A Series is a one-dimensional labeled array capable of holding any data type (integers, strings, floating point numbers, Python objects, etc.). It has to be remembered that unlike Python lists, a Series will always contain data of the same type.
Let’s see how to create a Pandas Series from lists.
Method #1 : Using Series() method without any argument.
# import pandas as pdimport pandas as pd # create Pandas Series with default index values# default index ranges is from 0 to len(list) - 1x = pd.Series(['Geeks', 'for', 'Geeks']) # print the Seriesprint(x) |
Output :
Method #2 : Using Series() method with 'index' argument.
# import pandas lib. as pdimport pandas as pd # create Pandas Series with define indexesx = pd.Series([10, 20, 30, 40, 50], index =['a', 'b', 'c', 'd', 'e']) # print the Seriesprint(x) |
Output :
Another example:
# import pandas lib. as pdimport pandas as pd ind = [10, 20, 30, 40, 50, 60, 70] lst = ['Geeks', 'for', 'Geeks', 'is', 'portal', 'for', 'Lazyroar'] # create Pandas Series with define indexesx = pd.Series(lst, index = ind) # print the Seriesprint(x) |
Output:
Method #3: Using Series() method with multi-list
# importing pandas import pandas as pd # multi-listlist = [ ['Geeks'], ['For'], ['Geeks'], ['is'], ['a'], ['portal'], ['for'], ['Lazyroar'] ] # create Pandas Seriesdf = pd.Series((i[0] for i in list)) print(df) |
Output:
