【发布时间】：2019-10-29 21:48:18
【问题描述】：
我想对 pandas 数据框的列进行整合。第一列是年龄（时间 - dt），其余列是时间积分。
我尝试使用 scipy 集成函数使用“应用”/“lambda”方法。但做不到。
import pandas as pd
from scipy import integrate
sfr =
Age_Gyr 3254 3269 3291
0 0.500000 5.182340e-08 2.642610e-07 2.783430e-09
1 0.560322 4.084170e-08 1.515610e-07 2.627680e-09
2 0.627922 2.986970e-08 2.819660e-08 2.410660e-09
3 0.703678 2.386120e-08 2.097600e-09 2.555090e-09
4 0.788572 1.793270e-08 5.751970e-11 5.490520e-09
5 0.883709 1.373250e-08 1.517070e-10 6.231230e-09
6 0.990324 1.028010e-10 5.139110e-09 7.419210e-09
7 1.109800 7.512700e-10 4.182470e-08 1.440080e-08
8 1.243690 1.719770e-09 2.239910e-10 4.866400e-08
9 1.393740 2.806130e-08 5.869810e-10 6.121040e-08
10 1.561880 3.359250e-08 1.530720e-08 1.116400e-07
11 1.750320 8.492680e-08 3.197630e-09 1.711650e-07
12 1.961480 1.090190e-07 2.578610e-09 2.090300e-07
13 2.198130 1.490990e-07 1.561680e-10 3.531300e-07
14 2.463320 2.050680e-07 6.861820e-10 3.742560e-07
15 2.760500 2.683970e-07 5.512860e-09 4.297430e-07
16 3.093540 3.093700e-07 1.798130e-08 3.771080e-07
17 3.466760 4.114820e-07 1.491870e-08 4.958250e-07
18 3.885010 4.540180e-07 1.275250e-08 5.664370e-07
19 4.353710 6.332550e-07 9.337140e-08 5.912740e-07
20 4.878970 6.151890e-07 9.788760e-08 5.900450e-07
21 5.467590 7.640760e-07 2.338090e-07 6.881540e-07
22 6.127220 7.573870e-07 3.309460e-07 8.128530e-07
23 6.866440 1.203460e-06 2.738100e-07 1.532900e-06
24 7.694840 1.613990e-06 2.767600e-07 8.485710e-07
25 8.623180 2.058680e-06 4.189610e-07 9.596390e-07
26 9.663520 2.620590e-06 9.887390e-07 2.471610e-06
27 10.829400 3.309770e-06 1.226540e-06 2.801140e-06
28 12.135900 3.977210e-06 5.305930e-06 3.492020e-06
29 13.600000 5.327290e-06 1.012560e-05 4.556700e-06
integral = np.array([])
for col in sfr.columns[1:]:
temp = sfr[sfr.columns[1:]].apply(lambda x: integrate.trapz(x[col],x['Age_Gyr']))
integral = np.append(integral,temp)
print(integral)
KeyError: ('3254', '发生在索引 Age_Gyr')
【问题讨论】：
标签： python-3.x pandas scipy