How to use a list as index in dataframe.map()?-CodePudding

I have a pandas df which looks like this:

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]

And a dict:

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

When I run the command below,

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

I receive this error:

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'

I am a complete python newbie, so I was wondering what might be the issue here. I already tried converting the dict to tuple, but then I received another error:

TypeError: 'type' object is not subscriptable

Please let me know if I should provide further info for reproduction of the error. Thanks!

CodePudding user response：

Your code seems to work for me.

Input data:

>>> 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]}

Try to map:

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