Pandas Series: add_prefix() function

Prefix labels with string prefix in Pandas series

The add_prefix() function is used to prefix labels with string prefix.

For Series, the row labels are prefixed. For DataFrame, the column labels are prefixed.

Syntax:

Series.add_prefix(self, prefix)

Parameters:

Returns: Series or DataFrame
New Series or DataFrame with updated labels.

Example:

Python-Pandas Code:

import numpy as np
import pandas as pd
s = pd.Series([2, 3, 4, 5])
s

Output:

0    2
1    3
2    4
3    5
dtype: int64

Python-Pandas Code:

import numpy as np
import pandas as pd
s = pd.Series([2, 3, 4, 5])
s.add_prefix('item_')

Output:

item_0    2
item_1    3
item_2    4
item_3    5
dtype: int64

Python-Pandas Code:

import numpy as np
import pandas as pd
df = pd.DataFrame({'X': [2, 3, 4, 5],  'Y': [4, 5, 6, 7]})
df

Output:

  X	Y
0	2	4
1	3	5
2	4	6
3	5	7

Python-Pandas Code:

import numpy as np
import pandas as pd
df = pd.DataFrame({'X': [2, 3, 4, 5],  'Y': [4, 5, 6, 7]})
df.add_prefix('col_')

Output:

  col_X	col_Y
0	 2	    4
1	 3	    5
2	 4	    6
3	 5	    7

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