Creating a Pandas Series - GeeksforGeeks

17 Jan, 2019
Pandas Series is a one-dimensional labelled array capable of holding data of any type (integer, string, float, python objects, etc.). The axis labels are collectively called index.
Labels need not be unique but must be a hashable type. The object supports both integer and label-based indexing and provides a host of methods for performing operations involving the index.
Creating an empty Series :A basic series, which can be created is an Empty Series.
# import pandas as pdimport pandas as pd  # Creating empty seriesser = pd.Series()  print(ser)
Output :
Series([], dtype: float64)

 Creating a series from array:In order to create a series from array, we have to import a numpy module and have to use array() function.
# import pandas as pdimport pandas as pd  # import numpy as npimport numpy as np  # simple arraydata = np.array(['g', 'e', 'e', 'k', 's'])  ser = pd.Series(data)print(ser)
Output :
 Creating a series from array with index :In order to create a series from array with index, we have to provide index with same number of element as it is in array.
# import pandas as pdimport pandas as pd  # import numpy as npimport numpy as np  # simple arraydata = np.array(['g', 'e', 'e', 'k', 's'])  # providing an indexser = pd.Series(data, index =[10, 11, 12, 13, 14])print(ser)
Output :
 Creating a series from Lists:In order to create a series from list, we have to first create a list after that we can create a series from list.
import pandas as pd  # a simple listlist = ['g', 'e', 'e', 'k', 's']   # create series form a listser = pd.Series(list)print(ser)
Output :
Creating a series from Dictionary:In order to create a series from dictionary, we have to first create a dictionary after that we can make a series using dictionary. Dictionary key are used to construct a index.
import pandas as pd   # a simple dictionarydict = {'Geeks' : 10,        'for' : 20,        'geeks' : 30}   # create series from dictionaryser = pd.Series(dict)   print(ser)
Output :
 Creating a series from Scalar value:In order to create a series from scalar value, an index must be provided. The scalar value will be repeated to match the length of index.
import pandas as pd  import numpy as np  # giving a scalar value with indexser = pd.Series(10, index =[0, 1, 2, 3, 4, 5])  print(ser)
Output :
 Creating a series using NumPy functions :In order to create a series using numpy function, we can use different function of numpy like numpy.linspace(), numpy.random.radn().
# import pandas and numpy import pandas as pd import numpy as np     # series with numpy linspace()  ser1 = pd.Series(np.linspace(3, 33, 3)) print(ser1)     # series with numpy linspace() ser2 = pd.Series(np.linspace(1, 100, 10)) print("\n", ser2) 
Output :
Python pandas-series
Python-pandas
Python
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