Summary: in this tutorial, you’ll learn about Python dictionary comprehension to transform or filter items in a dictionary.
Introduction to Python dictionary comprehension #
A dictionary comprehension allows you to run a for loop on a dictionary and do something on each item like transforming or filtering and returns a new dictionary.
Unlike a for loop, a dictionary comprehension offers a more expressive and concise syntax when you use it correctly.
Here is the general syntax for dictionary comprehension:
{key:value for (key,value) in dict.items() if condition}Code language: CSS (css)This dictionary comprehension expression returns a new dictionary whose item specified by the expression key: value
Python dictionary comprehension examples #
We’ll take a look at how to use dictionary comprehension to transform and filter items in a dictionary.
Using Python dictionary comprehension to transform a dictionary #
Suppose that you have the following dictionary whose items are stock symbol and price:
stocks = {
'AAPL': 121,
'AMZN': 3380,
'MSFT': 219,
'BIIB': 280,
'QDEL': 266,
'LVGO': 144
}Code language: Python (python)To increase the price of each stock by 2%, you may come up with a for loop like this:
stocks = {
'AAPL': 121,
'AMZN': 3380,
'MSFT': 219,
'BIIB': 280,
'QDEL': 266,
'LVGO': 144
}
new_stocks = {}
for symbol, price in stocks.items():
new_stocks[symbol] = price*1.02
print(new_stocks)
Code language: Python (python)Output:
{'AAPL': 123.42, 'AMZN': 3447.6, 'MSFT': 223.38, 'BIIB': 285.6, 'QDEL': 271.32, 'LVGO': 146.88}Code language: Shell Session (shell)How it works.
- First, loop over the items of the
stocksdictionary - Second, increase the price by 2% and add the item to the new dictionary (
new_stocks).
The following example shows how to use dictionary comprehension to achieve the same result:
stocks = {
'AAPL': 121,
'AMZN': 3380,
'MSFT': 219,
'BIIB': 280,
'QDEL': 266,
'LVGO': 144
}
new_stocks = {symbol: price * 1.02 for (symbol, price) in stocks.items()}
print(new_stocks)Code language: Python (python)This dictionary comprehension is equivalent to the for loop counterpart:
for loop
new_stocks = {}
for symbol, price in stocks.items():
new_stocks[symbol] = price*1.02
Code language: Python (python)dictionary comprehension
new_stocks = {symbol: price * 1.02 for (symbol, price) in stocks.items()}
Code language: Python (python)Using Python dictionary comprehension to filter a dictionary #
To select stocks whose prices are greater than 200, you may use the following for loop:
stocks = {
'AAPL': 121,
'AMZN': 3380,
'MSFT': 219,
'BIIB': 280,
'QDEL': 266,
'LVGO': 144
}
selected_stocks = {}
for symbol, price in stocks.items():
if price > 200:
selected_stocks[symbol] = price
print(selected_stocks)
Code language: Python (python)How it works.
- First, iterate over the item of the
stocksdictionary. - Then, add the item to the
selected_stocksdictionary if the price is greater than200.
The following example uses the dictionary comprehension with an if clause to get the same result:
stocks = {
'AAPL': 121,
'AMZN': 3380,
'MSFT': 219,
'BIIB': 280,
'QDEL': 266,
'LVGO': 144
}
selected_stocks = {s: p for (s, p) in stocks.items() if p > 200}
print(selected_stocks)Code language: Python (python)And you can compare the for loop and dictionary comprehension:
for loop
selected_stocks = {}
for symbol, price in stocks.items():
if price > 200:
selected_stocks[symbol] = price
Code language: Python (python)dictionary comprehension
selected_stocks = {s: p for (s, p) in stocks.items() if p > 200}
Code language: Python (python)Summary #
- A dictionary comprehension iterates over items of a dictionary and allows you to create a new dictionary by transforming or filtering each item.