# Basic dictionary filtering
scores = {'Alice': 85, 'Bob': 92, 'Charlie': 78, 'Diana': 95}
high_scores = {k: v for k, v in scores.items() if v >= 90}
print(f"High scores: {high_scores}")

# Different ways to filter dictionaries
scores = {'Alice': 85, 'Bob': 92, 'Charlie': 78, 'Diana': 95}

# Filter by value
high_scores = {k: v for k, v in scores.items() if v >= 90}
print(f"High scores: {high_scores}")

# Filter by key
names_with_a = {k: v for k, v in scores.items() if k.startswith('A')}
print(f"Names starting with A: {names_with_a}")

# Filter by key length
short_names = {k: v for k, v in scores.items() if len(k) <= 3}
print(f"Short names: {short_names}")

# Using filter function
def is_high_score(item):
    return item[1] >= 90

high_scores_filter = dict(filter(is_high_score, scores.items()))
print(f"Using filter(): {high_scores_filter}")

# Advanced filtering examples
students = {
    'Alice': {'age': 20, 'score': 85, 'grade': 'B'},
    'Bob': {'age': 19, 'score': 92, 'grade': 'A'},
    'Charlie': {'age': 21, 'score': 78, 'grade': 'C'},
    'Diana': {'age': 20, 'score': 95, 'grade': 'A'}
}

# Filter by nested value
a_students = {k: v for k, v in students.items() if v['grade'] == 'A'}
print(f"A students: {a_students}")

# Multiple conditions
young_high_performers = {k: v for k, v in students.items() 
                        if v['age'] < 21 and v['score'] >= 90}
print(f"Young high performers: {young_high_performers}")

# Filter and transform
names_scores = {k: v['score'] for k, v in students.items() 
               if v['score'] >= 85}
print(f"Names and scores >= 85: {names_scores}")

# Custom filter function
def meets_criteria(student_data):
    name, data = student_data
    return data['age'] >= 20 and data['score'] >= 85

qualified = dict(filter(meets_criteria, students.items()))
print(f"Qualified students: {qualified}")