Python | Pandas Index.astype ()

astype | File handling | NumPy | Python functions

Michael Zippo 18.07.2021

Index.astype() Pandas Index.astype() creates an index with values cast to dtypes ... The class of the new index is determined by the dtype. When conversion is not possible, a ValueError is thrown.

Syntax: Index.astype (dtype, copy = True)

Parameters:
dtype: numpy dtype or pandas type
copy: By default, astype always returns a newly allocated object. If copy is set to False and internal requirements on dtype are satisfied, the original data is used to create a new Index or the original Index is returned.

Example # 1: Use Index.astype () to change the data type of an index from floating to integer.

       # import pandas as pd 
   import   pandas as pd 
   
  # Create index  
   df   =   pd.Index ([  17.3  ,   69.221  ,   33.1  ,   15.5  ,   19.3  ,   74.8  ,   10  ,   5.5  ]) 
   
   print   (  "Dtype before applying function:"  , df)  
   
   print   (  "After applying astype function:"  ) 
   # Convert df data type to int64  
   df.astype (  ’int64’  )

Output:

< p> Example # 2: Use Index.astype () to change the data type of this index to string form.

# import pandas as pd

import pandas as pd

# Create index

df = pd.Index ([ 17.3 , 69.221 , 33.1 , 15.5 , 19.3 , 74.8 , 10 , 5.5 ])

print ( "Dtype before applying function:" , df)

print ( "After applying astype function:" )

# Convert datatype df to int64

df.astype ( ’str’ )

Output:

Example # 3: Let’s do something interesting with index.astype () .

Observe this DataFrame.

Setting the Number column as index.

Output:

Now let’s convert the index to an integer h islo.

# pandas module import

import pandas as pd

# read CSV file from URL

data = pd.read_csv ( " https://media.python.engineering/ wp-content / uploads / nba.csv " )

# remove null columns to avoid errors

data.drop na (inplace = True )

# Setting the column number as index

data = data.set_index ( ’Number’ )

# Installation index as None

data.index.names = [ None ]

data. head ( 5 )

Output:

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# applying astype to index

data.index.astype ( ’int64’ )