If you attempt to call the
values() method on a NumPy array, you will raise the error AttributeError: ‘numpy.ndarray’ object has no attribute ‘values’. The
values() method belongs to the DataFrame object. This error typically occurs when trying to call values after already converting a Series or DataFrame to NumPy array. You can avoid this error by checking the type of the object before calling values.
This tutorial will go through the error and how to solve it with code examples.
Table of contents
AttributeError: ‘numpy.ndarray’ object has no attribute ‘values’
AttributeError occurs in a Python program when we try to access an attribute (method or property) that does not exist for a particular object. The values method is a
DataFrame method, not a
numpy.ndarray method which returns a NumPy representation of a DataFrame.
Consider the following CSV file,
pizza,price margherita,£7.99 pepperoni,£8.99 four cheeses,£10.99 funghi,£8.99
We will attempt to load this file into a DataFrame using
pandas.read_csv to append a new pizza and its price.
import pandas as pd import numpy as np df = pd.read_csv('pizzas.csv') df
pizza price 0 margherita £7.99 1 pepperoni £8.99 2 four cheeses £10.99 3 funghi £8.99
Now that we have the DataFrame, we can convert it to a NumPy array using values:
data = df.values data
array([['margherita', '£7.99'], ['pepperoni', '£8.99'], ['four cheeses', '£10.99'], ['funghi', '£8.99']], dtype=object)
We can append a new pizza to the list using
new_data = np.append(data, np.array([['tartufo', '£14.99']]), axis=0) new_data
Let’s try to get the pizza data back into a DataFrame and save it to a new CSV file.
new_df = pd.DataFrame(new_data.values) new_df.to_csv('new_pizzas.csv')
--------------------------------------------------------------------------- AttributeError Traceback (most recent call last) Input In , in <cell line: 1>() ----> 1 new_df = pd.DataFrame(new_data.values) AttributeError: 'numpy.ndarray' object has no attribute 'values'
The error occurs because the
new_data variable is a
numpy.ndarray, which does not have values as an attribute. We can verify that new_data is a
numpy.ndarray using the built-in
We can convert the array to a DataFrame without using values. Let’s look at the revised code:
new_df = pd.DataFrame(new_data) new_df.to_csv('new_pizzas.csv')
The above code will run with no error and will write a new CSV file called
new_pizzas.csv in the working directory.
Congratulations on reading to the end of this tutorial! If you encounter this error, ensure that you check the type of object that is throwing the error using the
type() method. If the object is a NumPy ndarray you can remove the values method call.
For further reading on AttributeErrors, go to the article:
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Have fun and happy researching!
Suf is a research scientist at Moogsoft, specializing in Natural Language Processing and Complex Networks. Previously he was a Postdoctoral Research Fellow in Data Science working on adaptations of cutting-edge physics analysis techniques to data-intensive problems in industry. In another life, he was an experimental particle physicist working on the ATLAS Experiment of the Large Hadron Collider. His passion is to share his experience as an academic moving into industry while continuing to pursue research. Find out more about the creator of the Research Scientist Pod here and sign up to the mailing list here!