groupby

# 创建一个示例 DataFrame
data = {'Category': ['A', 'B', 'A', 'B', 'A', 'B', 'A', 'A'],
        'Value': [10, 20, 15, 25, 30, 35, 40, 45]}
df = pd.DataFrame(data)
print(df)
  Category  Value
0        A     10
1        B     20
2        A     15
3        B     25
4        A     30
5        B     35
6        A     40
7        A     45

# 使用 groupby 分组
grouped = df.groupby('Category')

# 获取某个组
roup_A = grouped.get_group('A')
print(group_A)

  Category  Value
0        A     10
2        A     15
4        A     30
6        A     40
7        A     45

# 每个组的详细信息，将每个组转为list
for name, group in grouped:
    print(f"Group: {name}")
    print(group)
    print(group["Value"].tolist())

Group: A
  Category  Value
0        A     10
2        A     15
4        A     30
6        A     40
7        A     45
[10, 15, 30, 40, 45]
Group: B
  Category  Value
1        B     20
3        B     25
5        B     35
[20, 25, 35]