How to Read Specific Columns from a CSV File Without Headers in Pandas?

Reading Table Data into Pandas Without Headers

When working with data in a tabular format, such as a CSV file, it may be necessary to read specific columns without the presence of headers. Using Pandas, a powerful Python library for data manipulation, this can be achieved by employing a combination of options.

To read a subset of columns from a CSV file without headers, you can utilize the read_csv() function with the following parameters:

• header=None: This parameter specifies that the CSV file does not contain any header row.
• usecols=[column_indices]: This parameter allows you to select specific columns by providing a list of the desired column indices (starting from 0).

For example, to read only the 4th and 7th columns of a CSV file without headers named data.csv, you would use the following code:

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

df = pd.read_csv('data.csv', header=None, usecols=[3, 6])</code>

This code will create a DataFrame df containing only the 4th and 7th columns of the CSV file. It is important to note that in this scenario, the columns will be named as 0, 1, ..., n.

To learn more about working with header-less CSV files in Pandas, you can refer to the official documentation.

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