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Python | Pandas Index.astype ()



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:


# applying astype to index

data.index.astype ( `int64` )