Python GroupBy语句不像字符串那样分组
晚上, 我的数据:Python GroupBy语句不像字符串那样分组,python,pandas,group-by,mask,Python,Pandas,Group By,Mask,晚上, 我的数据: display(dfRFQ_Breakdown_By_Done_Traded_Away_Grp.sort_values('security_type1',ascending=True)) state security_type1 count 0 Done CORP 239 4 Tied Done CORP 9 6 Tied Traded Away CORP
display(dfRFQ_Breakdown_By_Done_Traded_Away_Grp.sort_values('security_type1',ascending=True))
state security_type1 count
0 Done CORP 239
4 Tied Done CORP 9
6 Tied Traded Away CORP 7
9 Traded Away CORP 1075
1 Done GOVT 40
5 Tied Done GOVT 2
7 Tied Traded Away GOVT 16
10 Traded Away GOVT 150
2 Done MTGE 4
8 Tied Traded Away MTGE 3
11 Traded Away MTGE 7
3 Done SUPRA 31
12 Traded Away SUPRA 88
我想为每种证券类型1将具有“完成”或“交易结束”状态的所有行组合在一起:
state security_type1 count
Done CORP 248
Traded Away CORP 1082
Done GOVT 42
Traded Away GOVT 166
Done MTGE 4
Traded Away MTGE 10
Done SUPRA 31
Traded Away SUPRA 88
我的代码:
# Updating any Tied Done to Done and Tied Traded Away to Traded Away
mask = (dfRFQ_Breakdown_By_Done_Traded_Away_Grp['state'].str.contains('Tied Done'))
dfRFQ_Breakdown_By_Done_Traded_Away_Grp.loc[mask, 'state'] = 'Done'
mask = (dfRFQ_Breakdown_By_Done_Traded_Away_Grp['state'].str.contains('Tied Traded Away'))
dfRFQ_Breakdown_By_Done_Traded_Away_Grp.loc[mask, 'state'] = 'Traded Away'
display(dfRFQ_Breakdown_By_Done_Traded_Away_Grp.sort_values('security_type1',ascending=True))
更新后的字符串似乎按熊猫分别分组:
state security_type1 count
Done CORP 239
Done CORP 9
Traded Away CORP 7
Traded Away CORP 1075
Done GOVT 40
Done GOVT 2
Traded Away GOVT 16
Traded Away GOVT 150
Done MTGE 4
Traded Away MTGE 3
Traded Away MTGE 7
Done SUPRA 31
Traded Away SUPRA 88
如果熊猫不把已经做过的和被交易过的情况结合在一起,那又有什么意义呢?我是否需要创建数据帧的另一个副本。这几乎就像熊猫在更新之前有一个到旧值的链接 这似乎是可能的,并且:
谢谢@jpp。完美的一起避免这个问题。
res = df.query('(state == "Done") | (state == "TradedAway")')\
.groupby(['state', 'security_type1'], as_index=False)['count'].sum()\
.sort_values(['security_type1', 'state'])
print(res)
state security_type1 count
0 Done CORP 239
4 TradedAway CORP 1075
1 Done GOVT 40
5 TradedAway GOVT 150
2 Done MTGE 4
6 TradedAway MTGE 7
3 Done SUPRA 31
7 TradedAway SUPRA 88