Pandas - 基于条件的重复行
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Pandas - Duplicate Row based on condition
提问by Walt Reed
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.
如果行满足条件，我正在尝试创建一个重复的行。在下表中，我根据 groupby 创建了一个累积计数，然后对 groupby 的 MAX 进行了另一个计算。
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
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).
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）。
Desired Output:
期望输出：
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
Thanks in advance!
提前致谢！
采纳答案by jezrael
I think you need get uniquerows by Date Completedand then concatrows to original:
我认为您需要先获取unique行Date Completed，然后再concat获取原始行：
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
EDIT:
编辑：
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
回答by piRSquared
A creative numpyapproach using duplicated+ repeat
numpy使用duplicated+的创造性方法repeat
dc = df['Date Completed']
rg = np.arange(len(dc)).repeat((~dc.duplicated(keep=False).values) + 1)
df.iloc[rg]
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 1
3 2/1/17 1 1
4 2/2/17 1 2
5 2/2/17 2 2
