How to convert a Pandas series to a NumPy array and print it?

Last update on April 29 2025 12:54:31 (UTC/GMT +8 hours)

11. Series to Array Conversion

Write a NumPy program to convert a Pandas Series to a NumPy array and print the array.

Sample Solution:

Python Code:

import pandas as pd
import numpy as np

# Create a Pandas Series
series = pd.Series([10, 20, 30, 40, 50])
print("Original Pandas Series:",series)
print("Type:",type(series))
# Convert the Pandas Series to a NumPy array
array = series.to_numpy()
print("\nPandas Series to a NumPy array:")
# Print the NumPy array
print(array)
print("Type:",type(array))

Output:

Original Pandas Series: 0    10
1    20
2    30
3    40
4    50
dtype: int64
Type: <class 'pandas.core.series.Series'>

Pandas Series to a NumPy array:
[10 20 30 40 50]
Type: <class 'numpy.ndarray'>

Explanation:

Import Pandas and NumPy Libraries: Import the Pandas and NumPy libraries to work with Series and arrays.
Create Pandas Series: Define a Pandas Series with some example data.
Convert to NumPy Array: Use the to_numpy() method of the Pandas Series to convert it into a NumPy array.
Print NumPy Array: Output the resulting NumPy array to verify the conversion.

For more Practice: Solve these Related Problems:

Write a Numpy program to convert a Pandas Series with date-time indices into a NumPy array and extract the year from each element.
Write a Numpy program to convert a Pandas Series of categorical data into a NumPy array using label encoding.
Write a Numpy program to convert a large Pandas Series to a NumPy array and perform vectorized operations to standardize its values.
Write a Numpy program to convert a Pandas Series with missing values into a NumPy array and impute missing data using interpolation.

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