我pandas.DataFrame调用了companysubset，如下所示，但实际数据要长得多。
conm fyear dvpayout industry firmycount ipodate
46078 CAESARS ENTERTAINMENT CORP 2003 0.226813 Services 22 19891213.0
46079 CAESARS ENTERTAINMENT CORP 2004 0.226813 Services 22 19891213.0
46080 CAESARS ENTERTAINMENT CORP 2005 0.226813 Services 22 19891213.0
46091 CAESARS ENTERTAINMENT CORP 2016 0.226813 Services 22 19891213.0
114620 CAESARSTONE LTD 2010 0.487543 Manufacturing 10 20120322.0
114621 CAESARSTONE LTD 2011 0.487543 Manufacturing 10 20120322.0
114622 CAESARSTONE LTD 2012 0.487543 Manufacturing 10 20120322.0
114623 CAESARSTONE LTD 2013 0.487543 Manufacturing 10 20120322.0
114624 CAESARSTONE LTD 2014 0.487543 Manufacturing 10 20120322.0
114625 CAESARSTONE LTD 2015 0.487543 Manufacturing 10 20120322.0
114626 CAESARSTONE LTD 2016 0.487543 Manufacturing 10 20120322.0
132524 CAFEPRESS INC 2010 0.000000 Retail Trade 7 20120329.0
132525 CAFEPRESS INC 2011 0.000000 Retail Trade 7 20120329.0
132526 CAFEPRESS INC 2012 -0.000000 Retail Trade 7 20120329.0
132527 CAFEPRESS INC 2013 -0.000000 Retail Trade 7 20120329.0
132528 CAFEPRESS INC 2014 -0.000000 Retail Trade 7 20120329.0
132529 CAFEPRESS INC 2015 -0.000000 Retail Trade 7 20120329.0
132530 CAFEPRESS INC 2016 -0.000000 Retail Trade 7 20120329.0
120049 CAI INTERNATIONAL INC 2005 0.000000 Services 12 20070516.0
120050 CAI INTERNATIONAL INC 2006 0.000000 Services 12 20070516.0
3896 CALAMP CORP 1999 -0.000000 Manufacturing 23 NaN
3897 CALAMP CORP 2000 0.000000 Manufacturing 23 NaN
3898 CALAMP CORP 2001 0.000000 Manufacturing 23 NaN
3899 CALAMP CORP 2002 0.000000 Manufacturing 23 NaN
21120 CALATLANTIC GROUP INC 1995 -0.133648 Construction 22 NaN
21121 CALATLANTIC GROUP INC 1996 -0.133648 Construction 22 NaN
21122 CALATLANTIC GROUP INC 1997 -0.133648 Construction 22 NaN
21123 CALATLANTIC GROUP INC 1998 -0.133648 Construction 22 NaN
21124 CALATLANTIC GROUP INC 1999 -0.133648 Construction 22 NaN
21125 CALATLANTIC GROUP INC 2000 -0.133648 Construction 22 NaN
21126 CALATLANTIC GROUP INC 2001 -0.133648 Construction 22 NaN
21127 CALATLANTIC GROUP INC 2002 -0.133648 Construction 22 NaN
21128 CALATLANTIC GROUP INC 2003 -0.133648 Construction 22 NaN
1）我想按行业计算公司dvpayout的四分位数，并添加名为dv的列，并指出它位于Q1，Q2，{{1 }或Q3。
我想出了这段代码，但它不起作用。
Q4 2）如果有pd.cut(companysubset['dvpayout'].mean(), bins=[0,25,75,100], labels=False)
，我想添加名为age的列。该值将是一年中最大的ipodate。 （例如fyear - ipodate代表2016 - 1989）
我想看到的结果数据框如下所示。
CAESARS ENTERTAINMENT COR提前致谢!!!!
