英文:
Pandas multiindex and constraint returns unalignable boolean series
问题
要使用pandas的多重索引并根据次要索引和单列值的约束进行排序。以下是您要求的翻译：
# 选择特定Frame_ID范围内，且Lane_ID等于特定值的数据
idx = pd.IndexSlice
nl_df = trajec.loc[idx[:, 200:300, :], 'Lane_ID'] == 2
上述代码将帮助您根据Frame_ID和Lane_ID的条件选择数据，并存储在nl_df中以进行进一步分析。
英文:
Working with pandas multiindex and want to sort by secondary index and a constraint on a single column value.
Local_X Local_Y v_Length v_Width v_Class v_Vel v_Acc Lane_ID Preceding Following Space_Headway Time_Headway ewm_y ewm_x ewm_v ewm_a
Vehicle_ID Frame_ID
1 200 17.070 233.130 14.3 6.4 2 14.51 0.00 2 0 11 0.00 0.00 230.228002 17.035639 14.505089 0.463977
201 17.087 234.581 14.3 6.4 2 14.51 0.00 2 0 11 0.00 0.00 231.679002 17.052759 14.505982 0.441342
202 17.104 236.032 14.3 6.4 2 14.51 0.00 2 0 11 0.00 0.00 233.130001 17.069839 14.505803 0.419812
203 17.121 237.482 14.3 6.4 2 14.51 0.00 2 0 11 0.00 0.00 234.580667 17.086893 14.505657 0.399332
204 17.138 238.933 14.3 6.4 2 14.51 0.00 2 0 11 0.00 0.00 236.031445 17.103929 14.506447 0.379851
... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...
90 296 32.932 69.219 13.4 5.3 2 8.87 -0.85 3 86 0 58.82 6.63 67.578847 32.931133 8.951475 -0.178712
297 32.933 70.093 13.4 5.3 2 8.85 0.35 3 86 0 58.95 6.66 68.426700 32.931763 8.910204 -0.094582
298 32.930 70.970 13.4 5.3 2 8.97 1.88 3 86 0 59.07 6.59 69.281051 32.931170 8.897905 0.152664
299 32.930 71.863 13.4 5.3 2 9.26 3.86 3 86 0 59.18 6.39 70.146146 32.930778 8.949272 0.514508
300 32.945 72.801 13.4 5.3 2 9.67 4.80 3 86 0 59.22 6.12 71.034139 32.935535 9.091710 0.885495
I want to be able to sort out slices of Frame_ID that belong between values and where Lane_ID == cerrtain value.
idx = pd.IndexSlice
nl_df = trajec.loc[idx[:,200:300], :]
This above works to get the multiindex frame where Frame_ID fits certain values but cannot add in the lane_id consideration.
trajec.loc[idx[:,200:300], 'Lane_ID'] == 2
returns the boolean series but I want the entire dataframe for these conditions to be able to perform further analysis. I cannot however combine the 2 like with a normal dataframe and .loc for some reason.
I can perform the action in 2 lines by combining the 2 commands above but there probably is some way to solve with 1 line. I just can't figure it out.
答案1
得分: 0
这一行代码的翻译如下：
df.loc[idx[df.loc[idx[:,:], 'Lane_ID'] == 2,200:300],:]
英文:
Don't know if I understood you correctly, maybe this line solves the problem?
df.loc[idx[df.loc[idx[:,:], 'Lane_ID'] == 2,200:300],:]
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