,400,100]
print("The Scalar Value List is       = ", scalarvalue)

S1=pandas.Series(scalarvalue, index=[1,2,3,4,5])
# Labelled indexing 
print("The data at '1st' row label thru labelled index is   = ", S1[5])

# Positional indexing
print("The data at '1st' row label thru positional index is = ", S1[0])

The Scalar Value List is       =  [100, 200, 300, 400, 100]
The data at '1st' row label thru labelled index is   =  100

KeyError: 0


# Positional Negative indexing
print("The data at '1st' row label thru positional index is = ", S1[-1])

KeyError: -1


Summary Table - Series (Scalar Value List) Indexing (Extraction)




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