Accessing Pandas Series Items

Michael Zippo 18.07.2021

In this article we use the file “ nba.csv "to download CSV, click here .

Access to an element from a series with a position

An index number is used to access an element of a series. Use the index operator [] to access an item in a series. The index must be an integer.
To access several elements from the series, we use the Slice operation. The Slice operation is performed on a series using the colon (:). To print items from start to range, use [:Index ] to print items from end use [:-Index ] , to print items from a specific index to the end, use [Index:] to print items within a range use [Start Index: End Index] and to print an entire series using a slicing operation use [:> . Next, to print the entire series in reverse order, use [::-1 ] .

Code # 1: Accessing the first element of the series

# pandas and nudies import

import pandas as pd

import numpy as np

# create a simple array

data = np.array ([ ’g’ , ’ e’ , ’e’ , ’ k’ , ’s’ , ’ f’ , ’o’ , ’r’ , ’ g’ , ’e’ , ’e’ , ’ k’ , ’s’ ])

ser = pd.Series (data)

# get first element

print (ser [ 0 ] )

Output:

Code no. 2: Access the first 5 elements of the series

# import of pandas and nudies

import pandas as pd

import numpy as np

# create a simple array

ser = pd.Series (data)

# get first element

print (ser [: 5 ])

Output:

Code # 3: Access to the last 10 elements of the series

       # pandas and nudies import  
   import   pandas as pd 
   import   numpy as np 
   
  # create a simple array  
   data   =   np.array ([  ’g’  ,  ’ e’  ,   ’e’  ,   ’k’  ,   ’s’  ,  ’ f’  ,   ’o’  ,  ’ r’  ,  ’ g’  ,   ’e’  ,   ’e’  ,   ’k’  ,  ’ s’  ])  
   ser   =   pd.Series (data)  
   
   
  # get the first element  
   print   (ser [  -   10  :])

Output:

Code # 4: Accessing the first 5 Series elements in nba.csv

# pandas module import

import pandas as pd

# create data frame

df = pd.read_csv ( "nba.csv" )

ser = pd.Series (df [ ’Name’ ])

ser.head ( 10 )

We now access the first 5 e series elements

# get the first five names

ser [: 5 ]

Output:

Accessing an element by label (index)

To access an element from a series, we have to set values by the index label. A series is like a fixed-size dictionary where you can get and set values by an index mark.

Code # 1: Accessing a single item using an index mark

Output:

Code # 2: Accessing multiple elements with an index mark

# pandas and nudies import

import pandas as pd

import numpy as np

# create a simple array

data = np.array ([ ’g’ , ’e’ , ’ e’ , ’k’ , ’ s’ , ’f’ , ’o’ , ’ r’ , ’ g’ , ’e’ , ’e’ , ’ k’ , ’s’ ])

ser = pd.Series (data, index = [ 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 ])

# access the element using the index element

print ( ser [ 16 ])

# pandas and nudies import

import pandas as pd

import numpy as np

# create a simple array

data = np.array ([ ’g’ , ’ e’ , ’ e’ , ’k’ , ’s’ , ’f’ , ’ o’ , ’r’ , ’ g’ , ’e’ , ’ e’ , ’k’ , ’ s’ ])

ser = pd.Series (data, index = [ 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 ])

# access multiple items with
# index element

print (ser [[ 10 , 11 , 12 , 13 , 14 ]])

Output:

Code # 3: Access to multiple items by providing an index label

# pandas and numpy imports

import pandas as pd

import numpy as np

ser = pd.Series (np.arange ( 3 , 9 ), index = [ ’a’ , ’ b’ , ’c’ , ’ d’ , ’e’ , ’f’ ])

    
   print   (ser [[  ’a’  ,   ’d’  ,   ’g’  ,  ’ l’  ]])

Output:

Code # 4: Multiple access elements with an index mark in nba.csv

       # pandas module import  
   import   pandas as pd 
   
  # create data frame  
   df   =   pd.read_csv (  "nba.csv"  ) 
   
   ser   =   pd.Series (df [  ’Name’  ]) 
   ser.head (  10  )