Question

我正在尝试在“for”循环中使用“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）是否对应于其中一个索引另一个系列，但这样做会引发一个ValueError。这是产生问题的代码行：

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

我尝试使用随机整数或列表更改“in”语句的两侧并且它可以工作，这两个项目也正确构建，但是当它们在语句中耦合时会引发错误。

希望有人能给我一些关于问题所在或者执行相同任务的替代方法的提示。

ICM_items和ICM_tgt_items都是pandas.Series

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，并留意边缘情况（例如track_id对于给定的i呈现为空。）
使用正确的测试数据，这些步骤可以帮助您缩小搜索范围。

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

现在简单地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

ValueError：如果在语句中，Buffer的维度数量错误（预期为1，得到2）

1 个答案: