我在分组数据框架上计算了滚动总和,但是它加起来的方式错误,它是未来的总和,当我需要过去的总和时.
我在这做错了什么?
我导入数据并按维度和日期排序(我已尝试删除日期排序)
df = pd.read_csv('Input.csv', parse_dates=True)
df.sort_values(['Dimension','Date'])
print(df)
然后我创建一个新列,它是一个按滚动窗口分组的多索引
new_column = df.groupby('Dimension').Value1.apply(lambda x:
x.rolling(window=3).sum())
然后我将索引重置为与原始索引相同
df['Sum_Value1'] = new_column.reset_index(level=0, drop=True)
print(df)
我也尝试在计算之前反转索引,但也失败了.
输入
Dimension,Date,Value1,Value2
1,4/30/2002,10,20
1,1/31/2002,10,20
1,10/31/2001,10,20
1,7/31/2001,10,20
1,4/30/2001,10,20
1,1/31/2001,10,20
1,10/31/2000,10,20
2,4/30/2002,10,20
2,1/31/2002,10,20
2,10/31/2001,10,20
2,7/31/2001,10,20
2,4/30/2001,10,20
2,1/31/2001,10,20
2,10/31/2000,10,20
3,4/30/2002,10,20
3,1/31/2002,10,20
3,10/31/2001,10,20
3,7/31/2001,10,20
3,1/31/2001,10,20
3,10/31/2000,10,20
输出:
Dimension Date Value1 Value2 Sum_Value1
0 1 4/30/2002 10 20 NaN
1 1 1/31/2002 10 20 NaN
2 1 10/31/2001 10 20 30.0
3 1 7/31/2001 10 20 30.0
4 1 4/30/2001 10 20 30.0
5 1 1/31/2001 10 20 30.0
6 1 10/31/2000 10 20 30.0
7 2 4/30/2002 10 20 NaN
8 2 1/31/2002 10 20 NaN
9 2 10/31/2001 10 20 30.0
10 2 7/31/2001 10 20 30.0
11 2 4/30/2001 10 20 30.0
12 2 1/31/2001 10 20 30.0
13 2 10/31/2000 10 20 30.0
目标输出:
Dimension Date Value1 Value2 Sum_Value1
0 1 4/30/2002 10 20 30.0
1 1 1/31/2002 10 20 30.0
2 1 10/31/2001 10 20 30.0
3 1 7/31/2001 10 20 30.0
4 1 4/30/2001 10 20 30.0
5 1 1/31/2001 10 20 NaN
6 1 10/31/2000 10 20 NaN
7 2 4/30/2002 10 20 30.0
8 2 1/31/2002 10 20 30.0
9 2 10/31/2001 10 20 30.0
10 2 7/31/2001 10 20 30.0
11 2 4/30/2001 10 20 30.0
12 2 1/31/2001 10 20 Nan
13 2 10/31/2000 10 20 NaN
最佳答案 您可以通过window-1移动结果以获得左对齐的结果:
df["sum_value1"] = (df.groupby('Dimension').Value1
.apply(lambda x: x.rolling(window=3).sum().shift(-2)))