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Python | Pandas Index.all()
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Python | Pandas Index.copy()

Last Updated : 12 Jan, 2022
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Python is a great language for doing data analysis, primarily because of the fantastic ecosystem of data-centric python packages. Pandas is one of those packages and makes importing and analyzing data much easier. Pandas Index.copy() function make a copy of this object. The function also sets the name and dtype attribute of the new object as that of original object. If we wish to have a different datatype for the new object then we can do that by setting the dtype attribute of the function.
Syntax: Index.copy(name=None, deep=False, dtype=None, **kwargs) Parameters : name : string, optional deep : boolean, default False dtype : numpy dtype or pandas type Returns : copy : Index
Note : In most cases, there should be no functional difference from using deep, but if deep is passed it will attempt to deepcopy. Example #1: Use Index.copy() function to copy the Index value to a new object and change the datatype of new object to ‘int64’

Python3

# importing pandas as pd
import pandas as pd
  
# Creating the Index
idx = pd.Index([17.3, 69.221, 33.1, 15.5, 19.3, 74.8, 10, 5.5])
  
# Print the Index
idx
                      
                       
Output : Let’s create a copy of the object having ‘int64’ data type.

Python3

# Change the data type of newly 
# created object to 'int64'
idx.copy(dtype ='int64')
                      
                       
Output : As we can see in the output, the function has returned a copy of the original Index with ‘int64’ dtype.   Example #2: Use Index.copy() function to make a copy of the original object. Also set the name attribute of the new object and convert the string dtype into ‘datetime’ type.

Python3

# importing pandas as pd
import pandas as pd
  
# Creating the Index
idx = pd.Index(['2015-10-31', '2015-12-02', '2016-01-03', 
                             '2016-02-08', '2017-05-05'])
  
# Print the Index
idx
                      
                       
Output : Let’s make a copy of the original object.

Python3

# to make copy and set data type in the datetime format.
idx_copy = idx.copy(dtype ='datetime64')
  
# Print the newly created object
idx_copy
                      
                       
Output : As we can see in the output, the new object has the data in datetime format and its name attribute has also been set.


Next Article
Python | Pandas Index.all()

S

Shubham__Ranjan
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Article Tags :
  • Python
  • Python pandas-indexing
  • Python-pandas
Practice Tags :
  • python

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