Python Pandas Series Example

The python pandas series object is similar to the list object, it contains an index ( or tag ) and related values. This article will show you some examples of how to use it in python.

1. How To Create A Pandas Series Object.

1.1 Use pandas.Series(data, index=index) method.

  1. When the data parameter is a multi-dimensional array, the index length must be consistent with the data length.
  2. If the index parameter is not specified, a numerical index will be automatically created (minus 1 from the data parameter’s length)
    import pandas as pd
    
    s1 = pd.Series(['a', 'b', 3])
        
    print(s1)
    =======================================
    Output:
    0    a
    1    b
    2    3
    dtype: object

1.2 Use The Series Class From The Python Pandas Module.

  1. If you import the Series class from the pandas module, you can create Series objects directly in your program.
    from pandas import Series
    
    s2 = Series([7, 8, 9])
        
    print(s2)
    ===================================
    Output:
    0    7
    1    8
    2    9
    dtype: int64

2. Series Index.

  1. Config Series object index manually.
    import pandas as pd
    
    s3 = pd.Series(['80', '90', '100'], index=['c++', 'java', 'python'])
        
    print(s3)
    ==============================================================
    Output:
    c++        80
    java       90
    python    100
    dtype: object
    
  2. Get elements in Series object by location index.
    import pandas as pd
    
    s3 = pd.Series(['80', '90', '100'], index=['c++', 'java', 'python'])
    
    print(s3)
        
    print('s3[0] = ', s3[0])
    ==========================================================================
    Output:
    c++        80
    java       90
    python    100
    dtype: object
    s3[0] =  80
    
  3. Series label index.
    import pandas as pd
    
    s3 = pd.Series(['80', '90', '100'], index=['c++', 'java', 'python'])
        
    print(s3)
        
    print("s3['python'] = ", s3['python'])
    ============================================================================
    Output:
    c++        80
    java       90
    python    100
    dtype: object
    s3['python'] =  100
  4. Series slice index.
    import pandas as pd
    
    s3 = pd.Series(['80', '90', '100'], index=['c++', 'java', 'python'])
       
    print("s3['c++':'java'] = \n", s3['c++':'java'])
    ==============================================================
    Output:
    s3['c++':'java'] = 
     c++     80
    java    90
    dtype: object
  5. Get Series data through index slicing.
    import pandas as pd
      
    s4 = pd.Series(['a','b','c','d','e','f','g'])
        
    print("s4[1:5] =\n", s4[1:5])
    =======================================================
    Output:
    s4[1:5] =
     1    b
    2    c
    3    d
    4    e
    dtype: object
  6. Get Series object index and values.
    import pandas as pd
        
    s5 = pd.Series(['Hello','World','I','Love','Python'])
        
    print('s5.index = ', s5.index)
        
    print('s5.values = ', s5.values)
        
        
    s6 = pd.Series(['Hello','World','I','Love','Python'], index=['a','b','c','d','e'])
        
    print('s6.index = ', s6.index)
        
    print('s6.values = ', s6.values)
    ===========================================================================================
    Output;
    s5.index =  RangeIndex(start=0, stop=5, step=1)
    s5.values =  ['Hello' 'World' 'I' 'Love' 'Python']
    s6.index =  Index(['a', 'b', 'c', 'd', 'e'], dtype='object')
    s6.values =  ['Hello' 'World' 'I' 'Love' 'Python']
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