複数のキーで外部結合を行う場合、numpy.lib.recfunctionsのjoin_by関数に問題があるようです。matplotlib.mlab関数は正しく機能します。再関数バージョンは、いくつかのキーを混合/一致しているようです（私は2つのキーを持っていました：001258と001670、再機能は001258と001670に加えてキー001270と001658を生成しました）。誰かがこの問題に遭遇しましたか？
次の2つのテキストファイルtest.csvとtest2.csvがあります。test.csv：
gvkey,fyr,ogpoilq,datadate,cusip
001258,12,,03/31/2002,13916P209
001258,12,,06/30/2002,13916P209
001258,12,,09/30/2002,13916P209
001258,12,31.0000,12/31/2002,13916P209
001678,12,74968.0000,12/31/2003,037411105
001678,12,,03/31/2004,037411105
001678,12,,06/30/2004,037411105
001678,12,,09/30/2004,037411105
001678,12,84736.0000,12/31/2004,037411105
001678,12,,03/31/2005,037411105
001678,12,,06/30/2005,037411105
001678,12,,09/30/2005,037411105
001678,12,85434.0000,12/31/2005,037411105
001678,12,,03/31/2006,037411105
001678,12,,06/30/2006,037411105
001678,12,,09/30/2006,037411105
001678,12,81971.0000,12/31/2006,037411105
test2.csv：
gvkey,datadate,fyearq,fqtr,ciderglq,cisecglq
001258,12/31/2001,2001,4,,
001258,03/31/2002,2002,1,,
001258,06/30/2002,2002,2,,
001258,09/30/2002,2002,3,,
001258,12/31/2002,2002,4,,
001258,03/31/2003,2003,1,,
001258,06/30/2003,2003,2,,
001678,03/31/2004,2004,1,,
001678,06/30/2004,2004,2,,
001678,09/30/2004,2004,3,,
001678,12/31/2004,2004,4,,
001678,03/31/2005,2005,1,-136.9970,0.0000
001678,06/30/2005,2005,2,-7.8000,0.0000
001678,09/30/2005,2005,3,-164.6470,0.0000
001678,12/31/2005,2005,4,73.3180,0.0000
001678,03/31/2006,2006,1,71.6100,0.0000
001678,06/30/2006,2006,2,5.5850,0.0000
次のコードは、正しいマージテーブルと正しくないマージテーブルを生成します。
import datetime
import numpy as np
import numpy.lib.recfunctions as rf
import matplotlib.mlab as ml
date_converter = lambda x: datetime.date(int(x[-4:]), int(x[:2]), int(x[3:5]))
prod_df = np.genfromtxt("../data/test.csv", filling_values=np.nan, converters={3:date_converter}, dtype="S10, f8, O4", names="gvkey, prod, date", delimiter=",", usecols=(0,2,3), skip_header=1)
hedge_df = np.genfromtxt("../data/test2.csv", filling_values=np.nan, converters={1:date_converter}, dtype="S10, O4, f8", names="gvkey, date, hedgepnl", delimiter=",", usecols=(0,1,4), skip_header=1)
correct_outer_merge = ml.rec_join(["gvkey", "date"], prod_df, hedge_df, "outer")
incorrect_outer_merge = rf.rec_join(["gvkey", "date"], prod_df, hedge_df, "outer")