Pandas Data Structure

 DATA STRUCTURES IN PANDAS:

    One of the most important things in Pandas is Data Structure.

    Pandas have three data structures:

• Series
• DataFrame
• Panel

SERIES:

• Series is a one-dimensional array.
• It holds any type of data. 

WAYS TO CREATE A SERIES:

• Series using list
• Series using array
• Series using dictionary

SERIES USING LIST:

    Creating a series with the list values.

    Example: 

  

import pandas as pd 

list_data = ['pandas', 'numpy', 'pytest', 'pywin32']

result = pd.Series(list_data)

print(result)

      

SERIES USING ARRAY:

    Creating a series with the array values.

    Example: 

  

import pandas as pd 
import numpy as np

array_data =  np.array(['pandas', 'numpy', 'pytest', 'pywin32'])

result = pd.Series(array_data)

print(result)

      

SERIES USING DICTIONARY:

    Creating a series with the dictionary data.

    Example: 

  

import pandas as pd 

dict_data = { 'Name': 'Vetri', 'age': 20}

result = pd.Series(dict_data)

print(result)

      

CREATE LABELS:

    Change the index values with the labels specified.

    Example: 

  

import pandas as pd 

list_data = ['pandas', 'numpy', 'pytest', 'pywin32']

result = pd.Series(list_data, index=['a', 'b', 'c', 'd'])

print(result)

      

     Able to access the particular values based on the label.

print(result["a"])

      

    If the length of the index doesn't match the length of the value, then it throws the error.

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