Python dictionary comprehension with Pandas

Question

I am trying to create a dictionary from two columns of a DataFrame (df)

mydict={x :y for x in df['Names'] for y in df['Births']}

But all of the values are the same(the last value in the column)!

{'Bob': 973, 'Jessica': 973, 'John': 973, 'Mary': 973, 'Mel': 973}

I checked the column and it has many other values, what am I doing wrong?

Check `df[['Names', 'Births']].set_index('Names').to_dict()['Births']`. — Psidom, Dec 02 '16 at 04:06
Because dictionary keys can only store one value, and you are setting each key with each value, so it store the last one it was set with. — juanpa.arrivillaga, Dec 02 '16 at 04:09
Thanks for the help but I know this solution I was looking for a way to do it using the comprehension — AboJoe, Dec 02 '16 at 13:25

score 2 · Accepted Answer · answered Dec 02 '16 at 04:25

I think Abdou hit the nail on the head with dict(zip(dff['Names'], dff['Births'])), but if you want to do it with a dict comprehension you can do this:

    In [1]: import pandas as pd

    In [2]: df = pd.DataFrame(
       ...: [{'Births': 971, 'Names': 'Bob'},
       ...:  {'Births': 972, 'Names': 'Jessica'},
       ...:  {'Births': 973, 'Names': 'John'},
       ...:  {'Births': 974, 'Names': 'Mary'},
       ...:  {'Births': 975, 'Names': 'Mel'}])

    In [3]: {d['Names']: d['Births'] for d in df.to_dict(orient='records')}
    Out[3]: {'Bob': 971, 'Jessica': 972, 'John': 973, 'Mary': 974, 'Mel': 975}

score 0 · Answer 2 · answered Dec 27 '22 at 17:21

0

try my_dict = {row.Names:row.Births for (index,row) in df.iterows()}

answered Dec 27 '22 at 17:21

Abi Vernekar

1

1

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Python dictionary comprehension with Pandas

2 Answers2