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Pandas: Create an index labels by using 64-bit integers, floating-point numbers

Pandas Indexing: Exercise-4 with Solution

Write a Pandas program to create an index labels by using 64-bit integers, using floating-point numbers in a given dataframe.

Test Data:

0        s001     V  Alberto Franco     15/05/2002      35  street1   t1
1        s002     V    Gino Mcneill     17/05/2002      32  street2   t2
2        s003    VI     Ryan Parkes     16/02/1999      33  street3   t3
3        s001    VI    Eesha Hinton     25/09/1998      30  street1   t4
4        s002     V    Gino Mcneill     11/05/2002      31  street2   t5
5        s004    VI    David Parkes     15/09/1997      32  street4   t6

Sample Solution:

Python Code :

import pandas as pd
print("Create an Int64Index:")
df_i64 = pd.DataFrame({
    'school_code': ['s001','s002','s003','s001','s002','s004'],
    'class': ['V', 'V', 'VI', 'VI', 'V', 'VI'],
    'name': ['Alberto Franco','Gino Mcneill','Ryan Parkes', 'Eesha Hinton', 'Gino Mcneill', 'David Parkes'],
    'date_Of_Birth': ['15/05/2002','17/05/2002','16/02/1999','25/09/1998','11/05/2002','15/09/1997'],
    'weight': [35, 32, 33, 30, 31, 32],
    'address': ['street1', 'street2', 'street3', 'street1', 'street2', 'street4']},
    index=[1, 2, 3, 4, 5, 6])
print(df_i64)
print("\nView the Index:")
print(df_i64.index)

print("\nFloating-point labels using Float64Index:")
df_f64 = pd.DataFrame({
    'school_code': ['s001','s002','s003','s001','s002','s004'],
    'class': ['V', 'V', 'VI', 'VI', 'V', 'VI'],
    'name': ['Alberto Franco','Gino Mcneill','Ryan Parkes', 'Eesha Hinton', 'Gino Mcneill', 'David Parkes'],
    'date_Of_Birth ': ['15/05/2002','17/05/2002','16/02/1999','25/09/1998','11/05/2002','15/09/1997'],
    'weight': [35, 32, 33, 30, 31, 32],
    'address': ['street1', 'street2', 'street3', 'street1', 'street2', 'street4']},
    index=[.1, .2, .3, .4, .5, .6])
print(df_f64)
print("\nView the Index:")
print(df_f64.index)

Sample Output:

Create an Int64Index:
  school_code class            name date_Of_Birth  weight  address
1        s001     V  Alberto Franco    15/05/2002      35  street1
2        s002     V    Gino Mcneill    17/05/2002      32  street2
3        s003    VI     Ryan Parkes    16/02/1999      33  street3
4        s001    VI    Eesha Hinton    25/09/1998      30  street1
5        s002     V    Gino Mcneill    11/05/2002      31  street2
6        s004    VI    David Parkes    15/09/1997      32  street4

View the Index:
Int64Index([1, 2, 3, 4, 5, 6], dtype='int64')

Floating-point labels using Float64Index:
    school_code class            name date_Of_Birth   weight  address
0.1        s001     V  Alberto Franco     15/05/2002      35  street1
0.2        s002     V    Gino Mcneill     17/05/2002      32  street2
0.3        s003    VI     Ryan Parkes     16/02/1999      33  street3
0.4        s001    VI    Eesha Hinton     25/09/1998      30  street1
0.5        s002     V    Gino Mcneill     11/05/2002      31  street2
0.6        s004    VI    David Parkes     15/09/1997      32  street4

View the Index:
Float64Index([0.1, 0.2, 0.3, 0.4, 0.5, 0.6], dtype='float64')      

Python Code Editor:


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Previous: Write a Pandas program to display the default index and set a column as an Index in a given dataframe and then reset the index.
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Python: Inspect an object in Python

Example:

test_obj = [1, 3, 5, 7]
print( dir(test_obj) )

Output:

['__add__', '__class__', '__contains__', '__delattr__', '__delitem__', '__dir__', '__doc__', '__eq__', '__format__', 
'__ge__', '__getattribute__', '__getitem__', '__gt__', '__hash__', '__iadd__', '__imul__', '__init__',
'__init_subclass__', '__iter__', '__le__', '__len__', '__lt__', '__mul__', '__ne__', '__new__', '__reduce__',
'__reduce_ex__', '__repr__', '__reversed__', '__rmul__', '__setattr__', '__setitem__', '__sizeof__', '__str__',
'__subclasshook__', 'append', 'clear', 'copy', 'count', 'extend', 'index', 'insert', 'pop', 'remove', 'reverse', 'sort']