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 :
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