Pandas 根据特定的列值对数据框中的行进行分组
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Pandas group the rows in a dataframe based on specific column value
提问by Mahamutha M
I have the data frame as like below one,
我有如下所示的数据框，
Input DataFrame
gw_mac mac
0 ac233fc015f6 dce83f3bc820
1 ac233fc015f6 ac233f264a4c
2 ac233fc015f6 ac233f264a4c
3 ac233fc015f6 dce83f3bc820
4 ac233fc015f6 ac233f264a4c
5 ac233fc015f6 ac233f264a4c
6 ac233fc015f6 dce83f3bc820
7 ac233fc015f6 e464eecba5eb
Now I need to group the dataframe based on the column values "gw_mac" and "mac" and I should get the following three different groups
现在我需要根据列值“gw_mac”和“mac”对数据框进行分组，我应该得到以下三个不同的组
Expected Output
Group1
gw_mac mac
0 ac233fc015f6 dce83f3bc820
3 ac233fc015f6 dce83f3bc820
6 ac233fc015f6 dce83f3bc820
Group2
gw_mac mac
1 ac233fc015f6 ac233f264a4c
2 ac233fc015f6 ac233f264a4c
4 ac233fc015f6 ac233f264a4c
5 ac233fc015f6 ac233f264a4c
Group3
gw_mac mac
7 ac233fc015f6 e464eecba5eb
采纳答案by jezrael
If need different groups by columns loop by groupbyobject:
如果需要按列循环按groupby对象进行不同的组：
for i, g in df.groupby(['gw_mac','mac']):
print (g)
gw_mac mac
1 ac233fc015f6 ac233f264a4c
2 ac233fc015f6 ac233f264a4c
4 ac233fc015f6 ac233f264a4c
5 ac233fc015f6 ac233f264a4c
gw_mac mac
0 ac233fc015f6 dce83f3bc820
3 ac233fc015f6 dce83f3bc820
6 ac233fc015f6 dce83f3bc820
gw_mac mac
7 ac233fc015f6 e464eecba5eb
回答by Vaishali
You can try this to create a dictionary of data frames with unique groups,
您可以尝试使用此方法创建具有唯一组的数据框字典，
df['Group'] = df.groupby(['gw_mac', 'mac']).cumcount()
dfs = dict(tuple(df.groupby('Group')))
You can access a group using,
您可以使用访问组，
dfs[0]
gw_mac mac Group
0 ac233fc015f6 dce83f3bc820 0
1 ac233fc015f6 ac233f264a4c 0
7 ac233fc015f6 e464eecba5eb 0
