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 pd import pandas as pd
# create Pandas Series with default index values # default index ranges is from 0 to len(list) - 1 x = pd.Series([ 'Geeks' , 'for' , 'Geeks' ])
# print the Series print (x)
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Output :
Method #2 : Using Series()
method with 'index'
argument.
# import pandas lib. as pd import pandas as pd
# create Pandas Series with define indexes x = pd.Series([ 10 , 20 , 30 , 40 , 50 ], index = [ 'a' , 'b' , 'c' , 'd' , 'e' ])
# print the Series print (x)
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Output :
Another example:
# import pandas lib. as pd import pandas as pd
ind = [ 10 , 20 , 30 , 40 , 50 , 60 , 70 ]
lst = [ 'Geeks' , 'for' , 'Geeks' , 'is' ,
'portal' , 'for' , 'geeks' ]
# create Pandas Series with define indexes x = pd.Series(lst, index = ind)
# print the Series print (x)
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Output:
Method #3: Using Series()
method with multi-list
# importing pandas import pandas as pd
# multi-list list = [ [ 'Geeks' ], [ 'For' ], [ 'Geeks' ], [ 'is' ],
[ 'a' ], [ 'portal' ], [ 'for' ], [ 'geeks' ] ]
# create Pandas Series df = pd.Series((i[ 0 ] for i in list ))
print (df)
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Output: