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’ )