python pandas groupby agg get lag1

import pandas as pd

# 创建DataFrame对象
data = {'A': ['foo', 'bar', 'foo', 'bar', 'foo', 'bar', 'foo', 'foo'],
        'B': ['one', 'one', 'two', 'two', 'two', 'one', 'two', 'one'],
        'C': [1, 2, 3, 4, 5, 6, 7, 8],
        'D': [10, 20, 30, 40, 50, 60, 70, 80]}
df = pd.DataFrame(data)

# 按照列'A'进行分组，并计算每组的平均值
grouped = df.groupby('A')
result = grouped.mean()
print(result)

import pandas as pd

# 创建DataFrame对象
data = {'A': ['foo', 'bar', 'foo', 'bar', 'foo', 'bar', 'foo', 'foo'],
        'B': ['one', 'one', 'two', 'two', 'two', 'one', 'two', 'one'],
        'C': [1, 2, 3, 4, 5, 6, 7, 8],
        'D': [10, 20, 30, 40, 50, 60, 70, 80]}
df = pd.DataFrame(data)

# 按照列'A'进行分组，并计算每组的平均值和总和
grouped = df.groupby('A')
result = grouped.agg(['mean', 'sum'])
print(result)

import pandas as pd

# 创建Series对象
s = pd.Series([1, 2, 3, 4, 5], index=['a', 'b', 'c', 'd', 'e'])

# 获取索引为'b'的值
value = s.get('b')
print(value)

# 创建DataFrame对象
df = pd.DataFrame({'A': [1, 2, 3], 'B': [4, 5, 6]})

# 获取列'A'的值
values = df.get('A')
print(values)