pandas 从python中的groupby对象中选择特定行
声明：本页面是StackOverFlow热门问题的中英对照翻译，遵循CC BY-SA 4.0协议，如果您需要使用它，必须同样遵循CC BY-SA许可，注明原文地址和作者信息，同时你必须将它归于原作者（不是我）：StackOverFlow
原文地址: http://stackoverflow.com/questions/28175330/
Warning: these are provided under cc-by-sa 4.0 license. You are free to use/share it, But you must attribute it to the original authors (not me):
StackOverFlow
selecting a particular row from groupby object in python
提问by Shiva Prakash
id marks year
1 18 2013
1 25 2012
3 16 2014
2 16 2013
1 19 2013
3 25 2013
2 18 2014
suppose now I group the above on id by python command.
grouped = file.groupby(file.id)
假设现在我通过 python 命令将上述内容分组到 id 上。
分组 = file.groupby(file.id)
I would like to get a new file with only the row in each group with recent year that is highest of all the year in the group.
我想获得一个新文件，其中每个组中只有最近一年中最高的那一行。
Please let me know the command, I am trying with apply but it ll only given the boolean expression. I want the entire row with latest year.
请让我知道命令，我正在尝试使用 apply 但它只会给出布尔表达式。我想要最近一年的整行。
回答by EdChum
I cobbled this together using this: Python : Getting the Row which has the max value in groups using groupby
我用这个拼凑起来：Python : 使用 groupby 获取在组中具有最大值的行
So basically we can groupby the 'id' column, then call transformon the 'year' column and create a boolean index where the year matches the max year value for each 'id':
所以基本上我们可以按 'id' 列分组，然后调用transform'year' 列并创建一个布尔索引，其中年份与每个 'id' 的最大年份值匹配：
In [103]:
df[df.groupby(['id'])['year'].transform(max) == df['year']]
Out[103]:
id marks year
0 1 18 2013
2 3 16 2014
4 1 19 2013
6 2 18 2014
