Series() is a function present in the Pandas library that creates a one-dimensional array and can hold any type of objects or data in it. In this article, let us learn the syntax, create and display one-dimensional array-like object containing an array of data using Pandas library.
pandas.Series()
Syntax : pandas.Series(parameters)
Parameters :
- data : Contains data stored in Series.
- index : Values must be hashable and have the same length as data.
- dtype : Data type for the output Series.
- name : The name to give to the Series.
- copy : Copy input data.
Returns : An object of class Series
Example 1 : Creating Series from a list
# import the library import pandas as pd # create the one-dimensional array data = [1, 2, 3, 4, 5] # create the Series ex1 = pd.Series(data) # displaying the Series print(ex1) |
Output :
Example 2 :Creating a Series from a NumPy array.
# import the pandas and numpy library import pandas as pd import numpy as np # create numpy array data = np.array(['a', 'b', 'c', 'd']) # create one-dimensional data s = pd.Series(data) # display the Series print(s) |
Output :
Example 3: Creating a Series from a dictionary.
# import the pandas library import pandas as pd # create dictionary dict = {'a' : 0.1, 'b' : 0.2, 'c' : 0.3} # create one-dimensional data s = pd.Series(dict) # display the Series print(s) |
Output :
Example 4 :Creating a Series from list of lists.
# importing the module import pandas as pd # creating the data data = [['g', 'e', 'e', 'k', 's'], ['f', 'o', 'r'], ['g', 'e', 'e', 'k', 's']] # creating a Pandas series of lists s = pd.Series(data) # displaying the Series print(s) |
Output :
Attention geek! Strengthen your foundations with the Python Programming Foundation Course and learn the basics.
To begin with, your interview preparations Enhance your Data Structures concepts with the Python DS Course.
