如何在 dataframe.map() 中使用列表作为索引？

Question

我有一个看起来像这样的 pandas df：

ld_r2_array_df.head()
         SNP_A                  r2_ld_array
0  1:203337500  [1, NONE, NONE, NONE, NONE]
1   20:6730358  [1, NONE, NONE, NONE, NONE]
2   7:50878411  [1, NONE, NONE, NONE, NONE]
3  20:47025897  [1, NONE, NONE, NONE, NONE]
4   18:7553626  [1, NONE, NONE, NONE, NONE]

还有一个字典：

print(dict(list(csnps_indices.items())[0:2]))
{'10:100148542': [4582], '10:10091912': [4527]}

当我运行下面的命令时，

ld_r2_array_df["order"] = ld_r2_array_df.SNP_A.map(csnps_indices)

我收到此错误：

Traceback (most recent call last):
  File "pandas/_libs/hashtable_class_helper.pxi", line 4588, in pandas._libs.hashtable.PyObjectHashTable.map_locations
TypeError: unhashable type: 'list'
Exception ignored in: 'pandas._libs.index.IndexEngine._call_map_locations'

我是一个完整的 python 新手，所以我想知道这里可能是什么问题。我已经尝试将 dict 转换为元组，但随后又收到另一个错误：

TypeError: 'type' object is not subscriptable

如果我应该提供更多信息以重现错误，请告诉我。谢谢！

Answer 1

您的代码似乎对我有用。

输入数据：

>>> df
         SNP_A                  r2_ld_array
0  1:203337500  [1, NONE, NONE, NONE, NONE]
1   20:6730358  [1, NONE, NONE, NONE, NONE]
2   7:50878411  [1, NONE, NONE, NONE, NONE]
3  20:47025897  [1, NONE, NONE, NONE, NONE]
4   18:7553626  [1, NONE, NONE, NONE, NONE]

>>> d
{'1:203337500': [4582], '7:50878411': [4527]}

尝试映射：

df['order'] = df['SNP_A'].map(d)
print(df)

# Output:
         SNP_A                  r2_ld_array   order
0  1:203337500  [1, NONE, NONE, NONE, NONE]  [4582]
1   20:6730358  [1, NONE, NONE, NONE, NONE]     NaN
2   7:50878411  [1, NONE, NONE, NONE, NONE]  [4527]
3  20:47025897  [1, NONE, NONE, NONE, NONE]     NaN
4   18:7553626  [1, NONE, NONE, NONE, NONE]     NaN