Pandas to NumPy
Converting a Pandas DataFrame or Series to a NumPy array is a straightforward process. NumPy is a powerful library for numerical computations in Python, and Pandas is built on top of NumPy. Here are the steps to convert a Pandas DataFrame or Series to a NumPy array:
- Import the necessary libraries:
import pandas as pd
import numpy as np
- If you have a Pandas DataFrame and want to convert it to a NumPy array, you can use the
valuesattribute of the DataFrame:
# Create a Pandas DataFrame
df = pd.DataFrame({'A': [1, 2, 3], 'B': [4, 5, 6]})
# Convert DataFrame to NumPy array
numpy_array = df.values
print(numpy_array)
- If you have a Pandas Series and want to convert it to a NumPy array, you can use the
valuesattribute of the Series:
# Create a Pandas Series
series = pd.Series([1, 2, 3, 4, 5])
# Convert Series to NumPy array
numpy_array = series.values
print(numpy_array)
In both cases, the resulting numpy_array will be a NumPy array containing the data from the original DataFrame or Series. The conversion is quick and efficient since Pandas and NumPy data structures are tightly integrated. Keep in mind that any changes made to the NumPy array will not reflect back in the original DataFrame or Series and vice versa, as they become independent objects after conversion.
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