Convert Pandas DataFrame to NumPy array and print
NumPy: Interoperability Exercise-5 with Solution
Write a NumPy program to convert a Pandas DataFrame to a NumPy array and print the array.
Sample Solution:
Python Code:
import numpy as np
import pandas as pd
# Initialize a Pandas DataFrame
data = {'A': [1, 2, 3, 4, 5],
'B': [10, 20, 30, 40, 50],
'C': [100, 200, 300, 400, 500]}
df = pd.DataFrame(data)
print("Original Pandas DataFrame:",df)
print("Type:",type(df))
# Convert the Pandas DataFrame to a NumPy array
numpy_array = df.to_numpy()
print("\nPandas DataFrame to a NumPy array:")
# Print the NumPy array
print(numpy_array)
print("Type:",type(numpy_array))
Output:
Original Pandas DataFrame: A B C 0 1 10 100 1 2 20 200 2 3 30 300 3 4 40 400 4 5 50 500 Type: <class 'pandas.core.frame.DataFrame'> Pandas DataFrame to a NumPy array: [[ 1 10 100] [ 2 20 200] [ 3 30 300] [ 4 40 400] [ 5 50 500]] Type: <class 'numpy.ndarray'>
Explanation:
- Importing libraries: We first import the numpy and pandas libraries for array and DataFrame manipulations.
- Initializing a DataFrame: A Pandas DataFrame is initialized with some data.
- Converting to NumPy array: The Pandas DataFrame is converted to a NumPy array using the to_numpy() method.
- Printing the array: The resulting NumPy array is printed.
Python-Numpy Code Editor: