How to Use Values in pandas: Syntax and Examples

In pandas, you can use the values attribute on a DataFrame or Series to get the underlying data as a NumPy array. This is useful when you want to perform operations that require raw array data instead of pandas objects.

Syntax

The values attribute is used without parentheses on a pandas DataFrame or Series to extract the data as a NumPy array.

• DataFrame.values: Returns a 2D NumPy array of the DataFrame's data.
• Series.values: Returns a 1D NumPy array of the Series' data.

python

array = df.values
array_series = series.values

Example

This example shows how to create a pandas DataFrame and Series, then use values to get their underlying NumPy arrays.

python

import pandas as pd

# Create a DataFrame
data = {'Name': ['Alice', 'Bob', 'Charlie'], 'Age': [25, 30, 35]}
df = pd.DataFrame(data)

# Create a Series
series = pd.Series([10, 20, 30])

# Get underlying numpy arrays
df_values = df.values
series_values = series.values

print('DataFrame values:')
print(df_values)
print('\nSeries values:')
print(series_values)

Output

DataFrame values:
[['Alice' 25]
 ['Bob' 30]
 ['Charlie' 35]]

Series values:
[10 20 30]

Common Pitfalls

One common mistake is expecting values to preserve pandas index or column labels. It does not; it returns only raw data as a NumPy array without labels.

Also, for newer pandas versions, it is recommended to use to_numpy() instead of values for better consistency and options.

python

import pandas as pd

df = pd.DataFrame({'A': [1, 2], 'B': [3, 4]}, index=['x', 'y'])

# Using values loses index and columns
print('Using values:')
print(df.values)

# Using to_numpy() is preferred
print('\nUsing to_numpy():')
print(df.to_numpy())

Output

Using values:
[[1 3]
 [2 4]]

Using to_numpy():
[[1 3]
 [2 4]]

Quick Reference

Summary tips for using values in pandas:

• Use values to get raw NumPy arrays from DataFrames or Series.
• Labels (index/columns) are not included in the output.
• Prefer to_numpy() for more control and future compatibility.
• Useful for integrating pandas data with NumPy or other libraries.

Key Takeaways

Use values to extract raw NumPy arrays from pandas DataFrames or Series.

values returns data without index or column labels.

Prefer to_numpy() over values for better future support.

Extracted arrays are useful for NumPy operations or other libraries needing raw data.