DataFrame to Numpy Array - ( Pandas Operations )

Heading h2

Syntax

df.to_numpy()

Example

import pandas as pd

# creating a pandas DataFrame
data = {'Name':['John', 'Peter', 'Bob', 'Alice'], 
        'Age':[25, 30, 20, 35], 
        'Salary':[40000, 50000, 35000, 60000]}

df = pd.DataFrame(data)

# converting DataFrame to numpy array
numpy_array = df.to_numpy()

print(numpy_array)

Output

array([['John', 25, 40000],
       ['Peter', 30, 50000],
       ['Bob', 20, 35000],
       ['Alice', 35, 60000]])

Explanation

Pandas is a popular data manipulation library in Python. It provides many functionalities for data analysis, including the ability to convert a DataFrame to a numpy array.

The df.to_numpy() method is used to convert a pandas DataFrame to a numpy array. This function returns a numpy array with the same shape as the DataFrame.

In the above example, a pandas DataFrame is created, and then the df.to_numpy() method is used to convert it to a numpy array.

Use

Converting pandas DataFrames to numpy arrays is useful in many data analysis applications. Numpy arrays are often used in machine learning algorithms, and converting a pandas DataFrame to a numpy array allows data to be easily used as input in these algorithms.

Important Points

• Pandas provides the df.to_numpy() method to convert a DataFrame to a numpy array
• The method returns a numpy array with the same shape as the DataFrame
• Numpy arrays are often used in machine learning algorithms, making this method useful in data analysis applications

Summary

In conclusion, the df.to_numpy() method in Pandas can be used to convert a DataFrame to a numpy array. This method is useful in many data analysis applications, including machine learning, where numpy arrays are often used as input. Pandas and numpy are powerful tools for data analysis and manipulation in Python.