我有以下数据框:
time id type
2012-12-19 1 abcF1
2013-11-02 1 xF1yz
2012-12-19 1 abcF1
2012-12-18 1 abcF1
2013-11-02 1 xF1yz
2006-07-07 5 F5spo
2006-07-06 5 F5spo
2005-07-07 5 F5abc
对于给定的 ID，我需要找到最大日期。
对于那个最大日期，我需要检查类型。
如果类型与最大日期的类型不同，我必须删除给定 ID 的每一行。
目标数据框示例:
time id type
<deleted because for id 1 the date is not the max value and the type differs from the type of the max date for id 1>
2013-11-02 1 xF1yz
<deleted because for id 1 the date is not the max value and the type differs from the type of the max date for id 1>
<deleted because for id 1 the date is not the max value and the type differs from the type of the max date for id 1>
2013-11-02 1 xF1yz
2006-07-07 5 F5spo
2006-07-06 5 F5spo //kept because although the date is not max, it has the same type as the row with the max date for id 5
<deleted because for id 5 the date is not the max value and the type differs from the type of the max date for id 5>
我怎样才能做到这一点？ 我是 pandas 的新手，正在尝试学习使用该库的正确方法。
请您参考如下方法:
使用DataFrameGroupBy.idxmax对于获取最大值的索引，仅过滤列 id 和 type 以及 DataFrame.merge :
df = df.merge(df.loc[df.groupby('id')['time'].idxmax(), ['id','type']])
print (df)
time id type
0 2013-11-02 1 xF1yz
1 2013-11-02 1 xF1yz
2 2006-07-07 5 F5spo
3 2006-07-06 5 F5spo
或者使用DataFrame.sort_values与 DataFrame.drop_duplicates :
df = df.merge(df.sort_values('time').drop_duplicates('id', keep='last')[["id", "type"]])
