Python 基于列合并 Pandas 中数据帧的行
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Merge rows of a dataframe in pandas based on a column
提问by user3527975
I am new to pandas. I have a dataframe that looks like this
我是熊猫的新手。我有一个看起来像这样的数据框
sitename name date count
0 chess.com Autobiographer 2012-05-01 2
1 chess.com Autobiographer 2012-05-05 1
2 chess.com Autobiographer 2012-05-15 1
3 chess.com Autobiographer 2012-05-01 1
4 chess.com Autobiographer 2012-05-15 1
5 chess.com Autobiographer 2012-05-01 1
How to merge the rows based on date and sum up the count for the same date. Like in sql
如何根据日期合并行并总结同一日期的计数。就像在 sql 中一样
select sitename, name, date count(*) from table group by date
采纳答案by TimmyCarbone
If you want to keep your sitename and name in your dataframe, you can do :
如果要在数据框中保留站点名称和名称，可以执行以下操作：
df = dataframe.groupby(['date', 'sitename', 'name']).sum()
EDIT : See @DSM's comment to reset the indexes and have a non indexed dataframe.
编辑：请参阅@DSM的评论以重置索引并具有非索引数据框。
回答by 8one6
df = dataframe.groupby('date').sum()
