Filtering a List of Dictionary on Multiple Values in Python

Filtering a list of dictionaries is a common task in programming, especially when dealing with datasets. Often, you may need to extract specific elements that meet certain criteria. In this article, we'll explore four generally used methods for filtering a list of dictionaries based on multiple values, providing code examples in Python.

Filtering A List Of Dictionaries Based On Multiple Values

Below, are the method of Filtering A List Of Dictionaries Based On Multiple Values in Python.

• Using List Comprehension
• Using Filter and Lambda Function
• Using Pandas DataFrame
• Using custom Function

Filtering A List Of Dictionaries Based On Multiple Values Using List Comprehension

List comprehension is a concise and efficient way to create lists in Python. It can be leveraged to filter a list of dictionaries based on multiple values.

Example: In this example, the code creates a list of dictionaries named 'data' and filters it, retaining only dictionaries where the 'age' is greater than 25 and the 'city' is 'New York'. The resulting filtered data is stored in the 'filtered_data' variable and printed.

data = [
    {'name': 'Alice', 'age': 25, 'city': 'New York'},
    {'name': 'Bob', 'age': 30, 'city': 'San Francisco'},
    {'name': 'Charlie', 'age': 28, 'city': 'New York'},
    # ... additional dictionaries ...
]

filtered_data = [item for item in data if item['age'] > 25 and item['city'] == 'New York']
print(filtered_data)

[{'name': 'Charlie', 'age': 28, 'city': 'New York'}]

Filtering A List Of Dictionaries Based On Multiple Values Using Filter and Lambda Function

The filter function in combination with a lambda function is another approach for filtering lists based on multiple criteria.

Example : In this example, The code defines a list of dictionaries called 'data' and uses the `filter` function with a lambda expression to create 'filtered_data', containing dictionaries where the 'age' is greater than 25 and the 'city' is 'New York'.

data = [
    {'name': 'Alice', 'age': 25, 'city': 'New York'},
    {'name': 'Bob', 'age': 30, 'city': 'San Francisco'},
    {'name': 'Charlie', 'age': 28, 'city': 'New York'},
    # ... additional dictionaries ...
]

filtered_data = list(filter(lambda x: x['age'] > 25 and x['city'] == 'New York', data))
print(filtered_data)

[{'name': 'Charlie', 'age': 28, 'city': 'New York'}]

Filtering A List Of Dictionaries Based On Multiple Values Using Pandas DataFrame

If your data is structured and large, using a Pandas DataFrame can provide a powerful solution for filtering.

Example : In this example, The code uses the Pandas library to create a DataFrame from the list of dictionaries named 'data'. It then filters the DataFrame to include rows where the 'age' is greater than 25 and the 'city' is 'New York'.

import pandas as pd

data = [
    {'name': 'Alice', 'age': 25, 'city': 'New York'},
    {'name': 'Bob', 'age': 30, 'city': 'San Francisco'},
    {'name': 'Charlie', 'age': 28, 'city': 'New York'},
    # ... additional dictionaries ...
]

df = pd.DataFrame(data)
filtered_data = df[(df['age'] > 25) & (df['city'] == 'New York')].to_dict('records')
print(filtered_data)

Output

[{'name': 'Charlie', 'age': 28, 'city': 'New York'}]

Filtering A List Of Dictionaries Based On Multiple Values Using custom Function

Create a custom filtering function that accepts a dictionary and returns True if it meets the criteria.

Example : In this example, The code defines a custom filtering function named 'custom_filter' that checks if the 'age' is greater than 25 and the 'city' is 'New York' for a given dictionary. It then applies this filter function to the list of dictionaries called 'data' using the `filter` function, creating 'filtered_data'.

def custom_filter(item):
    return item['age'] > 25 and item['city'] == 'New York'

data = [
    {'name': 'Alice', 'age': 25, 'city': 'New York'},
    {'name': 'Bob', 'age': 30, 'city': 'San Francisco'},
    {'name': 'Charlie', 'age': 28, 'city': 'New York'},
    # ... additional dictionaries ...
]

filtered_data = list(filter(custom_filter, data))
print(filtered_data)

[{'name': 'Charlie', 'age': 28, 'city': 'New York'}]

Conclusion

Filtering a list of dictionaries based on multiple values is a common requirement in programming. The choice of method depends on the specific use case, data size, and personal preference. These four methods - list comprehension, filter with lambda function, Pandas DataFrame, and custom filtering function - provide versatile options for efficiently extracting relevant information from your data.