ValueError:if in statement上的缓冲区维数错误（应为1，得到2）

Question

我试图在“for”循环内使用“if”语句来检查循环中当前项的索引（包含该项的pandas系列的索引）是否与另一个系列的索引之一对应，但这样做会产生一个ValueError。 这一行代码给出了问题：

if(ICM_items[ICM_items['track_id'] == i].index[0] in ICM_tgt_items.index.values.flatten().tolist()):

我试着用随机整数或列表来改变“in”语句的两边，它也能正常工作，而且这两个项的构建是正确的，但是当它们在语句中耦合时会产生一个错误。

希望有人能给我一些提示，告诉我哪里出了问题，或者是执行相同任务的另一种方法。

ICM_项和ICM_tgt_项都是熊猫

下面是控制台错误：

Traceback (most recent call last):
File "/Users/LucaButera/git/rschallenge/similarity_to_recommandable_builder.py", line 27, in <module>
dot[ICM_tgt_items[ICM_items[ICM_items['track_id'] == i].index[0]]] = 0
File "/Users/LucaButera/anaconda/lib/python3.6/site-packages/pandas/core/series.py", line 603, in __getitem__
result = self.index.get_value(self, key)
File "/Users/LucaButera/anaconda/lib/python3.6/site-packages/pandas/indexes/base.py", line 2169, in get_value
tz=getattr(series.dtype, 'tz', None))
File "pandas/index.pyx", line 98, in pandas.index.IndexEngine.get_value (pandas/index.c:3557)
File "pandas/index.pyx", line 106, in pandas.index.IndexEngine.get_value (pandas/index.c:3240)
File "pandas/index.pyx", line 147, in pandas.index.IndexEngine.get_loc (pandas/index.c:4194)
File "pandas/index.pyx", line 280, in pandas.index.IndexEngine._ensure_mapping_populated (pandas/index.c:6150)
File "pandas/src/hashtable_class_helper.pxi", line 446, in pandas.hashtable.Int64HashTable.map_locations (pandas/hashtable.c:9261)
ValueError: Buffer has wrong number of dimensions (expected 1, got 2)
[Finished in 1.26s]

Answer 1

我建议您简化表达式，使用.loc，并注意边缘情况（例如，track_id对于给定的i显示为空）。
有了正确的测试数据，这些步骤将帮助您缩小bug搜索范围。

示例ICM_items数据：

import numpy as np
import pandas as pd

N = 7
max_track_id = 5
idx1 = ['A','B','C']
icm_idx = np.random.choice(idx1, size=N)
icm = {"track_id":np.random.randint(0, max_track_id, size=N)}
ICM_items = pd.DataFrame(icm, index=icm_idx)

ICM_items
   track_id
C         1
A         1
A         2
C         1
B         0
B         0
B         2

示例ICM_tgt_items数据：

idx2 = ['A','B']
icm_tgt_idx = np.random.choice(idx2, size=N)
icm = np.random.random(size=N)
ICM_tgt_items = pd.DataFrame(icm, index=icm_tgt_idx)

          0
B  0.785614
A  0.976523
A  0.856821
B  0.098086
B  0.481140
A  0.686156
A  0.851714

现在简单比较并捕捉潜在的边缘情况：

for i in range(max_track_id):
    mask = ICM_items['track_id'] == i
    try:
        # use .loc for indexing, no need to flatten() or use .values on the right.
        if ICM_items.loc[mask].index[0] in ICM_tgt_items.index:
            print("found")
        else:
            print("not found")
    # catch error if i not found in track_id
    except IndexError as e:           
        print(f"ERROR at i={i}: {e}")

输出：

found
not found
found
ERROR at i=3: index 0 is out of bounds for axis 0 with size 0
ERROR at i=4: index 0 is out of bounds for axis 0 with size 0