pandas -基于条件的重复行 [英] Pandas - Duplicate Row based on condition
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问题描述
如果该行符合条件,我将尝试创建一个重复行.在下表中,我根据groupby创建了一个累积计数,然后对groupby的MAX进行了另一次计算.
I'm trying to create a duplicate row if the row meets a condition. In the table below, I created a cumulative count based on a groupby, then another calculation for the MAX of the groupby.
df['PathID'] = df.groupby(DateCompleted).cumcount() + 1
df['MaxPathID'] = df.groupby(DateCompleted)['PathID'].transform(max)
Date Completed PathID MaxPathID
1/31/17 1 3
1/31/17 2 3
1/31/17 3 3
2/1/17 1 1
2/2/17 1 2
2/2/17 2 2
在这种情况下,我只想复制2/1/17的记录,因为该日期只有一个实例(即MaxPathID == 1).
In this case, I want to duplicate only the record for 2/1/17 since there is only one instance for that date (i.e. where the MaxPathID == 1).
所需的输出:
Date Completed PathID MaxPathID
1/31/17 1 3
1/31/17 2 3
1/31/17 3 3
2/1/17 1 1
2/1/17 1 1
2/2/17 1 2
2/2/17 2 2
提前谢谢!
推荐答案
我认为您需要按 Date Completed
的方式获取 unique
行,然后按
I think you need get unique
rows by Date Completed
and then concat
rows to original:
df1 = df.loc[~df['Date Completed'].duplicated(keep=False), ['Date Completed']]
print (df1)
Date Completed
3 2/1/17
df = pd.concat([df,df1], ignore_index=True).sort_values('Date Completed')
df['PathID'] = df.groupby('Date Completed').cumcount() + 1
df['MaxPathID'] = df.groupby('Date Completed')['PathID'].transform(max)
print (df)
Date Completed PathID MaxPathID
0 1/31/17 1 3
1 1/31/17 2 3
2 1/31/17 3 3
3 2/1/17 1 2
6 2/1/17 2 2
4 2/2/17 1 2
5 2/2/17 2 2
print (df)
Date Completed a b
0 1/31/17 4 5
1 1/31/17 3 5
2 1/31/17 6 3
3 2/1/17 7 9
4 2/2/17 2 0
5 2/2/17 6 7
df1 = df[~df['Date Completed'].duplicated(keep=False)]
#alternative - boolean indexing by numpy array
#df1 = df[~df['Date Completed'].duplicated(keep=False).values]
print (df1)
Date Completed a b
3 2/1/17 7 9
df = pd.concat([df,df1], ignore_index=True).sort_values('Date Completed')
print (df)
Date Completed a b
0 1/31/17 4 5
1 1/31/17 3 5
2 1/31/17 6 3
3 2/1/17 7 9
6 2/1/17 7 9
4 2/2/17 2 0
5 2/2/17 6 7
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