[英]Pandas cumulative diff from groupby
我需要計算從MultiIndex級別開始的差異,以計算從級別開始的衰減。 我的示例輸入和輸出將如下所示:
values
place time
A a 120
b 100
c 90
d 50
B e 11
f 12
g 10
h 9
values
A a NaN
b -20
c -30
d -70
B e Nan
f +1
g -1
h -2
我可以使用grouby來獲取級別中連續單元格之間的差異:
df.groupby(level=0)['values'].diff()
但這不是我想要的!
唉,接受的答案並不是我想要的。 我有一個更好的例子:
arrays = [np.array(['bar', 'bar', 'bar', 'foo', 'foo', 'foo']),
np.array(['one', 'two', 'three', 'one', 'two', 'three'])]
df = pd.DataFrame([1000, 800, 500, 800, 400, 200], index=arrays)
bar one 1000
two 800
three 500
foo one 800
two 400
three 200
expected_result = pd.DataFrame([Nan, -200, -500, Nan, -400, -600], index=arrays)
bar one Nan
two -200
three -500
foo one Nan
two -400
three -600
但是df.groupby(level=0).diff().cumsum()
給出:
pd.DataFrame([Nan, -200, -500, Nan, -900, -1100], index=arrays)
bar one Nan
two -200
three -500
foo one Nan
two -900
three -1100
你在尋找一個cumsum
嗎?
df.groupby(level=0)['values'].diff().cumsum()
你可以得到我想要通過鏈接另一groupby
:
arrays = [np.array(['bar', 'bar', 'bar', 'foo', 'foo', 'foo']),
np.array(['one', 'two', 'three', 'one', 'two', 'three'])]
df = pd.DataFrame([1000, 800, 500, 800, 400, 200], index=arrays)
bar one 1000
two 800
three 500
foo one 800
two 400
three 200
expected_result = pd.DataFrame([Nan, -200, -500, Nan, -400, -600], index=arrays)
df.groupby(level=0).diff().groupby(level=0).cumsum()
bar one Nan
two -200
three -500
foo one Nan
two -400
three -600
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