Good morning chaps,
Any pythonic way to explode a dataframe column into multiple columns with boolean flags, based on some condition (str.contains in this case)?
Let's say I have this:
Position Letter
1 a
2 b
3 c
4 b
5 b
And I'd like to achieve this:
Position Letter is_a is_b is_C
1 a TRUE FALSE FALSE
2 b FALSE TRUE FALSE
3 c FALSE FALSE TRUE
4 b FALSE TRUE FALSE
5 b FALSE TRUE FALSE
Can do with a loop through 'abc' and explicitly creating new df columns, but wondering if some built-in method already exists in pandas. Number of possible values, and hence number of new columns is variable.
Thanks and regards.
In [31]: df.join(df.Letter.str.get_dummies())
Out[31]:
Position Letter a b c
0 1 a 1 0 0
1 2 b 0 1 0
2 3 c 0 0 1
3 4 b 0 1 0
4 5 b 0 1 0
or
In [32]: df.join(df.Letter.str.get_dummies().astype(bool))
Out[32]:
Position Letter a b c
0 1 a True False False
1 2 b False True False
2 3 c False False True
3 4 b False True False
4 5 b False True False