Replace values in a Pandas Series using map() and dictionary mapping

Last update on December 21 2024 07:41:40 (UTC/GMT +8 hours)

Pandas: Custom Function Exercise-9 with Solution

Write a Python program that applies map() function to replace values based on a dictionary.

In this exercise, we have used map() function to replace values in a Pandas Series based on a dictionary mapping.

Sample Solution:

Code :

import pandas as pd

# Create a sample Series
s = pd.Series([1, 2, 3, 4, 5])

# Define a dictionary to map values
replace_dict = {1: 'one', 2: 'two', 3: 'three'}

# Apply the dictionary mapping using map()
s_mapped = s.map(replace_dict)

# Output the result
print(s_mapped)

Output:

0      one
1      two
2    three
3      NaN
4      NaN
dtype: object                             

Explanation:

• Created a Pandas Series with 5 values.
• Defined a dictionary replace_dict to map numeric values to string equivalents.
• Applied map() to the Series to replace values based on the dictionary.
• Returned the Series with replaced values where applicable, leaving other values as NaN.

Python-Pandas Code Editor:

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