Python Pandas Dataframe 按组中的最大值选择行
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Python Pandas Dataframe select row by max value in group
提问by user636322
I have a dataframe which was created via a df.pivot:
我有一个通过 df.pivot 创建的数据框：
type start end
F_Type to_date
A 20150908143000 345 316
B 20150908140300 NaN 480
20150908140600 NaN 120
20150908143000 10743 8803
C 20150908140100 NaN 1715
20150908140200 NaN 1062
20150908141000 NaN 145
20150908141500 418 NaN
20150908141800 NaN 450
20150908142900 1973 1499
20150908143000 19522 16659
D 20150908143000 433 65
E 20150908143000 7290 7375
F 20150908143000 0 0
G 20150908143000 1796 340
I would like to filter and return a single row for each 'F_TYPE' only returning the row with the Maximum 'to_date'. I would like to return the following dataframe:
我想为每个“F_TYPE”过滤并返回一行，只返回最大“to_date”的行。我想返回以下数据框：
type start end
F_Type to_date
A 20150908143000 345 316
B 20150908143000 10743 8803
C 20150908143000 19522 16659
D 20150908143000 433 65
E 20150908143000 7290 7375
F 20150908143000 0 0
G 20150908143000 1796 340
Thanks..
谢谢..
采纳答案by unutbu
A standard approach is to use groupby(keys)[column].idxmax().
However, to select the desired rows using idxmaxyou need idxmaxto return unique index values. One way to obtain a unique index is to call reset_index.
标准方法是使用groupby(keys)[column].idxmax(). 但是，要使用idxmax您选择所需的行，您需要idxmax返回唯一的索引值。获取唯一索引的一种方法是调用reset_index.
Once you obtain the index values from groupby(keys)[column].idxmax()you can then select the entire row using df.loc:
从您获得索引值后，groupby(keys)[column].idxmax()您可以使用df.loc以下命令选择整行：
In [20]: df.loc[df.reset_index().groupby(['F_Type'])['to_date'].idxmax()]
Out[20]:
start end
F_Type to_date
A 20150908143000 345 316
B 20150908143000 10743 8803
C 20150908143000 19522 16659
D 20150908143000 433 65
E 20150908143000 7290 7375
F 20150908143000 0 0
G 20150908143000 1796 340
Note: idxmaxreturns index labels, not necessarily ordinals. After using reset_indexthe index labels happen to also be ordinals, but since idxmaxis returning labels (not ordinals) it is better to alwaysuse idxmaxin conjunction with df.loc, not df.iloc(as I originally did in this post.)
注意：idxmax返回索引标签，不一定是序数。使用后reset_index的指数标签碰巧也是序，但由于idxmax正在恢复标签（不是序号），最好是始终使用idxmax与配合df.loc，而不是df.iloc（因为我原来在这个岗位做。）
