Python: How to Import and Read CSV to Various List Structures

Discover efficient methods to import and read CSV files into different list structures using Python. Learn how to handle CSV data as lists, dictionaries, and columns.
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Python: How to Import and Read CSV to Various List Structures

CSV (Comma-Separated Values) files are ubiquitous in data manipulation and storage. When working with data in Python, it's essential to know how to effectively import and read CSV files into various list structures. This post covers several approaches to handle CSV data, such as importing CSV columns into lists, converting entire CSV files into lists, and reading CSV data into lists of dictionaries.

Import CSV to List

Reading a CSV file into a simple list is straightforward in Python using the csv module. Below is an example demonstrating how to import data from a CSV file into a list.

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This code reads the entire CSV file and stores each row as a sublist within the data list.

Read CSV to List of Dictionaries

Working with dictionaries can be particularly useful when your CSV file contains headers. Here’s how you can convert a CSV file into a list of dictionaries:

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In this example, each row of the CSV file is converted into a dictionary. The keys of the dictionary are the column headers, making it easier to access individual entries.

Import CSV Column to List

Sometimes, you may only need to read a specific column from a CSV file. Here's how you can achieve that:

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This script reads only the data from the specified column and stores it in column_data.

Summary

By leveraging Python's csv module, you can efficiently read and manipulate CSV files into various list structures. Whether you need a simple list of rows, a list of dictionaries, or a specific column's data, these techniques provide robust solutions for data handling in Python.

Mastering these methods will enhance your ability to work with CSV files, making data manipulation tasks more effective and streamlined.