Write a NumPy array to an Excel file and read it back

NumPy: I/O Operations Exercise-12 with Solution

Write a NumPy array to an Excel file using a library like pandas and then read it back into a NumPy array.

Sample Solution:

Python Code:

import numpy as np
import pandas as pd

# Create a NumPy array
data_array = np.array([[10, 20, 30], [40, 50, 60], [70, 80, 90]])

# Define the path to the Excel file
excel_file_path = 'data.xlsx'

# Convert the NumPy array to a Pandas DataFrame
df = pd.DataFrame(data_array, columns=['Column1', 'Column2', 'Column3'])

# Write the DataFrame to an Excel file
df.to_excel(excel_file_path, index=False)

# Read the Excel file back into a Pandas DataFrame
df_loaded = pd.read_excel(excel_file_path)

# Convert the DataFrame back to a NumPy array
loaded_array = df_loaded.to_numpy()

# Print the original and loaded NumPy arrays
print("Original NumPy Array:")
print(data_array)

print("\nLoaded NumPy Array from Excel File:")
print(loaded_array)

Output:

Original NumPy Array:
[[10 20 30]
 [40 50 60]
 [70 80 90]]

Loaded NumPy Array from Excel File:
[[10 20 30]
 [40 50 60]
 [70 80 90]]

Explanation:

• Import NumPy and Pandas Libraries: Import the NumPy and Pandas libraries to handle arrays and data frames.
• Create NumPy Array: Define a NumPy array with some example data.
• Define Excel File Path: Specify the path where the Excel file will be saved.
• Convert Array to DataFrame: Convert the NumPy array to a Pandas DataFrame, providing column names for better readability.
• Write DataFrame to Excel: Use to_excel() to write the DataFrame to an Excel file, setting index=False to omit row indices.
• Read Excel File to DataFrame: Use read_excel() to read the contents of the Excel file back into a Pandas DataFrame.
• Convert DataFrame to Array: Convert the loaded DataFrame back to a NumPy array using to_numpy().
• Finally print the original NumPy array and the loaded array to verify that the data was saved and read correctly.

Python-Numpy Code Editor:

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