計算第n天，從第一個事件各組內的大熊貓

Question

這是my other question後續問題：

我有以下的數據幀，從我的原始數據幀子集，與列OB， 事件，unixtime和天，我想補充另一列arbday這是自第一事件，對第n天（與第一次爲1天）由OB分組：

import numpy as np 
import datetime as dt 

>>> newdf = pd.DataFrame({'ob': ['a','a','b','b','c', 'd', 'e', 'e', 'e', 'f', 'f', 'f'],'event': [1, 2, 1, 2, 1, 1, 1, 2, 3, 1, 2, 3], 'unixtime': [1346682124716, 1346682188598, 1346745432765, 1347080641650, 1346676710509, 1346702995184, 1346530405978, 1346530421609, 1346530570952, 1346617885925, 1346961625305,1347214217566]},index=[343340, 343341, 343342, 343343, 343344, 343345, 343349, 343350, 343351, 343352,343353,343354]) 
>>> newdf['day'] = newdf['unixtime'].apply(lambda x: dt.datetime.utcfromtimestamp(x/1000).date()) 

     ob event  unixtime   day arbday 
343340 a  1 1346682124716 2012-09-03  1 
343341 a  2 1346682188598 2012-09-03  1 
343342 b  1 1346745432765 2012-09-04  1 
343343 b  2 1347080641650 2012-09-08  5 
343344 c  1 1346676710509 2012-09-03  1 
343345 d  1 1346702995184 2012-09-03  1 
343349 e  1 1346530405978 2012-09-01  1 
343350 e  2 1346530421609 2012-09-01  1 
343351 e  3 1346530570952 2012-09-01  1 
343352 f  1 1346617885925 2012-09-02  1 
343353 f  2 1346961625305 2012-09-06  5 
343354 f  3 1347214217566 2012-09-09  8 

在一個OB，這將工作：

newdf['arbday'] = newdf['day'].map(lambda x: (x-testdf.get_value(newdf[newdf.event == 1].first_valid_index(), 'day')).days+1) 

或

newdf['arbday'] = newdf['day'].map(lambda x: (x-newdf.get_value(int(newdf[newdf.event == 1].index), 'day')).days+1) 

我嘗試下面的代碼和它的工作：

>>> newdf['arbday'] = newdf.groupby('ob')['day'].transform(lambda x: (x-x.min()).apply(lambda y: y.days)+1) 

     event ob  unixtime   day arbday 
343340  1 a 1346682124716 2012-09-03  1 
343341  2 a 1346682188598 2012-09-03  1 
343342  1 b 1346745432765 2012-09-04  1 
343343  2 b 1347080641650 2012-09-08  5 
343344  1 c 1346676710509 2012-09-03  1 
343345  1 d 1346702995184 2012-09-03  1 
343349  1 e 1346530405978 2012-09-01  1 
343350  2 e 1346530421609 2012-09-01  1 
343351  3 e 1346530570952 2012-09-01  1 
343352  1 f 1346617885925 2012-09-02  1 
343353  2 f 1346961625305 2012-09-06  5 
343354  3 f 1347214217566 2012-09-09  8 

但是，這是顯然不是最優雅的做法。另外，爲什麼事件和ob的順序發生了變化？

任何指針將不勝感激。謝謝！

Answer 1

In [46]: firstdays = df.groupby('ob').day.first() 

In [47]: firstdays 
Out[47]: 
ob 
a  2012-09-03 
b  2012-09-04 
c  2012-09-03 
d  2012-09-03 
e  2012-09-01 
f  2012-09-02 
Name: day 

In [48]: df.apply(lambda row: (row['day'] - firstdays[row['ob']]).days + 1, axis=1) 
Out[48]: 
343340 1 
343341 1 
343342 1 
343343 5 
343344 1 
343345 1 
343349 1 
343350 1 
343351 1 
343352 1 
343353 5 
343354 8