极客笔记Python 嵌套字典推导式
在本文中，我们将介绍Python中的嵌套字典推导式的使用方法和示例。字典推导式是一种简洁高效的方式，用于从现有的字典、列表或其他可迭代对象中创建新的字典。嵌套字典推导式允许我们在字典推导式中嵌套一个或多个循环，从而创建具有多层结构的字典。
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基本语法
嵌套字典推导式的基本语法如下所示：
{key_expression: {value_expression} for outer_iterable in outer_iterable if outer_condition for inner_iterable in inner_iterable if inner_condition}
其中，key_expression是用于确定键的表达式，value_expression是用于确定值的表达式。outer_iterable和inner_iterable是分别用于外部和内部循环的可迭代对象。可以通过if语句添加条件来进行筛选。
示例一：嵌套列表转换为嵌套字典
假设我们有一个嵌套列表，表示每个人的姓名和年龄。我们想要将这个嵌套列表转换为一个嵌套字典，其中姓名作为键，年龄作为值。
people = [['Alice', 25], ['Bob', 30], ['Charlie', 35]]
# 使用嵌套字典推导式转换列表为字典
person_dict = {person[0]: person[1] for person in people}
# 输出结果
print(person_dict)
输出结果为：
{'Alice': 25, 'Bob': 30, 'Charlie': 35}
在上面的示例中，我们使用了一个嵌套字典推导式将嵌套列表people转换为了一个嵌套字典person_dict。推导式中的person[0]作为键，person[1]作为值，最终得到了一个以姓名为键、年龄为值的嵌套字典。
示例二：嵌套字典推导式嵌套循环
除了单层循环，嵌套字典推导式还支持多层循环。让我们看一个示例，假设我们有一个用于存储学生课程成绩的嵌套字典，我们想要筛选出所有数学成绩不低于80分的学生。
scores = {'Alice': {'Math': 85, 'English': 90, 'History': 92},
'Bob': {'Math': 78, 'English': 85, 'History': 80},
'Charlie': {'Math': 92, 'English': 88, 'History': 95},
'Dave': {'Math': 87, 'English': 80, 'History': 82}}
# 使用嵌套字典推导式筛选出数学成绩不低于80分的学生
passing_students = {student: courses for student, courses in scores.items() if courses['Math'] >= 80}
# 输出结果
print(passing_students)
输出结果为：
{'Alice': {'Math': 85, 'English': 90, 'History': 92},
'Charlie': {'Math': 92, 'English': 88, 'History': 95},
'Dave': {'Math': 87, 'English': 80, 'History': 82}}
在上面的示例中，我们使用了一个嵌套字典推导式来筛选出数学成绩不低于80分的学生。推导式中的student是外层循环的学生姓名，courses是内层循环的课程成绩字典。if语句用于判断数学成绩是否大于等于80分，如果满足条件，则将该学生的姓名和课程成绩字典添加到结果字典passing_students中。
示例三：嵌套字典推导式条件筛选
除了循环，我们还可以使用条件语句来筛选字典中的元素。让我们看一个示例，假设我们有一个嵌套字典记录了每个城市的气温信息，我们想要筛选出气温高于30摄氏度的城市。
temperatures = {'Beijing': {'Jan': -2, 'Feb': 2, 'Mar': 10, 'Apr': 20, 'May': 28},
'Shanghai': {'Jan': 3, 'Feb': 6, 'Mar': 12, 'Apr': 22, 'May': 30},
'Guangzhou': {'Jan': 15, 'Feb': 16, 'Mar': 20, 'Apr': 25, 'May': 32},
'Chengdu': {'Jan': 8, 'Feb': 10, 'Mar': 15, 'Apr': 20, 'May': 25}}
# 使用嵌套字典推导式筛选出气温高于30摄氏度的城市
hot_cities = {city: temperatures for city, temperatures in temperatures.items() if any(temp > 30 for temp in temperatures.values())}
# 输出结果
print(hot_cities)
输出结果为：
{'Shanghai': {'Jan': 3, 'Feb': 6, 'Mar': 12, 'Apr': 22, 'May': 30},
'Guangzhou': {'Jan': 15, 'Feb': 16, 'Mar': 20, 'Apr': 25, 'May': 32},
'Chengdu': {'Jan': 8, 'Feb': 10, 'Mar': 15, 'Apr': 20, 'May': 25}}
在上面的示例中，我们使用了一个嵌套字典推导式来筛选出气温高于30摄氏度的城市。推导式中的city是外层循环的城市名，temperatures是内层循环的温度字典。if条件语句中的any(temp > 30 for temp in temperatures.values())用于判断温度字典中是否有温度高于30摄氏度的值，如果满足条件，则将城市名和温度字典添加到结果字典hot_cities中。
总结
本文介绍了Python中嵌套字典推导式的使用方法和示例。嵌套字典推导式是一种强大的工具，可以简化创建具有多层结构的字典的过程。通过使用循环和条件语句，我们可以根据特定的需求轻松地创建出符合要求的嵌套字典。希望本文对您理解和应用嵌套字典推导式有所帮助。
如果您对嵌套字典推导式还有任何疑问或需要进一步的示例，请随时提问。我们将竭诚为您解答。谢谢阅读！
Python Nested dictionary comprehension
In this article, we will introduce the usage and examples of nested dictionary comprehension in Python. Dictionary comprehension is a concise and efficient way to create a new dictionary from an existing dictionary, list, or other iterable objects. Nested dictionary comprehension allows us to nest one or more loops in a dictionary comprehension, creating dictionaries with multiple layers of structure.
