有没有更好的方法在多个条件下使用map函数来做熊猫groupby？

from collections import defaultdict

data = [
    {'animal': 'panda', 'color': 'black', 'age': 5},
    {'animal': 'panda', 'color': 'white', 'age': 3},
    {'animal': 'panda', 'color': 'black', 'age': 4},
    {'animal': 'elephant', 'color': 'gray', 'age': 10},
]

def group_by_conditions(data, conditions):
    grouped = defaultdict(list)
    for item in data:
        key = tuple(item[attr] for attr in conditions)
        grouped[key].append(item)
    return grouped

# 使用示例
conditions = ['animal', 'color']
grouped_data = group_by_conditions(data, conditions)

for key, group in grouped_data.items():
    print(f"Key: {key}, Group: {group}")

import pandas as pd

df = pd.DataFrame(data)
grouped_df = df.groupby(['animal', 'color'])
for name, group in grouped_df:
    print(f"Name: {name}, Group: {group}")