Trying to match a dictionary item with a string value from another column. sample data:
df = A B
0 'a' {'a': '2', 'b': '5'}
1 'c' {'a': '2', 'b': '16', 'c': '32'}
2 'a' {'a': '6', 'd': '23'}
3 'd' {'b': '4', 'd': '76'}
I'm trying to get the following out:
Df = A B
0 'a' {'a': '2'}
1 'c' {'c': '32'}
2 'a' {'a': '6'}
3 'd' {'d': '76'}
I got this far not inside a dataframe:
d = {k: v for k, v in my_dict.items() if k == 'a'}
for a single line, but I couldn't get this to work and to be fair, I didn't expect it to work directly, but was hoping i was close:
Test_df['B'] = {k: v for k, v in test_df['B'].items() if k == test_df['A']}
I get the following error:
ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().
What do I need to do to get this to work, or is there a better more efficient way?
You can use a list comprehension with zip:
df['B'] = [{x: d[x]} for x, d in zip(df['A'], df['B'])]
Output:
A B
0 a {'a': '2'}
1 c {'c': '32'}
2 a {'a': '6'}
3 d {'d': '76'}