The 2 Best ways to read CSV files into a List of Dictionaries with Python

What will we cover?

First we will look at the classical way to a read CSV file into Python and understand why we want to read it into a list of Dictionaries.

Then we will demonstrate the two most convenient ways to read CSV files into a list of dictionaries in Python.

See this more general introduction to CSV files.

The classical way to read CSV files in Python

To make the demonstration we need a CSV file.

Save the following content in NameRecords.csv

First name,Last name,Age

Then we will read the content with the default CSV reader in Python.

import csv
with open('NameRecords.csv') as csvfile:
    csv_reader = csv.reader(csvfile)
    rows = list(csv_reader)

Then if you want to get the content it will be in a list of list represented in rows.

for row in rows:

Resulting in the following output.

['First name', 'Last name', 'Age']
['Connar', 'Ward', '15']
['Rose', 'Peterson', '18']
['Paul', 'Cox', '12']
['Hanna', 'Hicks', '10']

Which illustrates two problems.

  1. The column names are given in the first item of the list.
  2. The row is a list of the items, and you need to keep track of what they represent.

Hence, if we could read the content directly into a list of dictionaries, it would make your life as a programmer easier.

What do I mean? See the two methods below.

Method 1: Using DictReader

This is possible the classical way to do it and uses standard Python library CSV.

First you need a CSV file to work with. Save the following content in NameRecords.csv

First name,Last name,Age

Then the following will read the content into a list of dictionaries.

import csv
with open("files/NameRecords.csv", "r") as f:
    csv_reader = csv.DictReader(f)
    name_records = list(csv_reader)

Access to the content can be achieved as follows.

print(name_records[0]['First name'])
  • Advantage of approach: No additional library needs installation.
  • Disadvantage of approach: You cannot access remote files.

Method 2: Using pandas read_csv()

This approach can read remote data.

import pandas as pd
url = ""
name_records = pd.read_csv(url)
name_records = name_records.to_dict('records')

Again the data is structured in a list of records in dictionaries.

  • Advantage of approach: Can read remote files directly (like from GitHub)
  • Disadvantage of approach: Need to install pandas library.

For an example see this project with pandas read_csv.

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