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Pandas:有条件的 2 列的累积和

[英]Pandas: Cumulative sum from 2 columns with conditions

假设我有两个农场,A 和 B。每周那里都有不同的动物。 我怎样才能获得每个农场当前的动物的累积数量?

+---+-----+--------+-----+--------+
|   |  A  | Farm_A |  B  | Farm_B |
+---+-----+--------+-----+--------+
| 0 | dog |   1    | cat |   1    |
| 1 | cat |   0    | dog |   1    |
| 2 | cat |   0    | dog |   1    |
| 3 | cat |   1    | dog |   0    |
| 4 | dog |   1    | dog |   1    |
| 5 | dog |   0    | dog |   0    |
| 6 | dog |   1    | cat |   1    |
+---+-----+--------+-----+--------+

使用 groupby 我可以从每个农场获得 cumsum:

df['A cumsum Farm_A'] = df.groupby(['A'])['Farm_A'].cumsum()
df['B cumsum Farm_B'] = df.groupby(['B'])['Farm_B'].cumsum()

+---+-----+--------+-----+--------+-----------------+-----------------+
|   |  A  | Farm_A |  B  | Farm_B | A cumsum Farm_A | B cumsum Farm_B |
+---+-----+--------+-----+--------+-----------------+-----------------+
| 0 | dog |   1    | cat |   1    |        1        |        1        |
| 1 | cat |   0    | dog |   1    |        0        |        1        |
| 2 | cat |   0    | dog |   1    |        0        |        2        |
| 3 | cat |   1    | dog |   0    |        1        |        2        |
| 4 | dog |   1    | dog |   1    |        2        |        3        |
| 5 | dog |   0    | dog |   0    |        2        |        3        |
| 6 | dog |   1    | cat |   1    |        3        |        2        |
+---+-----+--------+-----+--------+-----------------+-----------------+

我的问题是,我怎样才能从农场 A 和 B 中获得每行动物的累积总和?

例如第 3 行:农场 A 的动物是猫,那么我想要第 0、1、2、3 行中来自农场 A 和 B 的猫的总和 = 2 只猫。

再次在第 3 行,农场 B 的动物是狗,然后我想要第 0、1、2、3 行中两个农场的狗总数 = 3

这就是我想要实现的目标:

+---+-----+--------+-----+--------+-----------------+-----------------+-----------------+-----------------+
|   |  A  | Farm_A |  B  | Farm_B | A cumsum Farm_A | B cumsum Farm_B | A at both farms | B at both farms |
+---+-----+--------+-----+--------+-----------------+-----------------+-----------------+-----------------+
| 0 | dog |   1    | cat |   1    |        1        |        1        |        1        |        1        |
| 1 | cat |   0    | dog |   1    |        0        |        1        |        1        |        2        |
| 2 | cat |   0    | dog |   1    |        0        |        2        |        1        |        3        |
| 3 | cat |   1    | dog |   0    |        1        |        2        |        2        |        3        |
| 4 | dog |   1    | dog |   1    |        2        |        3        |        4        |        5        |
| 5 | dog |   0    | dog |   0    |        2        |        3        |        5        |        5        |
| 6 | dog |   1    | cat |   1    |        3        |        2        |        6        |        3        |
+---+-----+--------+-----+--------+-----------------+-----------------+-----------------+-----------------+

可以使用假人创建最后两列。 这使您可以跨农场为每种动物类型创建一个cumsum ,然后您可以lookup它以获得每行的适当值。

import pandas as pd

res = pd.get_dummies(df, columns=['A', 'B'])
# Animals only count if dummy & exists, so need to multiply.
res = pd.concat([res.filter(like='A_').multiply(res.Farm_A, axis=0),
                 res.filter(like='B_').multiply(res.Farm_B, axis=0)],
                axis=1)
# Cumsum per animal
res = res.groupby(res.columns.str.split('_').str[1], axis=1).apply(lambda x: x.sum(1).cumsum())
#   cat  dog
#0    1    1
#1    1    2
#2    1    3
#3    2    3
#4    2    5
#5    2    5
#6    3    6

# Lookup
df['A at both'] = res.lookup(df.index, df.A)
df['B at both'] = res.lookup(df.index, df.B)

Output

     A  Farm_A    B  Farm_B  A at both  B at both
0  dog       1  cat       1          1          1
1  cat       0  dog       1          1          2
2  cat       0  dog       1          1          3
3  cat       1  dog       0          2          3
4  dog       1  dog       1          5          5
5  dog       0  dog       0          5          5
6  dog       1  cat       1          6          3

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