在 Python Pandas 中查找 ID 的最小值、最大值和平均值
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Find min, max and average of an ID in Python Pandas
提问by Tasos
I have two Dataframes in Python Pandas. Let's say that the first one is the df1. It is not necessary that the id column is ordered.
我在 Python Pandas 中有两个数据框。假设第一个是df1. 没有必要对 id 列进行排序。
id B C
0 1 5 1
1 1 5 1
2 1 6 1
3 1 7 1
4 2 5 1
5 2 6 1
6 2 6 1
7 3 7 1
8 3 7 1
9 4 6 1
10 4 7 1
11 4 7 1
Then the second dataframe df2has a column with the unique values of the id
然后第二个数据帧df2有一个列的唯一值id
id
0 1
1 2
2 3
3 4
I want to calculate the min, max and average of column Bfor each idand add it to the second dataframe. The result would be like this:
我想计算B每个列的最小值、最大值和平均值，id并将其添加到第二个数据帧中。结果是这样的：
id min max avg
0 1 5 7 5.75
1 2 ..
2 3 ..
3 4 ..
In this example, I was able to replicate it by calculating them for each idmanual. It was not a problem since the example has only 4 ids. But my real example has more than 1000 ids. Is there any automatic way to do it?
在这个例子中，我能够通过为每个id手册计算它们来复制它。这不是问题，因为该示例只有 4 个 ID。但是我的真实示例有 1000 多个 ID。有没有自动的方法来做到这一点？
回答by Zero
Use aggfunction on groups
agg对组使用函数
In [96]: df.groupby('id')['B'].agg([pd.np.min, pd.np.max, pd.np.mean])
Out[96]:
amin amax mean
id
1 5 7 5.750000
2 5 6 5.666667
3 7 7 7.000000
4 6 7 6.666667
