问题描述
您好，我正在尝试使用Pandas滚动功能来计算下表中的滚动差异.我正在尝试在每月可用项目"列中生成值，但没有得到任何结果.请帮忙！
Hello I am trying to use Pandas rolling function to calculate a rolling difference on the table below. I am trying to produce the values in the Monthly available items column and not getting anywhere. Please help!
Item Adds Subtracts Month Monthly Available items
A 71 30 Jan 41
B 19 7 Jan 12
C 68 30 Jan 38
D 34 19 Jan 15
E 180 91 Jan 89
C 58 34 Feb 62
E 222 129 Feb 182
D 26 21 Feb 20
B 65 26 Feb 51
A 62 58 Feb 45
到目前为止的Python代码:
Python code so far:
rolling_triggers ['Adds'].rolling(window = 2).apply(lambda x:x [1]-x [0])
rolling_triggers['Adds'].rolling(window = 2).apply(lambda x: x[1] - x[0])
推荐答案
如果我正确理解了您的代码和注释，这将满足您的要求:
If I'm understanding your code and comments correctly, this will do what you want:
months = ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun', 'Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec']
df['Month'] = pd.Categorical(df['Month'], categories = months)
df = df.sort_values(['Item', 'Month'])
df['Net_Items'] = df['Adds'] - df['Subtracts']
df['Monthly_Available_Items'] = df.groupby('Item')['Net_Items'].cumsum()
df = df.reset_index(drop = True)
它将返回:
Item Adds Subtracts Month Net_Items Monthly_Available_Items
0 A 71 30 Jan 41 41
1 A 62 58 Feb 4 45
2 B 19 7 Jan 12 12
3 B 65 26 Feb 39 51
4 C 68 30 Jan 38 38
5 C 58 34 Feb 24 62
6 D 34 19 Jan 15 15
7 D 26 21 Feb 5 20
8 E 180 91 Jan 89 89
9 E 222 129 Feb 93 182
首先，将月份列转换为类别(因为按字母顺序，12月在1月之前，依此类推).接下来，将Net_Items计算为Adds和Subtracts之间的差.最后，计算每个产品的累计总和.
First, convert the month column to a Categorical (because alphabetically, December is before January, etc). Next, calculate Net_Items as the difference between Adds and Subtracts. Finally calculate a cumulative sum for each of the products.
假设一月是第一个月，则直觉是添加了71个Item A并删除了30个，总共31个.接下来的一个月，添加了62个并删除了58个，因此前一个月的净额41中增加了4，而总运转额为45.
Assuming January is the first month, the intuition is that there were 71 of Item A added and 30 removed for a net total of 31. In the next month, 62 were added and 58 were removed, so the net total of 4 is added to the prior month's net total of 41 for a running total of 45.
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