重新索引Pandas Multiindex

Question

我正在尝试为根文件创建的数据帧创建一个新索引。我在用uproot命令把文件带进来

upfile_muon = uproot.open(file_prefix_muon + '.root')
tree_muon = upfile_muon['ntupler']['tree']
df_muon = tree_muon.pandas.df(['vh_sim_r','vh_sim_phi','vh_sim_z','vh_sim_tp1','vh_sim_tp2',
                         'vh_type','vh_station','vh_ring','vh_sim_theta'], entrystop=args.max_events)

然后创建一个多索引数据帧，其中条目和子条目作为我的两个索引。我想过滤掉所有长度小于等于3的子条目。在创建将数据帧分割成所需数据的向量时，我使用以下命令来实现这一点。你知道吗

a = 0
bad_entries = 0
entries = []
nuindex = []
tru = 0
while(a < args.max_events):
    if(df_muon.loc[(a),:].shape[0] > 3):
        entries.append(a)
        b = 0
        while( b < df_muon.loc[(a),:].shape[0]):
            nuindex.append(tru)
            b = b + 1
        tru = tru + 1
    else:
        bad_entries = bad_entries + 1
    a = a + 1
df_muon = df_muon.loc[pd.IndexSlice[entries,:],:]

所以现在我的数据框是这样的

                  vh_sim_r  vh_sim_phi     vh_sim_z  vh_sim_tp1  vh_sim_tp2  vh_type  vh_station  vh_ring  vh_sim_theta
entry subentry                                                                                                         
0     0         149.724701 -124.728081   793.598755           0           0        3           2        1     10.684152
      1         149.236725 -124.180763   796.001221          -1          -1        3           2        1     10.618716
      2         149.456131 -124.687302   796.001221           0           0        3           2        1     10.633972
      3          92.405533 -126.913628   539.349976           0           0        4           1        1      9.721958
      4         149.345184 -124.332527   839.810669           0           0        1           2        1     10.083608
      5         176.544983 -123.978333   964.500000           0           0        2           3        1     10.372764
      6         194.614502 -123.764595  1054.994995           0           0        2           4        1     10.451831
      7         149.236725 -124.180763   796.001221          -1          -1        3           2        1     10.618716
      8         149.456131 -124.687302   796.001221           0           0        3           2        1     10.633972
      9          92.405533 -126.913628   539.349976           0           0        4           1        1      9.721958
      10        149.345184 -124.332527   839.810669           0           0        1           2        1     10.083608
      11        176.544983 -123.978333   964.500000           0           0        2           3        1     10.372764
      12        194.614502 -123.764595  1054.994995           0           0        2           4        1     10.451831
1     0         265.027252   -3.324370   796.001221           0           0        3           2        1     18.415092
      1         272.908997   -3.531896   839.903625           0           0        1           2        1     18.000479
      2         299.305176   -3.531351   923.885132           0           0        1           3        1     17.950438
      3         312.799255   -3.499015   964.500000           0           0        2           3        1     17.968519
      4         328.321442   -3.530087  1013.620056           0           0        1           4        1     17.947645
      5         181.831726   -1.668625   567.971252           0           0        3           1        1     17.752077
      6         265.027252   -3.324370   796.001221           0           0        3           2        1     18.415092
      7         197.739120   -2.073746   615.796265           0           0        1           1        1     17.802410
      8         272.908997   -3.531896   839.903625           0           0        1           2        1     18.000479
      9         299.305176   -3.531351   923.885132           0           0        1           3        1     17.950438
      10        312.799255   -3.499015   964.500000           0           0        2           3        1     17.968519
      11        328.321442   -3.530087  1013.620056           0           0        1           4        1     17.947645
      12        356.493073   -3.441958  1065.694946           0           0        2           4        2     18.495964
2     0         204.523163 -124.065643   839.835571           0           0        1           2        1     13.686690
      1         135.439163 -122.568153   567.971252           0           0        3           1        1     13.412345
      2         196.380875 -123.940300   796.001221           0           0        3           2        1     13.858652
      3         129.801193 -122.348656   539.349976           0           0        4           1        1     13.531607
      4         224.134796 -124.194283   923.877441           0           0        1           3        1     13.636631
      5         237.166031 -124.181770   964.500000           0           0        2           3        1     13.814683
      6         246.809235 -124.196938  1013.871643           0           0        1           4        1     13.681540
      7         259.389587 -124.164017  1054.994995           0           0        2           4        1     13.813211
      8         204.523163 -124.065643   839.835571           0           0        1           2        1     13.686690
      9         196.380875 -123.940300   796.001221           0           0        3           2        1     13.858652
      10        129.801193 -122.348656   539.349976           0           0        4           1        1     13.531607
      11        224.134796 -124.194283   923.877441           0           0        1           3        1     13.636631
      12        237.166031 -124.181770   964.500000           0           0        2           3        1     13.814683
      13        246.809235 -124.196938  1013.871643           0           0        1           4        1     13.681540
      14        259.389587 -124.164017  1054.994995           0           0        2           4        1     13.813211
3     0         120.722900  -22.053474   615.786621           0           0        1           1        4     11.091969
      1         170.635376  -23.190208   793.598755           0           0        3           2        1     12.134683
      2         110.061127  -21.370941   539.349976           0           0        4           1        1     11.533570
      3         164.784668  -23.263920   814.977478           0           0        1           2        1     11.430829
      4         192.868652  -23.398684   948.691345           0           0        1           3        1     11.491603
      5         199.817978  -23.325649   968.900024           0           0        2           3        1     11.652840
      6         211.474625  -23.265354  1038.803833           0           0        1           4        1     11.506759
      7         216.406830  -23.275047  1059.395020           0           0        2           4        1     11.545199
      8         170.612457  -23.136520   793.598755          -1          -1        3           2        1     12.133101
5     0         179.913177  -14.877813   615.749207           0           0        1           1        1     16.287615
      1         160.188034  -14.731569   565.368774           0           0        3           1        1     15.819215
      2         240.671204  -15.410946   793.598755           0           0        3           2        1     16.870745
      3         166.238678  -14.774992   586.454590           0           0        1           1        1     15.826117
      4         241.036865  -15.400753   815.009399           0           0        1           2        1     16.475443
      5         281.086792  -15.534301   948.707581           0           0        1           3        1     16.503710
      6         288.768768  -15.577776   968.900024           0           0        2           3        1     16.596043
      7         309.145935  -15.533208  1038.588745           0           0        1           4        1     16.576143
      8         312.951233  -15.579374  1059.395020           0           0        2           4        1     16.457436
      9         312.313416  -16.685022  1059.395020          -1          -1        2           4        1     16.425705

现在我的目标是找到一种方法，将entry索引中的5值改为4。我想用一种自动化的方式来实现这个过程，这样我就可以有大量的条目（~20000），我可以让我的过滤器删除不可用的条目，然后它将所有条目按顺序重新编号，从0到最后一个未过滤的条目。我试过各种各样的命令，但都不走运。有没有直接的方法？你知道吗

Answer 1

df_muon = (df_muon
           .reset_index()  # Get the multi-index back as columns
           .replace({'entry': 5}, {'entry': 4})  # Replace 5 in column 'entry' with 4
           .set_index(['entry', 'subentry'])  # Go back to the multi-index
          )