Python 数据透视表转换在pands中生成值错误
我正在从包含Python 数据透视表转换在pands中生成值错误,python,pandas,cursor,pivot,Python,Pandas,Cursor,Pivot,我正在从包含 execution_time, type, status, process, sub_process, value 2018-11-12 16:09:48.179547, backlog, started, p1, s1, 100 2018-11-12 16:09:48.179547, backlog, created, p1, s1, 1005 2018-11-12 16:09:48.179547, backlog, started, p2, s1, 500 2018-11-1
execution_time, type, status, process, sub_process, value
2018-11-12 16:09:48.179547, backlog, started, p1, s1, 100
2018-11-12 16:09:48.179547, backlog, created, p1, s1, 1005
2018-11-12 16:09:48.179547, backlog, started, p2, s1, 500
2018-11-12 16:09:48.179547, V1, created, p1, s1, 10
2018-11-12 16:09:48.179547, V2, created, p1, s1, 15
2018-11-12 16:09:48.179547, backlog, started, p3, s1, 0
2018-11-12 16:09:48.179547, backlog, started, p4, s1, 45
2018-11-12 16:09:48.179547, V1, started, p4, s1, 400
我希望将此数据透视为如下所示:
状态、流程、子流程、积压工作、V1、V2
(积压工作、V1和V2应包含相应的值(如果存在)
这是我的密码。我得到的错误是
pivot_table()为参数“values”获取了多个值
使用(删除pivot\u表中的df
)
或pd.pivot\u表
pd.pivot_table(df,index=['status','process','sub_process'],columns='type',values=['value'], aggfunc = 'sum')
Out[86]:
value
type V1 V2 backlog
status process sub_process
created p1 s1 10.0 15.0 1005.0
started p1 s1 NaN NaN 100.0
p2 s1 NaN NaN 500.0
p3 s1 NaN NaN 0.0
p4 s1 400.0 NaN 45.0
嘿@W-B我删除了df,但我得到的错误是“keyrerror:'value'”@madhuramhat再次检查df.columns的df列,我想你有空白,这就是我修改后的行df=df.pivot_表(index=['status','process','sub process',columns='type',values='value',aggfunc='sum'),这很有趣,我仍然明白“KeyError:'值'”
df.pivot_table(index=['status','process','sub_process'],columns='type',values='value', aggfunc = 'sum')
Out[85]:
type V1 V2 backlog
status process sub_process
created p1 s1 10.0 15.0 1005.0
started p1 s1 NaN NaN 100.0
p2 s1 NaN NaN 500.0
p3 s1 NaN NaN 0.0
p4 s1 400.0 NaN 45.0
pd.pivot_table(df,index=['status','process','sub_process'],columns='type',values=['value'], aggfunc = 'sum')
Out[86]:
value
type V1 V2 backlog
status process sub_process
created p1 s1 10.0 15.0 1005.0
started p1 s1 NaN NaN 100.0
p2 s1 NaN NaN 500.0
p3 s1 NaN NaN 0.0
p4 s1 400.0 NaN 45.0