<p>现在它起作用了。
首先使用combine_填充df开口中的间隙</p>
<pre class="lang-py prettyprint-override"><code>import pandas as pd
df = pd.DataFrame({
'country': {0: 'A', 1: 'A', 2: 'A', 3: 'A', 4: 'A', 5: 'A', 6: 'A', 7: 'A', 8: 'A', 9: 'A', 10: 'A', 11: 'A', 12: 'A', 13: 'B', 14: 'B', 15: 'B', 16: 'B', 17: 'B', 18: 'B', 19: 'B', 20: 'B', 21: 'B', 22: 'B'},
'item': {0: 1, 1: 1, 2: 1, 3: 1, 4: 1, 5: 1, 6: 1, 7: 2, 8: 1, 9: 2, 10: 2, 11: 1, 12: 1, 13: 1, 14: 1, 15: 1, 16: 2, 17: 3, 18: 2, 19: 1, 20: 2, 21: 1, 22: 3},
'week': {0: 1, 1: 2, 2: 3, 3: 4, 4: 5, 5: 6, 6: 7, 7: 7, 8: 8, 9: 8, 10: 9, 11: 9, 12: 10, 13: 1, 14: 2, 15: 3, 16: 3, 17: 3, 18: 4, 19: 4, 20: 5, 21: 5, 22: 5},
'stock': {0: 105, 1: 105, 2: 105, 3: 105, 4: 105, 5: 105, 6: 105, 7: 94, 8: 105, 9: 94, 10: 94, 11: 105, 12: 105, 13: 100, 14: 100, 15: 100, 16: 200, 17: 300, 18: 200, 19: 100, 20: 200, 21: 100, 22: 300},
'FCST': {0: 3, 1: 6, 2: 9, 3: 4, 4: 7, 5: 4, 6: 7, 7: 2, 8: 1, 9: -5, 10: 2, 11: 8, 12: 6, 13: 2, 14: 6, 15: 8, 16: 3, 17: 7, 18: 8, 19: 9, 20: 3, 21: 5, 22: 6}
})
</code></pre>
<pre class="lang-py prettyprint-override"><code>df_new = pd.DataFrame(columns=df.columns)
groups = df.groupby(["country", "item"])
df["closing"] = df.stock - groups.FCST.cumsum()
df["opening"] = groups.closing.shift(1)
df["opening"] = df["opening"].combine_first(df.stock)
</code></pre>
<p>产出:</p>
<pre><code> country item week stock FCST closing opening
0 A 1 1 105 3 102 105.0
1 A 1 2 105 6 96 102.0
2 A 1 3 105 9 87 96.0
3 A 1 4 105 4 83 87.0
4 A 1 5 105 7 76 83.0
5 A 1 6 105 4 72 76.0
6 A 1 7 105 7 65 72.0
7 A 2 7 94 2 92 94.0
8 A 1 8 105 1 64 65.0
9 A 2 8 94 -5 97 92.0
10 A 2 9 94 2 95 97.0
11 A 1 9 105 8 56 64.0
12 A 1 10 105 6 50 56.0
13 B 1 1 100 2 98 100.0
14 B 1 2 100 6 92 98.0
15 B 1 3 100 8 84 92.0
16 B 2 3 200 3 197 200.0
17 B 3 3 300 7 293 300.0
18 B 2 4 200 8 189 197.0
19 B 1 4 100 9 75 84.0
20 B 2 5 200 3 186 189.0
21 B 1 5 100 5 70 75.0
22 B 3 5 300 6 287 293.0
</code></pre>