答案 0 :(得分：0)
可以使用以下内容生成年龄列：
df.set_index(['conm'], inplace=True)
df['age'] = df.groupby(level=0).apply(
lambda x: max(x.fyear) - round(x.ipodate.iloc[0]/10000-0.5))
df = pd.read_fwf(StringIO(
u"""
ID conm fyear ipodate
46078 CAESARS ENTERTAINMENT 2003 19891213.0
46079 CAESARS ENTERTAINMENT 2004 19891213.0
46080 CAESARS ENTERTAINMENT 2005 19891213.0
46091 CAESARS ENTERTAINMENT 2016 19891213.0
114620 CAESARSTONE LTD 2010 20120322.0
114621 CAESARSTONE LTD 2011 20120322.0
114622 CAESARSTONE LTD 2012 20120322.0
114623 CAESARSTONE LTD 2013 20120322.0
114624 CAESARSTONE LTD 2014 20120322.0
114625 CAESARSTONE LTD 2015 20120322.0
114626 CAESARSTONE LTD 2016 20120322.0
132524 CAFEPRESS INC 2010 20120329.0
132525 CAFEPRESS INC 2011 20120329.0
132526 CAFEPRESS INC 2012 20120329.0
132527 CAFEPRESS INC 2013 20120329.0
132528 CAFEPRESS INC 2014 20120329.0
132529 CAFEPRESS INC 2015 20120329.0
132530 CAFEPRESS INC 2016 20120329.0
120049 CAI INTERNATIONAL INC 2005 20070516.0
120050 CAI INTERNATIONAL INC 2006 20070516.0
3897 CALAMP CORP 2000 NaN
3898 CALAMP CORP 2001 NaN
3896 CALAMP CORP 1999 NaN
3899 CALAMP CORP 2002 NaN
21120 CALATLANTIC GROUP INC 1995 NaN
21121 CALATLANTIC GROUP INC 1996 NaN
21122 CALATLANTIC GROUP INC 1997 NaN
21123 CALATLANTIC GROUP INC 1998 NaN
21124 CALATLANTIC GROUP INC 1999 NaN
21125 CALATLANTIC GROUP INC 2000 NaN
21126 CALATLANTIC GROUP INC 2001 NaN
21127 CALATLANTIC GROUP INC 2002 NaN
21128 CALATLANTIC GROUP INC 2003 NaN"""),
header=1)
df.set_index(['conm'], inplace=True)
df['age'] = df.groupby(level=0).apply(
lambda x: max(x.fyear) - round(x.ipodate.iloc[0]/10000-0.5))
print(df)
ID fyear ipodate age
conm
CAESARS ENTERTAINMENT 46078 2003 19891213.0 27.0
CAESARS ENTERTAINMENT 46079 2004 19891213.0 27.0
CAESARS ENTERTAINMENT 46080 2005 19891213.0 27.0
CAESARS ENTERTAINMENT 46091 2016 19891213.0 27.0
CAESARSTONE LTD 114620 2010 20120322.0 4.0
CAESARSTONE LTD 114621 2011 20120322.0 4.0
CAESARSTONE LTD 114622 2012 20120322.0 4.0
CAESARSTONE LTD 114623 2013 20120322.0 4.0
CAESARSTONE LTD 114624 2014 20120322.0 4.0
CAESARSTONE LTD 114625 2015 20120322.0 4.0
CAESARSTONE LTD 114626 2016 20120322.0 4.0
CAFEPRESS INC 132524 2010 20120329.0 4.0
CAFEPRESS INC 132525 2011 20120329.0 4.0
CAFEPRESS INC 132526 2012 20120329.0 4.0
CAFEPRESS INC 132527 2013 20120329.0 4.0
CAFEPRESS INC 132528 2014 20120329.0 4.0
CAFEPRESS INC 132529 2015 20120329.0 4.0
CAFEPRESS INC 132530 2016 20120329.0 4.0
CAI INTERNATIONAL INC 120049 2005 20070516.0 -1.0
CAI INTERNATIONAL INC 120050 2006 20070516.0 -1.0
CALAMP CORP 3897 2000 NaN NaN
CALAMP CORP 3898 2001 NaN NaN
CALAMP CORP 3896 1999 NaN NaN
CALAMP CORP 3899 2002 NaN NaN
CALATLANTIC GROUP INC 21120 1995 NaN NaN
CALATLANTIC GROUP INC 21121 1996 NaN NaN
CALATLANTIC GROUP INC 21122 1997 NaN NaN
CALATLANTIC GROUP INC 21123 1998 NaN NaN
CALATLANTIC GROUP INC 21124 1999 NaN NaN
CALATLANTIC GROUP INC 21125 2000 NaN NaN
CALATLANTIC GROUP INC 21126 2001 NaN NaN
CALATLANTIC GROUP INC 21127 2002 NaN NaN
CALATLANTIC GROUP INC 21128 2003 NaN NaN