Iterate Through List of Dictionaries in Python

In this article, we will learn various methods to iterate through the list of dictionaries in Python. When working with data in Python, it is very common to encounter scenarios where you have a list of dictionaries. Each dictionary represents an individual data entry, and you need to perform operations or extract specific information from these dictionaries.

Using a For Loop and Dictionary Access Methods

The approach is to use a for loop to iterate through each dictionary in the list. Inside the loop, we can use dictionary access methods like keys(), values(), or items() to retrieve the keys, values, or key−value pairs, respectively.

Syntax

keys()

dictionary.keys()

keys() method returns a view object that contains the keys of the dictionary.

values()

dictionary.values()

values() method returns a view object that contains the values of the dictionary.

items()

dictionary.items()

items() method returns a view object that contains the key−value pairs of the dictionary as tuples.

Explanation

• Create a list of dictionary `list_of_dict`.

• Iterate through the list of dictionaries using for loop.

• Now we use the items() method to access the key−value pairs in each dictionary.

• Print the Key, Value pairs.

Example

list_of_dict = [
    {"course": "DBMS", "price": 1500},
    {"course": "Python", "price": 2500},
    {"course": "Java", "price": 2500},
]

for dict in list_of_dict:
    for key, value in dict.items():
        print(key, ":", value)
    print("")

Output

course : DBMS
price : 1500

course : Python
price : 2500

course : Java
price : 2500

Using List Comprehension

List comprehension provides a way to iterate through the list of dictionaries and perform operations on each dictionary. Now we will use list comprehension to iterate over the entire list

Syntax:

[expression for element in iterable]

• Iterable: It can be a list, set, tuple, or any Python iterable.

• Element: item present in the iterable.

• Expression: Operation that we want to perform on the element

Explanation

• Create a list of dictionary `list_of_dict`.

• Use the list comprehensions to iterate over the list and fetch information in the dictionary in separate lists.

Example

list_of_dict = [
    {"course": "DBMS", "price": 1500},
    {"course": "Python", "price": 2500},
    {"course": "Java", "price": 2500},
]

# iterating through each dictionary
course= [dictionary["course"] for dictionary in list_of_dict]
price= [dictionary["price"] for dictionary in list_of_dict]

print(course)
print(price)

Output

['DBMS', 'Python', 'Java']
[1500, 2500, 2500]

Using the map() Function

The map() function is a built−in python function that applies a specified function to each item in an iterable in our case the iterable is a list and returns an iterator that yields the results. It takes two arguments: the function to apply and the iterable.

Syntax

map(function, iterable)

• Iterable: The sequence of items to which the specified function will be applied.

• Function: The function we want to apply to the items in the iterator.

Explanation

• Create a list of dictionaries

• Pass the function and iterable i.e. list of dictionaries to the map() method.

• Use the list() method to convert the result given by the map() into a list.

Example

list_of_dict = [
    {"course": "DBMS", "price": 1500},
    {"course": "Python", "price": 2500},
    {"course": "Java", "price": 2500},
]

def func(dict):
    return dict["course"]

# applying the function to all the dictionaries present in the list.
course = list(map(func, list_of_dict))

print(course)

Output

['DBMS', 'Python', 'Java']

Using the pandas Library

The DataFrame() constructor will convert the list of dictionaries into a data frame. Each dictionary in the list will be represented as a row in the data frame. Iterating the list of dictionaries can be convenient when dealing with large datasets.

Syntax

pd.DataFrame(iterable)

Iterable:Sequence of elements. For example list, tuple.

Explanation

• Create a list of dictionaries

• Pass the list of dictionaries to the DataFrame() constructor in the pandas library.

• The constructor will return a data frame object with each dictionary as a row in the data frame

Example

import pandas as pd

list_of_dict = [
    {"course": "DBMS", "price": 1500},
    {"course": "Python", "price": 2500},
    {"course": "Java", "price": 2500},
]

df = pd.DataFrame(list_of_dict)
print(df)

Output

   course  price
0    DBMS   1500
1  Python   2500
2    Java   2500

Using from_records() Method in DataFrame class of the pandas library

In this approach we will use the from_records() method. The pd.DataFrame.from_records() method in pandas allows us to create a DataFrame from a list of records (tuples or structured arrays) or an iterable.

Syntax

pd.DataFrame.from_records(data)

• Data: Structured array, List of dictionaries in this case.

Explanation

• Create a list of dictionaries.

• Pass the list to the from_records() method

• The from_records() method will return a data frame with each dictionary in the list as a row in the data frame.

Example

import pandas as pd

list_of_dict = [
    {"course": "DBMS", "price": 1500},
    {"course": "Python", "price": 2500},
    {"course": "Java", "price": 2500},
]
df = pd.DataFrame.from_records(list_of_dict)
print(df)

Output

   course  price
0    DBMS   1500
1  Python   2500
2    Java   2500

Conclusion

Throughout this article, we explored different approaches including looping, list comprehension and even leveraging the capabilities of the pandas library to iterate through a list of dictionaries. Happy learning!