How do you convert a Pandas DataFrame column or row to a list?

Mary-Kate Olsen
Release: 2024-10-27 01:02:30
Original
899 people have browsed it

How do you convert a Pandas DataFrame column or row to a list?

How to Convert Pandas DataFrame Column or Row to List

Within a pandas DataFrame, each column is represented by a pandas Series object. To obtain a list representation of a column, you can use the tolist() method on the Series object. For example:

<code class="python">import pandas as pd

data_dict = {'cluster': ['A', 'A', 'A', 'B', 'B', 'B', 'C', 'C', 'C'],
             'load_date': ['1/1/2014', '2/1/2014', '3/1/2014', '4/1/2014', '4/1/2014', '4/1/2014', '7/1/2014', '8/1/2014', '9/1/2014'],
             'budget': [1000, 12000, 36000, 15000, 12000, 90000, 22000, 30000, 53000],
             'actual': [4000, 10000, 2000, 10000, 11500, 11000, 18000, 28960, 51200],
             'fixed_price': ['Y', 'Y', 'Y', 'N', 'N', 'N', 'N', 'N', 'N']}

df = pd.DataFrame(data_dict)
cluster_list = df['cluster'].tolist()
print(cluster_list)</code>
Copy after login

Output:

['A', 'A', 'A', 'B', 'B', 'B', 'C', 'C', 'C']
Copy after login

You can also cast a Series object to a list directly using list():

<code class="python">cluster_list = list(df['cluster'])</code>
Copy after login

To obtain a list representation of an entire row, you can access it using the iloc() method of the DataFrame.

<code class="python">row1_list = df.iloc[0].tolist()
print(row1_list)</code>
Copy after login

Output:

[1000, '4000', 'Y']
Copy after login

Similarly, you can cast the entire row to a list directly:

<code class="python">row1_list = list(df.iloc[0])</code>
Copy after login

The above is the detailed content of How do you convert a Pandas DataFrame column or row to a list?. For more information, please follow other related articles on the PHP Chinese website!

source:php.cn
Statement of this Website
The content of this article is voluntarily contributed by netizens, and the copyright belongs to the original author. This site does not assume corresponding legal responsibility. If you find any content suspected of plagiarism or infringement, please contact admin@php.cn
Latest Articles by Author
Popular Tutorials
More>
Latest Downloads
More>
Web Effects
Website Source Code
Website Materials
Front End Template
About us Disclaimer Sitemap
php.cn:Public welfare online PHP training,Help PHP learners grow quickly!