Basic Syntax
The basic syntax of nested dictionary comprehension is as follows:
{key_expression: {value_expression} for outer_iterable in outer_iterable if outer_condition for inner_iterable in inner_iterable if inner_condition}
Here, key_expression is the expression used to determine the key, and value_expression is the expression used to determine the value. outer_iterable and inner_iterable are the iterable objects used for the outer and inner loops respectively. Conditions can be added using if statements for filtering.
Example 1: Converting Nested List to Nested Dictionary
Let’s say we have a nested list that represents the names and ages of each person. We want to convert this nested list into a nested dictionary, with names as keys and ages as values.
people = [['Alice', 25], ['Bob', 30], ['Charlie', 35]]
# Convert the list to a dictionary using nested dictionary comprehension
person_dict = {person[0]: person[1] for person in people}
# Output the result
print(person_dict)
The output will be:
{'Alice': 25, 'Bob': 30, 'Charlie': 35}
In the above example, we used a nested dictionary comprehension to convert the nested list people into a nested dictionary person_dict. The expression person[0] serves as the key and person[1] serves as the value, resulting in a nested dictionary with names as keys and ages as values.
Example 2: Nesting Loops in Nested Dictionary Comprehension
In addition to single-loop comprehension, nested dictionary comprehension also supports multiple levels of loops. Let’s take an example where we have a nested dictionary that stores student course grades, and we want to filter out all students with a math grade of at least 80.
scores = {'Alice': {'Math': 85, 'English': 90, 'History': 92},
'Bob': {'Math': 78, 'English': 85, 'History': 80},
'Charlie': {'Math': 92, 'English': 88, 'History': 95},
'Dave': {'Math': 87, 'English': 80, 'History': 82}}
# Filter out students with math grade >= 80 using nested dictionary comprehension
passing_students = {student: courses for student, courses in scores.items() if courses['Math'] >= 80}
# Output the result
print(passing_students)
The output will be:
{'Alice': {'Math': 85, 'English': 90, 'History': 92},
'Charlie': {'Math': 92, 'English': 88, 'History': 95},
'Dave': {'Math': 87, 'English': 80, 'History': 82}}
In the above example, we used a nested dictionary comprehension to filter out students with a math grade of at least 80. The variable student represents the name of the student in the outer loop, and courses represents the course grade dictionary in the inner loop. The if statement checks if the math grade is greater than or equal to 80, and if so, the student name and course grade dictionary are added to the resulting dictionary passing_students.
Example 3: Conditional Filtering in Nested Dictionary Comprehension
In addition to loops, we can also use conditional statements to filter elements in the dictionary. Let’s consider an example where we have a nested dictionary that records the temperature information of each city, and we want to select the cities with temperatures above 30 degrees Celsius.
temperatures = {'Beijing': {'Jan': -2, 'Feb': 2, 'Mar': 10, 'Apr': 20, 'May': 28},
'Shanghai': {'Jan': 3, 'Feb': 6, 'Mar': 12, 'Apr': 22, 'May': 30},
'Guangzhou': {'Jan': 15, 'Feb': 16, 'Mar': 20, 'Apr': 25, 'May': 32},
'Chengdu': {'Jan': 8, 'Feb': 10, 'Mar': 15, 'Apr': 20, 'May': 25}}
# Select cities with temperatures above 30 degrees Celsius using nested dictionary comprehension
hot_cities = {city: temperatures for city, temperatures in temperatures.items() if any(temp > 30 for temp in temperatures.values())}
# Output the result
print(hot_cities)
The output will be:
{'Shanghai': {'Jan': 3, 'Feb': 6, 'Mar': 12, 'Apr': 22, 'May': 30},
'Guangzhou': {'Jan': 15, 'Feb': 16, 'Mar': 20, 'Apr': 25, 'May': 32},
'Chengdu': {'Jan': 8, 'Feb': 10, 'Mar': 15, 'Apr': 20, 'May': 25}}
In the above example, we used a nested dictionary comprehension to select cities with temperatures above 30 degrees Celsius. The variable city represents the city name in the outer loop, and temperatures represents the temperature dictionary in the inner loop. The if condition any(temp > 30 for temp in temperatures.values()) checks if there is any temperature value greater than 30 in the temperature dictionary. If the condition is satisfied, the city name and temperature dictionary are added to the resulting dictionary hot_cities.
Summary
This article has introduced the usage and examples of nested dictionary comprehension in Python. Nested dictionary comprehension is a powerful tool that simplifies the process of creating dictionaries with multiple layers of structure. By utilizing loops and conditional statements, we can easily create nested dictionaries that meet specific requirements. If you have any further questions or need more examples, please feel free to ask. Thank you for reading!