Python | Pandas Index.to_series ()

Index.to_series() Pandas Index.to_series() creates a Series with index and values ​​equal to index keys, which are used with map to return an index-based indexer. You can set a new index mark for a newly created series by passing in a list of new index marks.

Syntax: Index.to_series (index = None, name = None)

Parameters:
index: index of the resulting Series. If None, defaults to original index
name: name of the resulting Series. If None, defaults to name of original index

Returns: Series: dtype will be based on the type of the Index values.

Example # 1: Use Index.to_series () to convert an index to a Series.

# import pandas as pd import pandas as pd   # Create index idx = pd.Index ([ ’Harry’ , ’Mike’ , ’ Arther’ , ’Nick’ ],   name = ’ Student’ )   # Print index print (idx)

Output:

Let’s convert the index to a series.

# convert index to series idx.to_series ()

Output:

The function converted the index to a series. By default, the function creates a series index using the values ​​of the original index.

Example # 2: Use Index.to_series () to convert the index to a series so that so that the created row uses the new index value.

# import pandas as pd import pandas as pd   # Create Index idx = pd.Index ([ ’Alice’ , ’ Bob’ , ’Rachel’ , ’Tyler’ , ’ Louis’ ], name = ’ Winners’ )   # Print index print (idx)

Output:

Let’s convert the index to a series.

# convert index to series idx.to_series (index = [ ’Student 1’ , ’Student 2’ , ’Student 3’ ,   ’Student 4’ , ’ Student 5’ ])

Output:

The function converted the index to a series. We have passed in a list of index marks to be used for the newly created series.