I want to split the following dataframe based on column ZZ
我想基于ZZ列拆分以下数据帧
df =
N0_YLDF ZZ MAT
0 6.286333 2 11.669069
1 6.317000 6 11.669069
2 6.324889 6 11.516454
3 6.320667 5 11.516454
4 6.325556 5 11.516454
5 6.359000 6 11.516454
6 6.359000 6 11.516454
7 6.361111 7 11.516454
8 6.360778 7 11.516454
9 6.361111 6 11.516454
As output, I want a new dataframe with the 'N0_YLDF' column split into 4, one new column for each unique value of ZZ. How do I go about this? I can do groupby, but do not know what to do with the grouped object.
作为输出,我想要一个新的数据帧,其中'N0_YLDF'列分为4个,每个ZZ的唯一值一个新列。我该怎么做?我可以做groupby,但不知道如何处理分组对象。
3 个解决方案
#1
55
gb = df.groupby('ZZ')
[gb.get_group(x) for x in gb.groups]
#2
2
In R there is a dataframe method called split. This is for all the R users out there:
在R中有一个名为split的数据帧方法。这适用于所有R用户:
def split(df, group):
gb = df.groupby(group)
return [gb.get_group(x) for x in gb.groups]
#3
2
There is another alternative as the groupby returns a generator we can simply use a list-comprehension to retrieve the 2nd value (the frame).
还有另一种选择,因为groupby返回一个生成器,我们可以简单地使用list-comprehension来检索第二个值(帧)。
df = [x for _, x in df.groupby('ZZ')]
#1
55
gb = df.groupby('ZZ')
[gb.get_group(x) for x in gb.groups]
#2
2
In R there is a dataframe method called split. This is for all the R users out there:
在R中有一个名为split的数据帧方法。这适用于所有R用户:
def split(df, group):
gb = df.groupby(group)
return [gb.get_group(x) for x in gb.groups]
#3
2
There is another alternative as the groupby returns a generator we can simply use a list-comprehension to retrieve the 2nd value (the frame).
还有另一种选择,因为groupby返回一个生成器,我们可以简单地使用list-comprehension来检索第二个值(帧)。
df = [x for _, x in df.groupby('ZZ')]